Monthly Archives: August 2018

Dichloroacetate (DCA) as an Oncology Chemotherapeutic Agent – What’s all the Hype and is it Warranted?

DOI: 10.31038/CST.2018341

Abstract

Cancer remains as one of the most challenging diseases to treat. However, this era has commenced with the introduction of novel drug treatments that are safer, and less toxic. The efficacy of a novel metabolic therapy, dichloroacetate sodium (DCA) was investigated.

27 solid-tumors were studied; 3 of 27 exhibited high or intermediate sensitivity to DCA as a single agent; 7 of 27 exhibited high or intermediate sensitivity to DCA in combination with chemotherapeutic agent(s). 9 of 27 exhibited no sensitivity to DCA as a single agent or in combination.

Clinical outcomes further validated the in vitro data.

Our findings indicate a potential role for DCA in oncology therapeutics in a wide range of cancer types. However, the diversity of the tumor responses among organ-specific cancer types underscores the necessity to conduct clinical studies on an individual basis rather than with a “one-size-fits-all” approach. The relative clinical safety, well- characterized pharmacodynamic profile, low side effects, and low cost of DCA further makes it an ideal candidate for development as an effective anticancer agent. Ideally, randomized controlled clinical trials should be designed to further correlate and validate this preliminary pilot study in the oncology setting and to fully appreciate the impact of DCA on cancer recurrence, response rates and survival rates.

Key Words

DCA, mitochondria, solid-tumors, oncology, chemotherapy, Warburg Effect

Introduction

Cytotoxic chemotherapeutic treatment regimens tend to be deleterious and toxic to cancer patients. Furthermore, these treatments often come with significant trade-offs: treatment may have to be halted because of cumulative toxicity; treatment may produce long-term complications; or the drug(s) that kill the cancer may permanently damage healthy organs [1] , or worse. Thus, today many clinicians are changing their clinical practices by opting for targeted and/or ancillary drug treatments that kill the tumor cell populations while sparing healthy cells, thus affording the patient a valuable quality-of-life.

It is known that greater than 70% of all cancer types rely on aerobic glycolysis for energy production, which is an inefficient means of generating ATP, a feature that becomes an advantageous biomarker. Aerobic glycolysis is a result of malfunctioning/hyperpolarized mitochondria. Cancer cells generally express increased aerobic glycolysis in the cytosol (Warburg Effect/lactic acid fermentation) [2] rather than oxidative phosphorylation (normal cells) for energy production,[3] thus producing excessive lactate and therefore inducing a low pH microenvironment [4].

In 2007, Drs. Archer and Michelakis from the University of Alberta, Canada, [5] decreed the use of Dichloroacetate (DCA) as a general use metabolic chemotherapeutic agent that could reverse this mitochondrial hyperpolarized state thus inducing cancer cells to undergo apoptosis.

The ability of DCA to decrease lactate production has been used for more than 30 years in the treatment of lactic acidosis in inherited mitochondrial diseases in humans [6] Lactic acidosis is a physiological condition characterized by low pH in the body tissues and blood accompanied by the buildup of lactate [7]. The condition typically occurs when cells become hypoxic thus impairing cellular respiration leading to the lower pH levels (acidosis). Simultaneously, cells are forced to metabolize glucose anaerobically, which leads to lactate formation. Therefore, elevated lactate is indicative of tissue hypoxia, hypoperfusion, manifesting in possible tissue damage [8]. The characteristics of mitochondrial diseases in humans are virtually identical to tumorigenesis, complete with the inefficient bioenergetic mitochondria. This property has led to trials of DCA for the treatment in humans presenting with a variety of cancers [9].

The generic drug sodium dichloroacetate (DCA) is an orally bioavailable small molecule that, by inhibiting pyruvate dehydrogenase kinase (PDK), increases the flux of pyruvate into the mitochondria, promoting glucose oxidation. This reverses the suppressed mitochondrial apoptosis in cancer cells and results in suppression of tumor growth in vitro and in vivo [6]. Thus, it would be reasonable to propose that cells with mitochondrial defects, or cells in a high glycolytic and hypoxic environment would likely be more sensitive to glycolytic inhibition by DCA. Therefore, a prospective study of the efficacy of DCA as a potential chemotherapeutic agent was conducted.

Materials and Methods

A variety of fresh solid tumor specimens (27) were procured from patients of a private clinic, Medicor Cancer Centres Inc. (Toronto, Ontario, Canada) The tumor specimens were either obtained from biopsies of superficial metastases, superficial lymph nodes infiltrated with metastases, or at the time of major cancer surgery. The tumor specimens were accredited by the attending pathologist to be comprised of tumor tissue. Patients were provided with a written informed consent to perform the CS/CR (chemosensitivity / chemoresistance) assay. The live tumor samples obtained were then mechanically disaggregated to obtain single-cell heterogenates (SCH). The SCH were then incubated at 360C / 5% CO2 for 48 hours in a humidified chamber to allow for equilibration. Following incubation, the SCH were washed, counted, and a small aliquot stained with trypan blue, to assess initial viability. Twenty thousand cells were added per analysis tube. The chemotherapeutic agents (obtained from Sigma-Aldrich; Selleck Chemical, and McKesson) were added at peak plasma concentrations (Cmax), plus/minus DCA (at peak plasma concentration/Cmax), and incubated at 360C / 5% CO2 for 72 hours in a humidified chamber. After 72 hours, the SCH were washed and tagged with green fluorescein LIVE/DEAD® Fixable Stains for Flow Cytometry (Molecular Probes). The reactive dye can permeate the compromised membranes of dead cells and react with free amines on the interior and exterior of the cell, whereas only membrane-exterior free amines of viable cells are available to react with the dye, resulting in intense or dim staining, respectively. SCH in vitro chemotherapy response was determined using a Becton Dickinson FACScan flow cytometer* and SCH analyzed for percentage of live versus dead cell populations against a live non-drug control. A dead cell control was also used consisting of SCH placed at 560C for 1 hour.

 *All specimens were high grade / metastatic tumors unless noted; no tumor was naïve; no tumor was a primary 10,000 events were counted for each SCH aliquot.

Results:

CST 2018-116_F1

CST 2018-116_F2

CST 2018-116_F3

Figure 1. Histograms/Graphs

Unless Noted: DCA inhibited the conventional therapeutic drug; or no synergy was noted with the conventional therapeutic drug; or if synergy was LDS; or inhibition of both agents when combined. This is noted by the Dark Colored Histograms.

Red Colored Histograms (X); Synergy (HDS) when conventional chemotherapeutic drug was combined with DCA

Blue Colored Histograms (X); Synergy (IDS) when conventional chemotherapeutic drug was combined with DCA

Note: 1) In our assay if percent kill was not > 33%, treatment was designated as LDS (Low Drug Sensitivity) and as such was not considered an efficacious treatment option; 34%-65% kill was designated as IDS (Intermediate Drug Sensitivity) a partial response may be obtained; > 66% kill was designated as HDS (High Drug Sensitivity) and a favorable response could be expected.

2) Definitions: Permissive: drug as a single agent is non-effective unless in combination with another agent; Additive: in combination the drugs produce a total effect the same as the sum of the individual effects; Synergy: in combination the drugs produce a total effect that enhance or magnify the sum of the individual effects; Inhibition: in combination the drugs produce a total effect that inhibits the sum of the efficacy of the effective drug(s).

Table 1. SAMPLE CLINICAL RESULTS: Previously Un-Published and Unrelated to Figure 1 Data

Total-27 solid-Tumors Sensitivity to DCA

Single Agent

Efficacy

Combination

Efficacy

11%

HDS

15%

HDS

15%

IDS

22%

IDS

33%

LDS/NONE

33%

LDS/NONE

11/27 Breast solid-Tumors Sensitivity to DCA

Single Agent

Efficacy

Combination

Efficacy

24%

HDS

15%

HDS

6%

IDS

24%

IDS

33%

LDS/NONE

33%

LDS/NONE

4/27 Colon solid-Tumors Sensitivity to DCA

Single Agent

Efficacy

Combination

Efficacy

0%

HDS

25%

HDS

25%

IDS

50%

IDS

0%

LDS/NONE

0%

LDS/NONE

  1. 32 year old male, leg melanoma, treated with wide excision and inguinal node dissection, local recurrence and progressive inguinal lymphadenopathy post-op while receiving natural therapy only, CT proven complete response to oral DCA therapy for over 3 yearswith no concurrent conventional therapies.
  2. 63 year old female, non-Hodgkins lymphoma treated with standard chemotherapy, marrow injury from chemo (stopped), progression while off treatment, CT-proven stable disease for 2 years while taking oral DCA and no concurrent conventional therapy.
  3. 80 year old male with transitional cell bladder carcinoma, recurrent disease after multiple resections and BCG, cystoscopy- proven tumour shrinkage with short course of oral DCA (6 weeks), re-treated after 1 year, delayed radical cystectomy for 4 years.
  4. 31 year old female with frontotemporal grade 3 astrocytoma transformed to glioblastoma, treated with debulking surgery followed by chemoradiation. Patient received DCA for 3 months following chemoradiation, with no concurrent chemotherapy, and no subsequent conventional therapy. Initial MRI appeared to show rapid progression with patient remaining asymptomatic. MRI deemed to reflect pseudoprogression. Patient had a complete response and remains alive and well 6 years post-treatment.
  5. 67 year old female with recurrent transitional cell bladder carcinoma following multiple TURBT procedures and intravesical chemotherapy. Treated with oral DCA 26mg/kg/day for 6 weeks on a cycle of 2 weeks on and 1 week off. DCA stopped due to neuropathy. Disappearance of recurrent solitary bladder tumour by pelvic ultrasound, confirmed by cystoscopy and repeated negative urine cytology reports. Patient remained clear at 6 months post-DCA therapy. Started low dose naltrexone combined with purified honokiol (magnolia extract) for recurrence prevention. Remains clear of bladder cancer 3 years following therapy.

Results/Discussion

Early carcinogenesis occurs in a hypoxic microenvironment and thus the transformed cells initially rely on aerobic glycolysis for energy production [4]. However, this early metabolic adaptation appears to also offer a proliferative advantage, suppressing apoptosis. Furthermore, the byproducts of glycolysis (i.e. lactate and acidosis) contribute to the breakdown of the extracellular matrix, facilitate cell mobility, and increase the metastatic potential [11]. Moreover, even though the tumors eventually become vascularized and O2 levels increase, the glycolytic phenotype persists, resulting in the ‘‘paradox’’ of glycolysis during aerobic conditions, the Warburg effect [2].

Aerobic glycolysis is a common metabolic alteration of tumor cells that results in overt lactic acid production, adapting the cells to tumor microenvironments and is necessary for their survival. Although lactate production results in less ATP per molecule of glucose, it has been shown that increased glycolysis and decreased oxidative phosphorylation may serve to increase the rate of ATP production without producing reactive oxygen species [2]. Indeed tumor cells do not suffer from ATP deficiency; in fact they generate more energy than normal cells, by increasing the level of glycolysis several-fold to support their enhanced growth and proliferation.12 It has also been shown that the Warburg effect is also involved in the avoidance of apoptosis [2]. Alternatively and paradoxically, the Warburg effect might serve to increase the biomass to provide nucleotides and lipid material necessary for rapidly dividing cells [13]. This theory is supported by the fact that signaling pathways such as AKT/mTOR, are known to play a role in biomass production, which also control aspects of the Warburg effect [13].

Moreover, it is well established that solid tumors tend to have a more acidic microenvironment than normal tissues [2]. Intracellular acidic water holds very little oxygen while an alkaline water micromilieu can hold large amounts of oxygen. It follows, then, that the more acidic the tumor cells, the less intracellular oxygen will be available. Thus this acidic phenotype would further support enhanced proliferation and hence tumorigenesis [15]. Indeed, it has been reported that due to this acidic milieu, an unusual reprogramming phenomenon will be the fate of some somatic cells. They can be drastically altered through changes and committed to a specific lineage and thus converted into a pluripotent state (capable of differentiating into nearly all cell types) when exposed to an environmental stress, in this case short exposure to low pH. This reprogramming process does not need nuclear manipulation or the introduction of transcription factors, thought to be necessary to induce pluripotency. This research group calls the phenomenon “stimulus-triggered acquisition of pluripotency” (STAP) [16].

Further support for tumors utilizing this bioenergetic inefficient, non-mitochondrial means of generating ATP has been shown by tumor cells exclusive expression of the embryonic M2 isoform of pyruvate kinase M2 which is necessary for aerobic glycolysis [14]. This unique phenotype provides a selective growth advantage for tumor cells in vivo and is associated with suppression of mitochondrial function and thus resistance to apoptosis, a further hallmark that characterizes cancer.

The Parra-Bonilla group demonstrate that pulmonary artery microvessel endothelial cells preferentially utilize glycolysis to generate ATP (Warburg effect), which may be necessary to sustain their growth and other rapidly growing untransformed cells [17]. Others have also demonstrated that AKT (Protein Kinase B, a serine/threonine-specific protein kinase that plays a key role in multiple cellular processes such as glucose metabolism, apoptosis, cell proliferation, transcription and cell migration). is activated by latent Kaposi’s sarcoma-associated herpes virus (KSHV) infection of endothelial cells [18,19]. KSHV infection of endothelial cells also activates hypoxia-induced factors HIF -1 and HIF-2 [19]. Further, AKT and HIFs have been shown to play prominent roles in the Warburg effect. During latent infection of endothelial cells, KSHV induces aerobic glycolysis and lactic acid production while decreasing oxygen consumption, leading to endothelial cell activation and thus angiogenesis promotion via the hypoxic milieu [20].

Lactic acidosis is characterized by tissue lactate levels of >5 mmol/L concurrently with serum levels of pH <7.35. [21]. Researchers at the University of Regensburg, Germany [22] show that intratumoral concentrations of lactic acid vary by tumor type as well as from tumor burden. They collected serum of 160 patients suffering from different malignancies and determined that patients with high tumor burden indeed present with a significant increase in serum lactate levels. Furthermore, since a characteristic feature of the tumor environment is local acidosis, they investigate the direct effect of lactic acid on T-cell proliferation, showing lactic acid inhibits T-cell proliferation as well as an intracellular increase concentration of lactic acid in the T-cell itself of10–20 mmol/L [22].

Taken in totality, it appears that virtually all cells associated with the tumor microenvironment play prominent roles in the Warburg effect.

But, Michelakis et al, demonstrate that this metabolic-electrical remodeling is an adaptive response and thus reversible. Since cancer cells are relatively deficient in Kv channels, [5,11] one could reverse the suppression of PDC (pyruvate dehydrogenase complex) activity, and thus increase apoptosis. The metabolic and the apoptotic pathways converge in the mitochondria and thus not independent from each other and therefore the glycolytic phenotype is associated with a state of apoptosis resistance [23].

Many glycolytic enzymes have been recognized to also regulate apoptosis, and several oncoproteins also induce the expression of glycolytic enzymes [24]. For example, AKT, which stimulates glycolysis and induces resistance to apoptosis, activates hexokinase, an enzyme catalyzing the first and irreversible step in glycolysis [25]. Via its downstream mediator glycogen synthase kinase 3 (GSK3), AKT induces the translocation of hexokinase to the mitochondrial membrane where it binds to the voltage-dependent anion channel (VDAC), suppressing apoptosis [25]. Inhibition of GSK3 in cancer cells causes unbinding of hexokinase from VDAC, induces apoptosis, and increases sensitivity to chemotherapyv [26].

DCA enters the cancer cell switching cancer promoting/inhibiting genes on or off including mtDNA. However, it appears that DCA requires an ectopic membrane transporter protein called SLC5A8 to enter the cancer cells. SLC5A8 mediates acetate transport in a Na+-coupled manner, with the affinity of dichloroacetate for the transporter ~45-fold higher than that of Na+, (dichloroaceate/ Na+ stoichiometry for the transport process is 2: 1.) [27]. When it does so, it restores mitochondrial function by reversing the ionic remodeling of hyperpolarized mitochondria, thus restoring apoptosis, allowing cancer cells to commit “suicide” which results in tumor shrinkage. Indeed, it has been shown that DCA does have broad spectrum anticancer properties with minimal toxicity in animal models, and has efficacy in humans including the treatment of glioblastoma (by virtue of its ability to cross the blood-brain barrier). DCA causes depolarization of mitochondria in GBM tissue but not in healthy brain tissue, as this tissue possesses ectopic expression of the SLC5A8 transporter [28].

Several studies have shown that DCA induces apoptosis, in a variety of cancer cell lines and as the mitochondria-K+ channel axis is suppressed in cancer and its normalization promotes apoptosis and inhibits cancer growth [29–31]. However, a recent investigation was not able to confirm these findings [32]. In correlation with our pilot studies we also observed that even though DCA was able to induce mitochondrial depolarization (Figure 2), we observed highly variable induction of apoptosis or necrosis when DCA was used as a single agent, or even as a chemosensitizer (Figure 1). Nonetheless, long and continuous in vivo exposure may be required as demonstrated by Bradford and Khan [33] and/or DCA may cause cell growth inhibition without causing apoptosis [34] and hence account for minimal in vitro results noted in the third decade (apoptosis) and thus account for the clinical ‘stable disease’ case noted above(as well as other unpublished cases observed at Medicor Cancer Centres)

Reversal of the glycolytic phenotype by dichloroacetate inhibits metastatic breast cancer cell growth in vitro and in vivo [35]. This would not be detected by the ChemoFit assay. We show that DCA selectively targets cells with defects in the mitochondrial and could demonstrate apoptosis or necrosis when DCA was combined with conventional chemotherapies thus acting as a chemosensitizer inducing synergistic effects on various tumor types. Moreover, Stockwin et al [32] demonstrate that a very high concentration of the compound (≥25 mM) was required to induce apoptosis, wherein our studies incorporated peak plasma concentrations as well as exposure time of the SCH to DCA was 72 hours and not beyond. A limiting factor in the study is the use of “fresh” tumor cells (not cell lines) and thus the inability to use cultures for extended periods of time, which would be required to measure growth inhibition.

CST 2018-116_F4

Figure 2. “X” scale – logarithm – fluorescence intensity spanning four decades (a 10,000-fold range)

“Y” scale – logarithm – cell Number

EXAMPLE-When live tumor cells are run through the flow cytometer without any drugs added, the histogram exhibits a peak in the 100–102 as noted in “A” the “ghost” peak; whereas if DCA is added to the aliquot of live tumor cells, the peak becomes very narrow, less ‘choppy’, and falls square in the middle of the 2 decades, as noted in “B” the “solid” peak– indicating reversing of the hyperpolarized mitochondria – the cell populations are “healthier?” [Unpublished Data]

A 1982 and a 1988 paper by Chen, et al. show that rhodamine 123 accumulates by various cancers and normal cells. The rhodamine 123 molecule, carries a net positive charge, and as such is accumulated and retained in areas of the cell that are more negatively charged in greater amounts and for longer periods of time than in less negatively charged areas [34–35]. Thus, retention of Rh123 in the mitochondria of many carcinomas suggests that the mitochondria in such cells are hyperpolarized. Due to this biochemical property, Chen points to two types of cancer that do not retain Rh123, sarcoma and oat cell lung cancer (SCLC). The 1988 paper also mentions as exceptions “large cell carcinomas of the lung” and “poorly differentiated carcinoma of the colon.” This is not definitive since there is certainly much variation among all types of cancer cells, but in light of the data contained in the Chen papers, and given the importance of the normalization of mitochondrial membrane potential to the apoptosis-inducing mechanism described by Michelakis, [36] it seems reasonable to assume that sarcomas, and small cell lung cancers are unlikely to respond to DCA and perhaps partially explain the results of our current study. However, in clinical practice of using DCA for over 7 years, Khan has observed both sarcoma and small cell lung cancers respond well (unpublished data), again highlighting the variability of individual tumor behaviors and the need to individualize therapy. Although neurotoxicity is a known and rather common side-effect and was indeed noted in the patients, it was reversible upon withdrawal of the drug or when treated with natural neuroregenerative medicinessuch as lipoic acid and B vitamins

Many of the patients who supplied tumours listed in Fig 1 could not be followed to determine if the in vivo responses matched the in vitro results noted above. The reasons were:

  1. the patient’s condition changed, and they were unable to take chemotherapy,
  2. the patient’s oncologist refused to prescribe the assay-guided therapy,
  3. the patient was lost to follow-up.

Since DCA had been used for years to treat rare metabolic disorders and was known to be relatively safe, [6] the potential existed for rapid translation of these findings to clinical use in the oncology setting. However, our pilot studies using DCA to restore normal generation of ATP and therefore reverse the resistant apoptosis phenotype, show that most of the tumors did not respond to DCA as a single agent or in combination with conventional agents. 3 of 10 breast cancer subtypes had intermediate or high sensitivity to DCA as a single agent, DCA also exhibited high efficacy when combined with various chemotherapeutic agents in the same 3 breast tumors. We noted 1 of 4 colon cancer subtypes had intermediate sensitivity to DCA as a single agent, and the only bile duct cancer tested had high sensitivity to DCA as a single agent.

Actually our data indicates that DCA inhibited the sensitivity of many of the conventional agents used including those used on breast and brain tissue that we hypothesized would be effective as noted above by other research groups. It should also be noted that although we analyzed “fresh” tumor tissue and any components associated with the micromilieu, many research groups tested DCA on human cells cultured outside the body and found that it killed lung, breast and brain cancer cells, but not healthy cells [29–32]. The issue of using fresh tissue versus cells lines; cells in cultures always present with concern and relevance. Cell lines are homogeneous rather than representing the heterogenic milieu of a specific patient’s tumor mass. As such, results for a given therapeutic agent(s) may not represent the individual‘s specific response and actually may reflect false positive or false negative effects. Further, allowing cells to proliferate in vitro does not represent the original tumor mass and thus not reflect in vivo response dynamics.

As mentioned, not all of the tumors responded to DCA as a single agent or in combination with conventional agents. There are several possible explanations for this. It is possible that the resistant tumors do not express the membrane transporter protein SLC5A8. It is known to be silenced in many tumors and not ectopic, which has been shown to be required for DCA entry into the cancer cells [28]. The tumor specimens analyzed were high grade / metastatic tumors and hence had prior exposure, if not multiple exposures, to drugs and radiation prior to analyses. It is also possible that the tumors had developed cross resistance to DCA as a result of prior treatment with multiple cytotoxic agents. It has also been shown that when the tumor bulk has not been effectively eradicated, the risk of recurrence and metastasis is high, [37] hence, the efficacy of DCA may be higher when it is administered in patients with low tumor burden. Thus, as mentioned above, most of our patient population was of high tumor burden explaining our subdued results. Another conjecture is that certain tumors may be able to utilize alternate fuels to generate ATP when glycolysis is shut down by DCA (e.g. ketone bodies or free fatty acids). Moreover, a limitation of the assay is based on altered cell membrane permeability but the initial site of cellular damage caused by some toxic agents is intracellular. Therefore, cells may be irreversibly damaged and committed to die, while the plasma membrane is still intact. Thus this assay could underestimate cell death. Despite this fact, these types of assays are widely used, accepted and correlate with clinical outcomes [38]. Finally, if DCA is cytostatic (growth inhibition without apoptosis) as shown by Blackburn’s group, [36] instead of cytolytic/cytotoxic, a cell death assay will not detect this influence [37, 39, 40].

Conclusion

Despite the challenges that remain in treating cancer, this era has commenced with the introduction of novel drug treatments that are safer, and less toxic. Thus, many clinicians are changing their clinical practices by opting for these “gentler” “targeted” treatments that kill the tumor cells and leave normal cells unaffected. Furthermore, it appears that with the advent of targeted therapies, and the prediction that individualizing therapy is now an appropriate method for treating cancer, many physicians are now realizing the value of CS/CR testing, and advocating its use to guide them in choosing a chemotherapeutic regimen. Microscopic histological “sameness” does not equate to tumor genetic, epigenetic and phenotypic “sameness”. Indeed, the characteristics and behavior of specific cancer types differs widely from individual-to-individual [12]. However, It can be deduced that since tumor evolution is likely to be non-linear, and substantial genetic heterogeneity is expected in tumor cell populations, this heterogeneity will be reflected epigenetically and hence may be treated in-vivo by in-vitro guidance assays. This forms the basis of individualized/personalized medicine, in which one takes the diagnostic information from a person’s own cancer to develop a highly individualized treatment for a given cancer patient, rather than relying on the challenge of empiric “one-size-fits-all” treatment modalities [10].

Since DCA had been used for years to treat rare metabolic disorders and was known to be relatively safe, [6] our data demonstrates the potential for rapid translation into clinical practice. It becomes central to develop new agents that effectively kill the cancer cells and overcome drug resistance associated with hypoxia and mitochondrial respiratory defects. Furthermore, these agents should favor cytolysis rather than cytostatic effects, so that tumor cell populations are actually killed and not merely “dazed”, if one is to achieve totally eradication of the tumor. However, if the anticancer agent is cytostatic, long-term use may still yield acceptable clinical outcomes and augmented survival rates keeping the patient in a chronic “stable” state.

Simultaneously, controlled clinical trials of DCA must be conducted to thoroughly delineate the value of DCA in cancer treatment. It is apparent that empirically-selected chemotherapy has tremendous room for improvement, since the published response rates are low in many types of cancers especially if metastaticb [39] The identification and stratification of patients to predict DCA benefit and response can easily be performed in vitro, prior to in vivo administration [40]. Toxicity is the main reason for the high failure rate (40–50%) [39] (and acquired resistance), of chemotherapeutic interventions thus, predicting how the individual oncology patient will respond to DCA (and other agents) and differentiating between direct and indirect effects [40] may be challenging but is certainly not insurmountable. Personalized treatment remains the current endeavor as improperly treated cancer takes a huge toll on our healthcare system and, more importantly, on the lives of patients and their families. Improving response rates and survival must be a priority. Thus, the initiation of new focused clinical trials containing strong correlative science components on a range of cancer patients becomes fundamental.

Abbreviations

IDC=invasive ductal carcinoma,

NSCLC= non-small cell lung cancer,

*chlor-Chlorambucil;

ix-Ixempra;

lap-Lapatinib;

lom-Lomustine;

TMZ-Temozolomide;

eto-Etoposide;

met-Metformin;

riba-Ribvirin;

rapa-Rapammune;

tam-Tamoxifen;

cis-Cisplatin;

tar-Tarceva;

MTX-Methotrexate;

dox-Doxorubicin;

tax-Taxol;

fem-Femara;

chlor-Chloroquine;

FU-Fluorouracil;

mito-Mitomycin;

vin-vinblastine;

carbo-Carboplatin;

gem-Gemcitabine;

nav-Navelbine;

iri-Irinotecan;

oxi-Oxilaplatin;

HD-High Drug Concentration = 10X Peak Plasma Concentration;

LD = Low Drug Concentration = 50% Peak Plasma Concentration

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Analysis of Clinical Features and Risk Factors of Death in Patients Admitted to Hospital with Acute Mushroom Poisoning: A Retrospective Analysis of 315 Cases

DOI: 10.31038/JCRM.2018123

Abstract

Aim: To review the clinical features and identify mortality risk factors of patients admitted to hospital for acute mushroom poisoning (AMP) .

Methods: We retrospectively analyzed a database of 315 patients who underwent acute mushroom poisoning between September 2003 and December 2017 at our hospital. The patients were divided into the survival group (n = 272) and death group (n = 43) based on the prognosis. Multivariate logistic regression was used to evaluate the risk factors associated with death.

Results: Overall, 315 cases were enrolled into the statistical analysis. The average age of them was 40.66 ± 20.86 years and there were 193 (61.27%) male. Patients with latency of 6–24 hours had a higher rate of composition (54.60%) and mortality (11.75%) . Liver was the most commonly involved organ (152/523, 29.06%) and patients with liver damage had the highest mortality (40/315,12.70%) . There was significant relationship between the number of organs involvement and mortality rate. Three or more organs damage could obviously increase mortality rate (P﹤0.05) . Compared with survival group, patients in death group had higher levels of alanine aminotransferase (ALT) , total bilirubin direct (TBIL) , direct bilirubin (DBIL) , prothrombin time (PT) , activated partial thrombin time (APTT) , creatine kinase MB (CK-MB) , myoglobin (Mb) , lactate dehydrogenase (LDH) and lower levels of albumin (ALB) and sodium (Na+) (P < 0.05) . ALT ≥ 200U/L, PT ≥ 20s and ALB≤30g/L were identified as independent risk factors of the death in AMP (P < 0.05) .

Conclusion: We found that the number of organs involvement, ALT ≥ 200U/L, PT ≥ 20s and ALB≤30g/L were significantly associated with mortality. Clinicians should be aware the dynamic changes in the above factors so that they can be detected early and treated as soon as possible.

Key words

acute mushroom poisoning; survival group; death group; clinical features; risk factors; multiple organ dysfunction syndrome; retrospective analysis

Introduction

Poisonous mushroom has many types, colors, sizes and morphologies. It is difficult to visually distinguish it from edible mushrooms. Therefore, AMP is a common phenomenon. Some poisonous mushrooms are rich in toxins, which are heat stable and not inactivated by cooking .The chemical structure of toxins is similar to the herbicides diquat and paraquat, they can lead to nausea, vomiting, abdominal pain, diarrhea and it can even make the disease progress rapidly and cause multiple organ dysfunction syndrome (MODS) to death [1,2]. Amanita poisoning has long been a worldwide problem, because it accounts for about 90% of fatality[3]. The lethal dose of α-amanitin is very low, only 0.1mg / kg, and some mushroom can contain up to 15 mg. That’s one of the reasons why the mortality of α-amanitin is high and it’s known as the most poisonous toxins [4,5]. It had been reported that there were 50 to 100 deaths in Western European countries each year, and it was relatively rare in the United States, but there were also approximately 100 deaths in five years [6,7]. In China, the mortality of AMP is still high even as high as 21.2% and there are no special antidotes [8,9]. Although the disease has a high mortality rate, at present, most articles on AMP are case reports or series, and limited data exist on the clinical characteristics and possible mortality risk factors of patients admitted to hospital for AMP. To better identify the disease clinical features that are related to the fatal outcome of AMP patients admitted to hospital , we collected clinical data of 315 AMP patients admitted to our hospital from September 2003 to December 2017 and analyzed the clinical features and risk factors of the death, based on data from the initial admission.

Materials and Methods

Participant enrollment and inclusion/exclusion criteria

The patients who were diagnosed as AMP in our hospital between September 2003 and December 2017 were enrolled in the retrospective study. All these patients were included in the study according to the following inclusion: (1) . They had a clear history of eating wild poisonous mushrooms and duration did not exceed three days. (2). Co-fed persons had different symptoms of poisoning, while others had not. (3) . They all had relevant laboratory abnormalities. (4) .Clinical datas were complete and successfully received follow-up for at least six months. The patients with history of related diseases including drugs of abuse, viral hepatitis, glomerulonephritis or other which could lead to liver, kidney and other organs damage were excluded from this study. This study strictly followed the ethical principles of human medical research in the Declaration of Helsinki and was approved by the hospital ethics committee and obtained the informed consent of all patients or their relatives.

Diagnostic criterias for organs involvement

The diagnostic criterias for organs involvement were as follows: (1). Elevated alanine aminotransferase ( ≥ 200 U/L) six-fold greater than the upper limit of normal concentration (5~35 U/L) , and/or the presence of total bilirubindirect ( ≥ 35umol/L) (normal range:0~27 umol/L), both of them were defined as liver damage. (2) Increased prothrombin time ( ≥ 20s) (normal range:0~14 s) and/or activated partial thrombin time ( ≥ 40s) (normal range:20~40 s) was considered to be coagulation abnormalities. (3). Elevated creatine kinase MB ( ≥ 5ug/ml) (normal range: 0.01–4.94 ng/ml) was defined as heart involvement. (4) . Increased creatinine ( ≥ 160umol/L) double than the normal concentration (normal range:45–84 umol/L) was considered to be kidney involvement. (5). The presence of relevant symptoms and/or signs (delirium, coma, twitch and irritability) was defined as damage to nervous system. (6). The appearance of abdominal signs and increased serum amelase ( ≥ 300 U/L) three-fold greater than the upper limit of normal concentration (28–100 U/L) , and/or videography showed pancreatitis, both of them were defined as pancreas damage.

Collection of clinical information

The data we collected including gender, age, duration of hospitalization, latency period, laboratory indicators (including blood routine indexes, liver function indexes, renal function indexes, coagulation function indexes, myocardial injury markers, electrolytes indexes) and prognosis.

Statistical analysis

All statistical analyses were performed using SPSS version 22.0 for Windows (SPSS Corp, Chicago, IL, USA) . Kolmogorov-Smirnov test was used to test the normality of measurement data. Normal distribution data were expressed as the mean ± standard deviation (SD) . Inter-group comparisons of continuous variables were performed by a 2-sample t-test or t’ test when the variance was uneven. While non-normal distribution of measurement data were described using median and interquartile range (IQR) values and rank sum test was used to compare the difference between the two groups. Frequencies and percentage were used to indicate categorical variables, and inter-group comparisons were performed by Chi-square test. To identify independent factors associated with death, explanatory items were selected using univariate analysis, followed by multivariate logistic regression. We considered p values less than 0.05 as statistically significant.

Result

1. Baseline clinical features of all patients with acute mushroom poisoning

During the study period, a total number of 315 patients were enrolled, including 272 (86.35%) survival cases and 43 (13.65%) death cases. Among all the patients, 193 (61.27%) were male. The mean age was 40.66 ± 20.86 (range, 1- 92) years. Table I shows the clinical baseline datas of all patients. The mean value of first recorded laboratory indexes were as follows: ALT 111.50 (26.1, 1087.40) U/L, TBIL 19.70 (11.70, 38.70) umol/L, ALB 44.90 ± 7.39 g/L, PT 14.20 (12.70,19.40) seconds, APTT 35.00 (30.20,45.00) seconds, CK-MB 1.54 (0.52,3.71) ng/m, LDH 340.20 (211.40,875.80) U/L and Na+ 136.31 ± 5.93 mmol/L.

Poisonous mushroom’ colors are varied. For the specific shapes of them, such as wearing “hat”, waist “skirt”, wearing “shoes”, patients could not describe clearly. The intake amount was not equal, ranging from 20–500g. Regional distribution was significantly different, mostly in Sichuan, Yunnan and Guizhou province. Most patients were collective disease, while a small number of them was single.

2. Multiple organ involvement of all the patients

Liver (152 / 523, 29.06%) was the most affected organs, followed by heart (134 / 523, 25.62%) and coagulation system (107 / 523, 20.46%) (Figure. 1A) . The patients with liver damage had the highest mortality (40 / 315, 12.70%) , then followed by coagulation disorders (35 / 315, 11.11% ) and heart damage (34/315, 10.79%) , respectively (Figure. 1B) . In addition, the more affected organs or systems, the higher mortality rate (0.00%, 5.36%, 7.69%, 21.95%,47.37%, 53.85%). The mortality of patients with four organs damage was higher than those who had three organs damage (47.37% vs. 21.95%; P < 0.05), and the latter is higher than that of patients with two organs damage (21.95% vs. 7.69%; P < 0.05) (Figure.1C) .

3. Comparisons of clinical factors and outcomes in acute mushroom poisoning

Late onset (latent period was 6–24 hours) (86.05% vs. 49.63% ) was more common in death group and a total of 37 (11.75%) patients became dead. According to data analysis, patients in death group had higher levels of ALT (P < 0.001) , TBIL (P = 0.002) , DBIL (P < 0.001), PT (P < 0.001) , APTT (P < 0.001) , CK-MB (P < 0.001) , Mb (P < 0.001) , LDH (P < 0.001) and lower levels of ALB (P = 0.001) and Na+ (P < 0.001) . Table I summarizes the patients’clinical data and outcomes of AMP.

4. Risk assessment of clinical features associated with the death of acute mushroom poisoning patients

Univariate logistic regression indicated that whether or not to adjust related confounding factors (age, gender and latency) ,WBC ≥ 12×109/L,ALT ≥ 200 U/L, TBIL ≥ 35umol/l, DBIL ≥ 20umol/l, ALB≤30g/L, PT ≥ 20s, APTT ≥ 40 s , CK-MB ≥ 5 μg/L, MB ≥ 140 μg/L, LDH ≥ 500 U/L and Na+≤135 mmol/L were signifcantly associated with death in AMP (Table II) . The above indicators were all included in the multivariate regression analysis, results showed that only ALT ≥ 200 U/L (OR = 4.50, 95%CI:1.01–20.10, P = 0.049) , PT ≥ 20s (OR = 6.14, 95%CI:1.61–23.41, P = 0.008) and ALB≤30g/L (OR = 5.78, 95%CI:1.05–31.98, P = 0.044) were identified as independent risk factors for death. Among them PT ≥ 20s had the highest lethal risk and increased the risk of death by 5.14 times.

JCRM 2018-108_F1

Figure 1. (A) Composition ratio of organ damage in patients with acute mushroom poisoning. They were 29.06%, 25.62%, 20.46%, 15.68%, 7.07%, 2.49%, respectively.

(B) The comparison of organ damage in patients with different prognosis.

(C) Relationship between organ damage and mortality rate. The number of organs damage from one to four, mortality rates were 0.00%, 5.36%, 7.69%, 21.95%, 47.37%. *P < 0.05 was considered statistically significant.

Table I. The clinical baseline datas of 315 patients with acute mushroom poisoning

Parameters

Total (n = 315)

Survival (n = 272)

Death (n = 43)

P value

Male , n (%)

193 (61.27%)

163 (59.93%)

30 (69.77%)

0.218

Age , years

40.66 ± 20.86

40.46 ± 20.16

41.95 ± 25.04

0.710

Latent period, n (%)

 < 0.001

 < 6 hours

125 (39.68%)

120 (44.12%)

5 (11.63%)

6–24 hours

172 (54.60%)

135 (49.63%)

37 (86.05%)

>24 hours

18 (5.71%)

17 (6.25%)

1 (2.33%)

White blood cell (×109/L)

11.56 ± 5.77

11.03 ± 5.24

14.81 ± 7.43

0.002

Red blood cell (×1012/L)

4.81 ± 0.79

4.78 ± 0.79

5.04 ± 0.69

0.043

Alanine transaminas (U/L)

111.50 (26.1,1087.40)

67.20 (23.60,796.98)

1383.00 (342.10,2691.50)

 < 0.001

Total bilirubin (umol/L)

19.70 (11.70,38.70)

17.35 (10.98,32.78)

48.20 (22.50,75.10)

0.002

Direct bilirubin (umol/L)

7.0 (3.9,21.00)

6.20 (3.70,13.18)

36.00 (14.10,56.70)

 < 0.001

Albumin (g/L)

44.90 ± 7.39

45.10 ± 22.56

40.82 ± 7.98

0.001

Prothrombin time (s)

14.20 (12.70,19.40)

13.85 (12.50,17.00)

28.20 (17.40,67.80)

 < 0.001

Activated partial thrombin time (s)

35.00 (30.20,45.00)

34.20 (29.13,39.78)

57.30 (41.00,76.30)

 < 0.001

Creatine kinase-MB (ng/ml)

1.54 (0.52,3.71)

1.24 (0.45,3.02)

3.71 (1.48,15.32)

 < 0.001

Myoglobin (ng/ml)

69.22 (39.44,181.36)

62.83 (37.99,157.30)

163.00 (77.22,982.09)

 < 0.001

Lactate dehydrogenase (U/L)

340.20 (211.40,875.80)

289.15 (203.25,609.63)

1083.70 (492.60,2987.80)

 < 0.001

Sodium (mmol/L)

136.31 ± 5.93

136.88 ± 5.58

132.76 ± 6.85

 < 0.001

Table II. The risk factors of death in acute mushroom poisoning analyzed by univariate logistic regression

Parameters

Occurrence rate No. (%)

Unadjusted

Pa value

Adjusted

Pb value

Survival (n = 272)

Death (n = 43)

OR [95% CI]

OR [95% CI]

Age ≥ 16years

221 (81.25%)

32 (74.42%)

0.67 (0.32–1.42)

0.295

Male (n/%)

193 (61.27%)

163 (59.93%)

0.65 (0.32–1.30)

0.218

Latent period ≥ 6h

152 (55.88%)

38 (88.37%)

6.00 (2.29–15.71)

 < 0.001

White blood cell ≥ 12×109/L

84 (30.88%)

25 (58.13%)

3.11 (1.61–6.00)

 < 0.001

2.88 (1.46–5.70)

0.002

Red blood celll ≥ 5×1012/L)

109 (40.07%)

26 (60.46%)

2.29 (1.19–4.42)

0.012

2.03 (0.99–4.16)

0.054

Alanine transaminas ≥ 200U/L

103 (37.86%)

40 (93.02%)

21.88 (6.60–72.53)

 < 0.001

11.65 (3.95–34.35)

 < 0.001

Total bilirubin ≥ 35umol/L

62 (22.79%)

29 (67.44%)

7.02 (3.49–11.10)

 < 0.001

5.26 (2.57–10.80)

 < 0.001

Direct bilirubin ≥ 20umol/L

66 (24.26%)

33 (76.74%)

10.30 (4.82–22.02)

 < 0.001

6.17 (2.98–12.78)

 < 0.001

Albumin≤30g/L

7 (2.57%)

5 (11.62%)

4.98 (1.51–16.49)

0.004

5.18 (1.46–18.43)

0.011

Prothrombin time ≥ 20s

43 (15.80%)

29 (67.44%)

11.03 (5.39–22.58)

 < 0.001

15.81 (6.80–36.73)

 < 0.001

Activated partial thrombin time ≥ 40s

38 (13.97%)

29 (67.44%)

12.76 (6.18–26.31)

 < 0.001

9.07 (4.04–20.37)

 < 0.001

Creatine kinase-MB ≥ 5ng/ml

37 (13.60%)

20 (46.51%)

5.52 (2.76–11.04)

 < 0.001

4.26 (2.05–8.84)

 < 0.001

Myoglobin ≥ 140ng/ml

73 (26.83%)

23 (53.48%)

3.14 (1.63–6.04)

 < 0.001

2.14 (1.08–4.23)

0.029

Lactate dehydrogenase ≥ 500U/L

78 (28.67%)

32 (74.41%)

7.24 (3.47–15.07)

 < 0.001

5.60 (2.64–11.88)

 < 0.001

Sodium≤135mmol/L)

74 (27.20%)

26 (60.46%)

4.09 (2.10–7.97)

 < 0.001

3.17 (1.59–6.34)

0.001

Abbreviatoins: OR, odds ratio; CI, confidence interval;

a Univariate analyses (Continuity correction χ2 test) were performed to evaluate the risk factors associated with death. Unadjustment of age, gender and latent period, P < 0.05 is considered statistically significant.

b Adjustment of age, gender and latent period, P < 0.05 is considered statistically significant.

Table III. The independent risk factors of death in acute mushroom poisoning analyzed by multivariate logistic regression

B

S.E.

Wald

Exp (B)

95% C.I

P value

Latent period ≥ 6h

.95

.56

2.81

2.57

.85

7.78

0.094

White blood cell ≥ 12×109/L

.83

.47

3.13

2.28

.92

5.69

0.077

Alanine transaminas ≥ 200U/L

1.50

.76

3.88

4.50

1.01

20.10

0.049

Total bilirubin ≥ 35umol/L

-.11

.85

.02

.90

.17

4.76

0.901

Direct bilirubin ≥ 20umol/L

.26

.91

.08

1.30

.22

7.72

0.777

Albumin≤30g/L

1.76

.87

4.04

5.78

1.05

31.98

0.044

Prothrombin time ≥ 20s

1.82

.68

7.08

6.14

1.61

23.41

0.008

Activated partial thrombin time ≥ 40s

-.26

.74

.13

.77

.18

3.29

0.723

Creatine kinase-MB ≥ 5ng/ml

-.35

.61

.33

.70

.21

2.32

0.564

Myoglobin ≥ 140ng/ml

.41

.54

.58

1.51

.53

4.31

0.447

Lactate dehydrogenase ≥ 500U/L

.19

.54

.13

1.21

.42

3.48

0.724

Sodium≤135mmol/L)

.49

.43

1.28

1.63

.70

3.80

0.259

Discussion

Mushrooms are widely distributed in the world, their species are more than 5000, of which 50 to 100 species had been identified as toxic species, including more than 30 species could cause human death [10]. Mushroom poisoning mortality is up to 21.2% and this study described a mortality of 13.7%, indicating that it has become one of the most important causes of death [11]. The prognosis of patients with AMP was very different, and may be influenced by many factors, such as the types of poisonous mushrooms, toxin dose, clinical phenotype, laboratory indexes, medical treatment and hemodialysis and so on [12,13]. Yilmaz et al.[14] also suggested that white poison umbrella intake dose was closely related to the severity of the disease. Basing on the clinical characteristics of patients admitted to hospital for AMP, we mainly analyze the risk factors of death, to lay the foundation for guiding clinical treatment.

Different structures of poisonous mushrooms contain different concentrations of toxins, they can accumulate in different organs, making it difficult to detect in blood or urine [14,15], so, we can’t accurately analyze poisonous mushrooms’ species and toxins in our study. According to previous study, Cevik ea tl.[16] reported that age was closely related to the mortality of mushroom poisoning and they thought organ function of the elderly gradually depletes, so that it was difficult to tolerate toxins to death. Schmutz et al. [17] found that children who were younger than 6 years old were more prone to poisoning, but they did not specifically analyze the relationship between age and mortality. In our study, there were no significant differences in age between the two groups. The reason may be that we only compared the differences between children and adults and did not divide them more specifically. In terms of gender, Yardan et al. suggested that there were more women in the poisoning case than men, but some author described that males were more susceptible to toxins [7,18,19]. We also revealed that the ratio of male to female was 1.34: 1, however, gender differences have no effect on prognosis in AMP.

The clinical classification of mushroom poisoning varies greatly at home and abroad, and clinical types may overlap, there is still much controversy over the existence of hybrids. So far, there is no definitive guideline or consensus to define their classification accurately. Diza ea tl.[20] divided it into three types: early onset ( < 6 hours) , late onset (6 ~ 24 hours) and delayed onset (> 24 hours) . As already reported, latent period was crucial for the prognosis, but it was not a specific predictor [21,22]. In general, early-onset has the highest survival rate , but late-onset has the highest mortality rate, it can easily lead to liver and kidney failure [22,23]. At the present study, we inferred that late onset had the highest incidence and mortality, based on it, we conducted univariate logistic regression analysis, showing that the incubation period which was greater than or equal to 6 hours was indeed one of the risk factors for toadstool poisoning to death. Clinicians should pay attention to such patients early and adequately.

Liver is the most important organ in patients with AMP, accounting for 29.06% in all organ or system involvement, this finding is consistent with previous literature [24]. The mortality of liver failure is relatively high, it was 12.70% in this study, however, past literature reported that it was as high as 50% to 90% [25]. The reason may be that difference in evaluation criteria of liver damage can leads to difference in mortality, and widespread use of blood purification may effectively reduce mortality, but, so far, the most effective method to rescue liver failure is still liver transplantation [26]. Heart damage is also common, death group had high level of CK-MB, but it was within the normal range and logistic regression analysis showed that it had no effect on prognosis. The possible reason is that the effect of poisonous mushrooms on the cardiovascular system was mainly reflected in the abnormal electrocardiogram and blood pressure, as Ali [27] said. So the markers of myocardial injury are often normal and not a risk factor for death.

In our study, most patients have more than two organs or systems damage. Therefore, we hypothesized that there was a link between the number of organs damage and mortality rate. Finally, the results confirmed that the number of organs damage from one to four, the mortality were 5.36%, 7.69%, 21.95%, 47.37%. A small number of patients have five or six organs damage, so the mortality has not been counted. Three or more organs damage could obviously increase mortality rate, thus, early assessment of organ damage by clinicians has a positive effect on guiding clinical outcomes.

For the analysis of risk factors of experimental indicators, first of all, we compared the level of each index of two groups and select the index of difference statistically, excluding some of the error caused by unpredictable factors and selecting an appropriate range for logistic regression analysis, respectively. Because ALT mainly exists in the cytoplasm of hepatocytes and can be more sensitive to the damage of liver function and combined with changes in coagulation parameters, we found that when the ALT was less than 200 U / L, the changes of PT and APTT were not obvious. While it was more than 200 U / L, the changes of all of them were almost the same. Therefore, ALT ≥ 200 U / L for prognosis of AMP patients have a very important guiding significance. In our study, ALT in death group was significantly higher than survival group, 143 (45.40%) patients had the ALT of more than 200 U / L, including 103 (37.86%) cases in survival group and 40 (93.02%) cases in death group. The multivariate logistic regression analysis showed ALT ≥ 200 U / L was the independent risk factors of the death in AMP. However, Bita et al. [28] suggested that even though ALT increased to more than 10 times of normal limits, it played no role in prognosis. The hepatotoxicity mechanism may be that metabolite of toxins, not the toxins, can binds to hepatocyte DNA-dependent RNA polymerase II and terminates intracellular protein synthesis, ultimately leading to cell death and releasing ALT [29,30,31]. Therefore, in order to prevent the occurrence of the risk factors of death, we can start from the mechanism to study the treatment.

Liver is a major site for the synthesis of many clotting factors in the human body and hepatic damage can be associated with irreversible coagulation abnormalities [32]. In our study, 107 (33.97%) patients had coagulation disorders, with prolonged PT and APTT, which was consistent with the conclusion that Trabulus et al. and Bita et al. proposed [28,33]. But not the same, they thought that both of them were closely related to death, however, we only confirmed that PT ≥ 20s was independently associated with death in AMP. Also, liver plays an important role in the synthesis of albumin. Ahishali ea tl.[34] found that toxins inhibit protein synthesis and cause hepatocyte necrosis, even lead to death. Our present study showed that albumin level in death group (40.82 ± 7.98g/L) was lower than control group (45.10 ± 22.56g/L) and it was an independent risk factor to death. As to the reason of low albumin, on the one hand, liver function may be severely damaged; On the other hand, gastrointestinal inflammation is more likely to cause intestinal congestion it and poor diet, resulting in malnutrition. For prevention, patients with AMP must not only be hepatopro tective but also need to strengthen nutritional support treatment.

Limitation

Some limitations of our study should be discussed. Firstly, as a retrospective study, we need to extract information from medical records and some necessary data are not noted precisely, prone to selection bias. Secondly, poisonous mushrooms samples are difficult to collect and preserve and there’s a lack of mushroom toxicology appraisal agencies. Therefore, we cannot analyze the influence of mushrooms type and prognosis. Thirdly, another challenging issue is difficulty in accurate determination of organs toxicity, so, in this study, self-defining analysis of the damage of various organs is conducted, which may also be one of the reasons leading to differences between the research conclusions and the past. Finally, our study is only a single center retrospective study , large-scale prospective studies can be carried out in the future to compare the prognosis of patients with high-risk and non-high-risk, so that the correlation between risk factors and clinical prognosis can be confirmed more accurately.

Conclusion

In summary, ALT ≥ 200U/L, PT ≥ 20s and ALB≤30g/L are independent risk factors for the death, this implies that clinicians should carefully monitor these indexes for the development of AMP. Three organs damage could significantly increase mortality rate, especially liver. With the increase of liver damage, it may lead to coagulation and protein synthesis disorders. Therefore, hepatotoxic mushroom poisoning should be regarded as a medical emergency. However, the avoidance of re-exposure are sufficient treatment recommendations for mushroom poisoning.

Conflict of interest: The authors declare that there is no potential conflicts of interest.

Acknowledgments: We would like to thank the personnel of medical records department and in particular the department of nephrology, emergency, hemotology and infections for their kind cooperation.

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  6. Yardan T, Baydin A, Eden AO, et al. Wild mushroom poisonings in the Middle Black Sea region in Turkey: Analyses of 6 years. Hum Exp Toxicol. 2010; 29 (9): 767–771.
  7. Karvellas CJ, Tillman H, Leung AA, et al. Acute liver injury and acute liver failure from mushroom poisoning in North America. Liver Int. 2016;36 (7): 1043–1050.
  8. Dinis-Oliveira RJSoares MRocha-Pereira C, ea tl. Human and experimental toxicology of orellanine. Hum Exp Toxicol. 2016;35 (9): 1016–1029.
  9. Eren SH, Demirel Y, Ugurlu S, ea tl. Mushroom poisoning: retrospective analysis of 294 cases. Clinics (Sao Paulo) . 2010;65 (5): 491–496.
  10. Cervellin G , Comelli I , Rastelli G, ea tl. Epidemiology and clinics of mushroom poisoning in Northern Italy: A 21-year retrospective analysis. Hum Exp Toxicol.2017 Jan 1:960327117730882.
  11. Lima AD, Costa Fortes R, Carvalho Garbi Novaes MR, ea tl. Poisonous mushrooms: a review of the most common intoxications. Nutr Hosp; 2012;27 (2): 402–408.
  12. Cevik AA, Unluoglu I. Factors Affecting Mortality and Complications in Mushroom Poisonings Over a 20 Year Period: Report from Central AnatoliaPeA Report from Central Anatolia. Turk J Emerg Med. 2016;14 (3): 104–110.
  13. Yilmaz IKaya ESinirlioglu ZA, ea tl. Clinical importance of toxin concentration in Amanita verna mushroom. Toxicon. 2014;87:68–75.
  14. Frank H, Zilker T, Kirchmair M, et al. Acute renal failure by ingestion of Cortinarius species confounded with psychoactive mushrooms: a case series and literature survey. Clin Nephrol; 2009; 71 (5): 557–562.
  15. Cevik AA , Unluoglu I. Factors Affecting Mortality and Complications in Mushroom Poisonings Over a 20 Year Period: A Report from Central Anatolia.Turk J Emerg Med. 2016; 14 (3): 104–110.
  16. Schmutz M , Carron PN , Yersin B. ea tl. Mushroom poisoning: a retrospective study concerning 11-years of admissions in a Swiss Emergency Department.Intern Emerg Med. 2018;13 (1): 59–67.
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Study of the Bond at the Zirconia / Feldspathic Ceramic Interface

DOI: 10.31038/JDMR.2018112

Abstract

The growing aesthetic demands of patients have led to the development of different types of all-ceramic crowns. Y-TZP zirconia-based restorations with feldspathic ceramic guarantee more satisfaction in terms of mimicry and biocompatibility than the metal-ceramic crowns. However, the bond at the zirconia and veneered porcelain interface seems to be the weakest link in this type of restoration. Indeed, numerous cases of interfacial decohesion of the cosmetic ceramic have been reported. For this purpose, numerous scientific studies have been carried out to further explore and accurately describe the characteristics of the interface at these two ceramics in order to strengthen the bond of bilayered ceramics.

Keywords

Y-TZP Zirconia, Veneered Porcelain, Interface, Bond Strength, Decohesion

1. Introduction

The objective of fixed dental prosthesis has always been to restore the morphology and occlusal function of the teeth to give the patient satisfactory chewing by integrating the prosthetic element seamlessly.

The metal-ceramic crown meets these mechanical and aesthetic requirements is still considered to be the gold standard in fixed prosthesis. However, the importance of aesthetics is growing rapidly in today’s society, and the metal-ceramic system, although clinically reliable in the long term, gives less satisfaction in terms of mimicry and biocompatibility. “The restoration of the natural appearance of a smile cannot be designed without the use of all-ceramic systems.” (John MacLean, 1975)

Nowadays, the development of new ceramic which is more resistant and offers excellent light transmission has made it possible to extend to all the clinical situations the application of all-ceramic crown to all clinical situations. The alliance of professional skills and innovations in biomaterials brought Y-TZP zirconia-based infrastructures (Yttrium Tetragonal Zirconia Polycrystal) forward in the early 1990s. Given its mechanical properties, Y-TZP zirconia can now expand the indications of this all-ceramic system to multi-prosthetic processes. In response to today’s growing demands of biocompatibility and aesthetics, Y-TZP zirconia infrastructures appear as a prosthetic solution that should not be overlooked.

However, the problem durability of ceramo-ceramic restorations arises. Indeed, many cases of cosmetic ceramics fracture along the interface with the Y-TZP zirconia-based infrastructure have been reported [1]. This clinical observation was the subject of many scientific studies aiming to explore the existing link between the Y-TZP zirconia-based infrastructure and the veneered ceramic.

The aim of this article is the synthesis of scientific data acquired through experimental research, in regards to both the origin and propagation mode of the various cracks in the ceramic, as well as the strength of the bond at the zirconia / feldspathic ceramic interface, and the factors influencing it.

2. Characteristics of the Interface

The long term success of the ceramo-ceramic crowns consisting of veneering ceramic to zirconia is a critical issue. Indeed, the zirconia-based restorations constitute a high percentage of cosmetic ceramics fracture. As a matter of fact, the rate of fracture in vivo of laminating ceramics is 15% after 24 months, 25% after 31 months, whereas it is only 2.9% after 36 months for metal-ceramic restorations [2]. The location of the interface as an original defect was reported, suggesting that the link between the veneering ceramic and the zirconia-based infrastructure is the weakest link in this type of restoration [3].

2.1 The Different Modes of Interaction Occurring between the Structural Ceramic and the Cosmetic Ceramic

Existing studies have focused on some critical clinical perspective issues regarding the quality of the connection at the level of the interface of zirconia and the veneered ceramic.

It was shown that the combination of structural analysis techniques such as Raman confocal microscopy (Figure1) and the recently introduced FIB / SEM (Figure 2, 3) analysis in microscopy ensured a better understanding of the relationship between the two similar but physically incomparable ceramic materials. Indeed, feldspathic ceramic has a biphasic structure: vitreous and crystalline, while zirconia is a polycrystalline ceramic.

JDMR2018-102-NASRElie-Revised_F1

Figure 1. Confocal Raman microscopic analysis of the zirconia / feldspathic ceramic interface. (Durand et al, 2012)

JDMR2018-102-NASRElie-Revised_F2

Figure 2. Microstructural analysis FIB / SEM of the zirconia and the veneered ceramic interface. (Mainjot et al, 2013)

JDMR2018-102-NASRElie-Revised_F3

Figure 3. The FIB / SEM analysis of the interdiffusion zone, shows the presence of zirconia crystals (white arrows) within the feldspathic ceramic. (Mainjot et al, 2013)

Microscopic observations revealed three different structural layers. However, the presence of an intermediate layer of 50 μm thickness in the cosmetic ceramic in contact with zirconia, has defined a process of interdiffusion (i.e. mutual diffusion). Thus, this transition layer is characterized by the presence of zirconia particles (certified by the EDS), up to 20 μm in size in the glass matrix.

2.1.1 Chemical Interaction

Existing literature gives little evidence as to the presence of a chemical bond between the zirconia-based infrastructure and veneered feldspathic ceramic. No scientific evidence of a chemical bond between the two materials has been put forward.

The adhesion between the structural and cosmetic ceramic depends on the basic material. In the case of a glass-infiltrated ceramic infrastructure (e.g. InCeram Spinell, InCeram Alumina, InCeram Zirconia), a chemical bond is established by diffusion of the glass into the cosmetic ceramic during sintering.

Polycrystalline ceramics have low vitreous mass (1%), which calls into question the presence of a chemical bond between zirconia and the veneered ceramic.

2.1.2 Mechanical Interaction

The absence of tangible evidence indicating the presence of a chemical bond between the zirconia-based infrastructure and veneered feldspathic ceramic, suggests that it is the mechanical link that plays the major role in the integration of the two materials together.

The mechanical phenomena are very well documented and widely accepted by the scientific community. Accordingly, they can be broken down into two principles.

2.1.2.1 The Compressive Stresses

The development of compressive stresses by the cosmetic ceramic on the infrastructure is mechanically favorable, since direction of these stresses opposes the propagation of cracks from inter-facial defects and compensates for the tension stresses at the surface of the zirconia. These compressive stresses arise from the difference in the coefficients of thermal expansion between two ceramics.

The coefficient of thermal expansion is a characteristic of the dimensional changes of a sample of material that depends on the variation in temperature. It is given by the following relation: L = α . L0 . ∆T

With: – L: Length variation of the sample (m)

– α: Coefficient of thermal expansion (K-1 or oC-1)

– L0: Initial length of the sample (m)<

T: Temperature variation (K or oC)

The higher the value of the coefficient of thermal expansion, the more the material will tend to expand during sintering, and shrink upon cooling. This explains the importance of having similar coefficients of thermal expansion between the structural ceramic and the cosmetic ceramic in order to avoid expansion cracks.

Ideally, the two coefficients of thermal expansion should be identical with a slightly lower coefficient of thermal expansion for the cosmetic ceramic compared to the structural ceramic, so as not to generate a crack in the veneered ceramic during its cooling. Indeed, the fragile cosmetic ceramic is mechanically more resistant when it is compressed compared to when it is in a state of tension. Mastering the thermal properties of different ceramics is essential to ensure a sustainable, durable restoration. In order to increase the bond strength between the zirconia framework and the veneered ceramic, the coefficient of thermal expansion of the cosmetic ceramic should be slightly less than the coefficient of thermal expansion of the infrastructure. Thus, the compressive stresses created reinforce the bond between the two ceramics.

2.1.2.2 Micromechanical Retention

It corresponds to the “entanglement rate” of the feldspathic ceramic in the infrastructure. This mechanical locking between the two materials is due to surface irregularities of the zirconia that are present prior to the veneering procedure.

This micromechanical adhesion will be dependent on the surface roughness of the infrastructure due to the milling, polishing, and sandblasting procedures, as well as the ability of the cosmetic ceramic to lodge in these rough edges (size grains, wettability).

The preparation of the surfaces of the infrastructure must provide sufficient roughness to increase the surface area in contact with the provided mass of the cosmetic ceramic. However, excessive roughness leads to deep grooves that reduce grip and weaken the bond strength.

2.2 Experimental Values of the Bond Strength

In order to study the bond strength at the zirconia and the veneered ceramic interface, Ozkurt et al. [2] selected four types of zirconia-based ceramics: Zirkonzahn, Cercon, Lava, and DC-Zircon. For each zirconia system, 30 disk samples were veneered with IPS e.max Ceram, Vita VM9, and a coating ceramic recommended by the manufacturer. (Tabel 1) A SBS (Shear Bond Strength) test was performed, and a fracture surface analysis was also conducted to determine failure modes, categorized as follows:

  • Cohesive fracture : Rupture within the cosmetic ceramic.
  • Adhesive fracture : Rupture at the interface.
  • Combined fracture : Combination of the two aforementioned fracture modes.

Table 1. Average bond strength (MPa) and fracture mode (%) for different combinations of zirconia-based and veneered ceramics. (Ozkurt et al, 2010)

Zirconia Infrastructure Ceramic

Feldspathic

Bond Strength

Failure Mode

Cosmetic Ceramic

(MPa)

(%)

Zirkonzahn

Ice Keramik®

24,46

50% adhesive

50% combined

IPS e.max Ceram®

26,04

50% adhesive

50% combined

Vita VM9®

26,52

100% combined

Cercon

Cercon Ceram®

20,19

80% adhesive

20% combined

IPS e.max Ceram®

24,17

50% adhesive

50% combined

Vita VM9®

21,67

100% combined

Lava

Lava Ceram®

27,11

30% adhesive

70% combined

IPS e.max Ceram®

23,05

60% adhesive

40% combined

Vita VM9®

18,66

50% adhesive

50% combined

DC-Zirkon

Triceram®

40,49

50% adhesive

50% combined

IPS e.max Ceram®

21,38

50% adhesive

50% combined

Vita VM9®

31,51

100% combined

3. The Fracture

The use of innovative materials, such as Y-TZP zirconia for ceramo-ceramic reconstructions, constitutes a breakthrough in the field of prosthetics. Its harmonious color and biological integration with the surrounding tissue perfectly match the current trends in aesthetics and biocompatibility.

However, the long term success of this type of restoration is still a major concern. Different fracture lines can be observed in these ceramo-ceramic crowns that break abruptly without prior plastic deformation. Moreover, the fracture occurs by propagation of a crack from an initial defect.

In this sense, various clinical studies were conducted to understand the possible failure mechanisms. In fact, the study of the origin and path of the fracture line is of great importance to determine the factors allowing or limiting the propagation of the crack along the zirconia and veneered ceramic interface.

3.1 Origin of the Fracture

Descriptive fractography is an effective imaging tool applied in dentistry to clinical failure analyses of ceramic restorations [4].

The analysis of the fractured surface at the level of defective ceramic crowns contributes to determine the direction of propagation of the crack, and trace the origin of the fracture [5].

3.1.1 Occlusal

One of the emerging causes of fracture in all-ceramic dental restorations is the generation of micro-cracks due to occlusal contacts and wear. This occlusal load falls under the bi-axial type; during a masticatory cycle the compression is always followed by a lateral sliding movement (Figure 4). These forces trigger a series of conical cracks in the cosmetic ceramic [6]. According to a study by Aboushelib et al. [7] the majority of porcelain zirconia single unit restorations fracture by initiation and propagation of conical cracks from the occlusal surface to the interface.

JDMR2018-102-NASRElie-Revised_F4

Figure 4. Schematic representation of the forces involved during occlusal contact in a masticatory cycle. (Kim et al, 2007)

3.1.2 Interface

The fracture can also arise at the level of the zirconia and ceramic lamination interface. This type of failure is related to the low adhesive strength between the two ceramics used as well as the presence of localized tensile stresses at the interface level. These constraints which have a significant effect on the weakening of the bond are due to the incompatibility of the coefficients of thermal expansion between the two materials.

Aboushelib et al. [7] analyzed clinically fractured zirconia layered ceramics restorations; out of 19 examined unit crowns, 6 exhibited an interfacial decohesion (Figure 5).

JDMR2018-102-NASRElie-Revised_F5

Figure 5. The SEM analysis of the zirconia and the veneered ceramic interface shows an interfacial decohesion. (Aboushelib et al, 2009)

3.1.3 Bridge Connections

Generally, bridge connections are weak spots and favor the concentration of constraints. Indeed, the connections are subject to constraints of tension and bending.

According to a study from Toskanak et al. [4], in the case of an Y-TZP zirconia-based infrastructure of a three-unit bridge veneered with a feldspathic ceramic, the fracture takes place in four of the five samples at the connection level, more specifically on the gingival side (Figure 6).

3.2  The Crack Propagation

A crack originates at a point of major stress concentration. It spreads when it receives the energy necessary for its elongation. However, the propagation of the crack is mainly dependent on the composition of the ceramic, the shape, the size, and the orientation of the grain, but is also affected by the rate of residual stresses in the material [8].

JDMR2018-102-NASRElie-Revised_F6

Figure 6. The 3D numerical modeling is used to simulate the fracture initiation sites of an Y-TZP bridge. (Kou et al, 2011)

3.2.1 The Hertzian Cone Cracks

These cracks progress very quickly, at relatively low charges (<100N), but generally do not broadcast very far inside the sample. They initially develop in the form of a superficial ring then spread unstably and stop taking the form of a cone. They are able to maintain stability without causing a fracture.

3.2.2 The Internal Cone Cracks

These cracks appear only after repetitive loads. They spread quickly and deeply in the direction of the zirconia / feldspathic ceramic interface, which can cause the mass fracture of the restoration.

3.2.3 The Radial Cracks

These cracks are formed at high and continuous loads (200 to 600N). They originate from a pre-existing defect at the inner surface of the cosmetic ceramic, when the tensile stress exceeds the flexural strength of the material.

This type of crack has been identified as the main mode of failure in all-ceramic crowns [9].

4. The Required Criteria to Achieve a Better Ceramo-Ceramic Connection

Thanks to various scientific researches, light was shed on the multiple variables affecting the ceramo-ceramic bond strength. In fact, understanding the characteristics of the interface between zirconia and the veneered ceramic made it possible to adjust the various parameters, thus leading to the design of a sustainable restoration.

4.1 Surface Treatment

In what follows, we will describe the procedures commonly used in the surface treatment of zirconia before the veneering procedure.

4.1.1 Sandblasting

Nowadays, it is commonly accepted that sandblasting with alumina oxide at 50 μm with a pressure of 2 bar causes a significant increase in the mechanical properties of zirconia by allowing the formation of a compressive layer on the surface.

The impact of sand on the surface of zirconia induces residual stresses that promote the conversion of tetragonal particles into monoclinic particles. This phase transformation is accompanied by a volume increase of 3 to 5% of the monoclinic crystals inducing the formation of a compressive surface layer.

However, the surface defects introduced by sandblasting (Figure 7) must be less deep than the thickness of the compressive layer to obtain an increase in the fracture resistance.

JDMR2018-102-NASRElie-Revised_F7

Figure 7. Observation under an electron microscope, the surface of the zirconia before (A) and after (B) sandblastinging with alumina oxide at 50 μm. (Hjerppe et al, 2016)

Fischer et al. [10] studied the effect of sandblasting of zirconia on bond strength with feldspathic ceramic. By observing the fracture mode of the specimens, they deduced that the crack propagates towards the interface, but against the compressive layer, the latter changes direction and diffuses parallel to the interface in the thickness of the cosmetic ceramics.

The sandblasting technique, which is widely used in the dental prosthesis laboratory, proves to be advantageous in terms of mechanical strength resistance of the zirconia-based infrastructure.

4.1.2 Application of a Liner

The “liner” corresponds to a specific layer composed of feldspathic ceramic enriched with selenium (Se), used initially to mask the color of the zirconia, which is too white, by generating a colored background [11].

However, its application on zirconia infrastructure before veneering is not recommended [12] since its use decreases the ceramo-ceramic adhesion force [13, 14].

4.2 The Cooling Speed

Zirconia is a bad thermal conductor, and this is an important factor to take into consideration to correct the sintering mechanisms of the cosmetic ceramic.

Tan et al. [3] have shown that the mechanical properties of a veneered zirconia framework restoration are doubled by the use of slow heating and cooling regimes.

However, it is the cooling speed that greatly influences the ceramo-ceramic bond strength. Indeed, during cooling after sintering, the surface of the cosmetic ceramic cools quickly while the cosmetic interface progressively cools. This “gradient solidification” entails the incorporation of numerous residual thermal stresses between the infrastructure and veneered ceramic.

According to Rues et al. and Guazzato et al. [15, 16] fast cooling results in compressive residual stresses while slow cooling results in the formation of extensive residual stresses.

The presence of compressive stresses increases the bond strength of zirconia and veneered ceramic, but also promotes the probability of chipping of the cosmetic ceramic. On the other hand, extensive stresses decrease the ceramo-ceramic bond strength, but prevent cosmetic chips [15].

Therefore, the residual thermal stresses must be controlled in order to strengthen the ceramo-ceramic adhesion without risking to weaken the veneered ceramic.

Currently, the slow heating and cooling regimes are widely adopted by dental technicians.

5. Conclusion

The growing demand for aesthetic restorations that replicate natural looks and the increasing concerns about the metal restorations have been the driving force behind the development of new materials and techniques in the field of the fixed dental prosthesis.

Nowadays, all-ceramic crowns are gaining well-deserved ground. Indeed, the Y-TZP zirconia-based infrastructure veneered with a feldspathic ceramic meets the rational requirements of the patient in search for aesthetics, biocompatibility and function.

However, clinical studies report an increased incidence and severity of fractures in this type of restoration. The fractographic analysis makes it possible to determine the failure modes, the origins of rupture and the propagation of cracks at the level of these ceramo-ceramic crowns.

The various types of failures found such as cohesive fracture or “chipping” at the level of cosmetic ceramics and interfacial decohesion are complex and depend on the internal factors (compositions, properties) and external factors (masticatory forces applied) to the materials.

The bond at the zirconia and veneered ceramic interface has proven to be a real challenge. Below are the criteria that must be adapted to obtain a viable restoration, able to withstand intraoral conditions:

  • Sandblasting with alumina oxide at 50 μm with a pressure of 2 bar on the surface of the zirconia.
  • Controlled cooling regimes during the different sintering phases.
  • Similar coefficients of thermal expansion with a coefficient of expansion slightly lower for the ceramic overlay compared to that of the structural ceramic.

Thus, in order to overcome the problems of bilayer structures, monolithic crowns made from polychromatic zirconia, characterized by a fine and homogeneous structure, and shaped using CAD / CAM procedures have been placed on the market. The latter are promising in terms of aesthetics and mechanics. In the meantime, only clinical and in vitro studies will provide the data needed to the universal consent to their use in the near future.

References

  1. Baldassarri M, Zhang Y, Thompson VP, Rekow ED, Stappert CFJ (2011) Reliability and failure modes of implant-supported zirconium-oxide fixed dental prostheses related to veneering techniques. J Dent 39: 489–498.
  2. Ozkurt Z, Kazazoglu E, Unal A (2010) In vitro evaluation of shear bond strength of veneering ceramics to zirconia. Dent Mater J 29: 138–146. [crossref]
  3. Tan JP, Sederstrom D, Polansky JR, McLaren EA, White SN (2012) The use of slow heating and slow cooling regimens to strengthen porcelain fused to zirconia. J Prosthet Dent 107: 163–169. [crossref]
  4. Taskonak B, Yan J, Mecholsky JJ Jr, Sertgöz A, Koçak A (2008) Fractographic analyses of zirconia-based fixed partial dentures. Dent Mater 24: 1077–1082. [crossref]
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  7. Aboushelib MN, Feilzer AJ, Kleverlaan CJ, (2009) Bridging the gap between clinical failure and laboratory fracture strength tests using a fractographic approach. Dent Mater 25: 383–391.
  8. Etman MK (2009) Confocal examination of subsurface cracking in ceramic materials. J Prosthodont 18: 550–559. [crossref]
  9. Lawn BR, Deng Y, Lloyd IK, Janal MN, Rekow ED, et al. (2002) Materials design of ceramic-based layer structures for crowns. J Dent Res 81: 433–438. [crossref]
  10. Fischer J, Stawarczyk B, Hämmerle CH (2008) Flexural strength of veneering ceramics for zirconia. J Dent 36: 316–321. [crossref]
  11. Fouquier R (2008) La zirconne comment je m’y accroche. Tech Dent 263: 7–17.
  12. Alghazzawi TF, Janowski GM (2016) Effect of liner and porcelain application on zirconia surface structure and composition. Int J Oral Sci 8: 164–171. [crossref]
  13. Ishibe M, Raigrodski AJ, Flinn BD, Chung KH, Spiekerman C, et al. (2011) Shear bond strengths of pressed and layered veneering ceramics to high-noble alloy and zirconia cores. J Prosthet Dent 106: 29–37. [crossref]
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  15. Rues S, Kröger E, Müller D, Schmitter M (2010) Effect of firing protocols on cohesive failure of all-ceramic crowns. J Dent 38: 987–994. [crossref]
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Pattern of Anti-Epileptic Drug use in Libyan Children and Their Effects on Liver Enzyme Activities

DOI: 10.31038/JPPR.2018113

Abstract

Epilepsy is one of the most common chronic neurological disease that characterized by recurrent, spontaneous brain seizures. Anti-epileptic drug is used clinically to control the epilepsy or reduce the frequency of the attacks. Liver is the primary and main organ for drug metabolism and elimination of several drugs such as anti-epileptic drugs (AEDs). Thus, drug-induced toxicity may occur. Since liver enzymes can serve as biological markers of hepatocellular injury, this study was aimed to evaluate the effect of anti-epileptic drugs used in patients treated at the Department of Neurology in Benghazi Children Hospital, on activities of liver enzymes; aspartate aminotransferase (AST), alanine aminotransferase (ALT) and alkaline phosphatase (ALP). Out of 58 patients selected randomly in this study 38% of them were female with age ranged from four months to five years old. Male patients were more susceptible to the adverse effects than the female patients. Mode of therapy and age of the patient did not show any effect on the levels of enzyme changes. Sodium valproate was the frequent drug used and level of ALP of the majority of patient was elevated above the normal level. Routine screening of hepatic enzymes level during the chronic use of anti-epileptic drugs is recommended and the need for obtaining baseline liver function tests is also essential before starting anti-epileptic therapy in Libyan children.

Keywords

Anti-epileptic drug, Liver enzyme, Adverse effect, Child, Libya

Introduction

Epilepsy is one of the oldest neurological conditions known to mankind. It is characterized by recurrent, spontaneous brain seizures. Epilepsy affecting about 50 million individuals worldwide and 90% of them are from developing countries [1]. About, 70 – 80% of the patients who develop epilepsy may expect to have their seizures controlled with optimal anti-epileptic therapy [2]. All anti-convulsant medications are associated with adverse effects which may have significantly impact on the quality of life and contributing to non-compliance and, in rare circumstances be, potentially life-threatening [3]. Some anti-convulsants, particularly phenytoin and carbamazepine induce and increase the production of hepatic enzymes. This can result in clinically significant drug interactions by increasing the metabolism of some co-administered drugs. Other enzyme inducing anti-epileptics include phenobarbitone sodium and primidone. Topiramate and oxcarbazepine are inducers at high dose but at lower doses have some inhibiting properties. Sodium valproate is an inhibitor of specific isoenzymes and typically increases the concentrations of other anticonvulsants, particularly lamotrigine and the active metabolite of carbamazepine. Doses of lamotrigine should be halved while taking sodium valproate [4]. Since liver is the primary organ for drug metabolism and elimination for many antiepileptic drugs (AEDs) thus, drug-induced toxicity may occur. Hepatotoxic reactions, ranged from mild and transient elevations of hepatic enzymes to fatal hepatic failure. Chronic therapy with AED causes abnormalities in calcium metabolism, including hypocalcemia, hypophosphatemia, elevated levels of serum alkaline phosphatase and serum parathyroid hormone, reduced serum levels of biologically active vitamin D metabolites, radiologic evidence of rickets, and histologic evidence of osteomalacia [5].

It has been found that, carbamazepine, phenytoin and sodium valproate are associated with mild elevations of liver enzymes, which may occur in up to 50% of patients. Although this elevation is usually transitory or dose-related and do not appear to be associated with hepatocellular injury [6], the liver enzymes can serve as biological markers of hepatocellular injury [7]. Since the adverse metabolic effects of AED treatments have only recently received attention, the objectives of the present study are to investigate the pattern and the clinical effects of these drugs on the liver enzyme activities of young children admitted to Department of Neurology, Benghazi Children Hospital, second major city in Libya.

Materials and Methods

A descriptive serious case study was conducted on 58 medical record selected from Pediatric Neurology Unit at the Benghazi Children Hospital, Benghazi, Libya during 2016. The study included epileptic patients receiving anti-epileptic drugs only. Exclusion subjects: Epileptic patients who had concomitant liver diseases, using other drugs causing elevation of liver enzymes (e.g. antibiotics, anti-rheumatic drugs, statins and on steroidal anti-inflammatory drugs) were excluded from this study.

Liver enzyme assessed

Laboratory investigations were investigated to assess the liver enzyme activities which include: alanine aminotransferase (ALT, reference range of 5.0 – 41.0 U/L), aspartate aminotransferase (AST, reference range of 5.0 – 41.0 U/L) and alkaline phosphatase (ALP, reference range of 40.0 – 129.0 U/L). Data was presented as a descriptive analysis (mean and standard deviation).

Results and Discussion

From a total number of pediatric patients admitted to the Department of neurology in Benghazi Children Hospital, only 58 patients from randomly selected files were included. Out of total, 36 patients were males and the rest of them (n = 22) were female patients; accordingly, as demonstrated in (Figure 1), the majority of children admitted were male and formed 62% of total. The age of the included patients were ranged from four months up to 17 years old. They were divided into three sub-groups according to their ages as following: group 1: up to five years old (n = 36, 62.0%), group 2: included children from 6 to 10 years old (n = 9, 15.5%) and group 3: from 11 to 17 years old (n = 13, 23.5%) as shown in (Figure 2).

JPPR-18-104_F1

Figure 1. The percentage of male and female.

JPPR-18-104_F2

Figure 2. Distribution of patients with regard to Age.

According to the records, several AEDs with different mechanisms of action were used for treatment of the admitted patients (8). The most frequently drug used, as shown in table 1, was sodium valproate which administered by 42 of the patients, while only one patient was receiving clonazepam. The number of patients which received phenytoin, carbamazepine, diazepam and levetiracetam was almost equal for each drug. While, phenobarbital, lamotrigine and clonazepam were the lowest frequency in use (Table 1).

Table 1. Frequency of antiepileptic drugs prescribed for the patients.

Anti-epileptic drug

Frequency of use No. (%)

Sodium Valproate

42 (72.4%)

Phenytoin

18 (31.0%)

Carbamazepine

17 (29.3%)

Diazepam

16 (27.5%)

Levetiracetam

15 (25.8 %)

Phenobarbital

6 (10.3%)

Lamotrigine

3 (5.1)%

Clonazepam

1 (1.7%)

Most of the patients included in this study were belongs the group 1 and represent 62% of all the patients, while the percentage of patients belongs to group 2 and group 3 were 15.5% and 22.4%, respectively. The mean age for each group was 2.50  ± 1.65, 7.89 ± 1.54 and 12.54 ± 1.90 in that order. In order to assess whether AEDs have changed the level of liver enzyme activities of the admitted patients; the results of investigation recorded in patient’s files were tabulated to evaluate and abnormal levels of AST, ALT and ALP. According to (Figure 3), out of the total number of patients respected; only 9 (16%) children of them had no changes in their enzymes level while, the level of same enzymes of 49 (84%) patients were increased to be more than the normal range (Table 2).

Table 2. frequency with percentage of Libyan patients for abnormal liver enzyme activities.

Enzyme

AST

ALT

ALP

No. of patients with changed enzyme levels

17

3

47

Percentages

29.30%

5.20%

81.00%

JPPR-18-104_F3

Figure 3. Percentage of patients with normal and abnormal enzyme level

Our finding was in line with the study performed on 2010 which reported that liver enzymes were elevated as a result of AEDs adverse reaction [2]. It was reported that hepatotoxic reactions ranged from mild and transient elevations of hepatic enzymes to fatal hepatic failure [6] and the level of liver enzymes can serve as biological markers of hepatocellular injury as confirmed by Ahmed and Siddiqi [7]. Accordingly, present results indicate that AEDs may leads to hepatocellular injury which appeared as elevation in level of liver enzymes. It has been found that, levels of both AST and ALP enzyme in all the groups have been increased above the normal range, whereas, ALT level has elevated in only group 1 (Table 3). The present results also indicated that ALP level of the majority of patients (81%) was increased to be more than normal range meanwhile, AST was above the range in 29.3 % of patients. Only three patients (5.20%) had high level of AST.

Table 3. Abnormal level of liver enzyme in each group (Mean ±STD).

Enzyme Levels in U/L

AST

ALT

ALP

group 1

52.77 ± 15.26

52.73 ± 12.13

218.00 ± 59.14

group 2

48

192.25 ± 64.51

group 3

54.33 ± 9.16

190.91 ± 43.50

It has been reported that, sodium valproate is more hepatotoxic than other AEDs, phenytoin and Carbamazepine [8], and according to our findings shown in table 2, subsequently, it could be proposed that the elevation in lever enzyme was a results of sodium valproate, phenytoin and Carbamazepine administration. The number of patients (female /male) had abnormal level enzyme in each group were illustrated in (Table 4). It has been found that percentage of boys with abnormal level of liver enzyme formed a higher percentage of the total patients included see table 4. The number of boys was approximately double of girl’s in both groups 1 and 3 while it was 3 fold in group 2 as seen in table. Since there was a marked difference between male and female patients in our result, it may indicate that male is more susceptible to liver injury due to AEDs.

Table 4. Male and female who had abnormal level of liver enzyme in each group.

Groups/gender

Female

Male

Group 1

27.70%

55.50%

Group 2

22.20%

66.60%

Group 3

30.80%

61.50%

Regarding mode of therapy; the epileptic patients were divided into 2 subgroups; patients who were treated by receiving a single AED (monotherapy) and patients who received multiple AEDs (polytherapy). The effect of mode of therapy, in term of single and multiple drug use, in the level of liver enzyme been evaluated. Thus, as demonstrated in (Figure 4); 17 patients (29.3%) were on single therapy (7 of them were on sodium valproate and 5 were on carbamazepine while only 3 and 2 of were on diazepam and phenytoin respectively). Level of respected enzyme of 14 of them has been elevated to become above the normal range. The rest of the patients were on multiple therapy (receive two or more AEDs) and were represented 70.7 % of the patients. Enzymes level of 36 of these patients was affected.

JPPR-18-104_F4

Figure 4. Frequency (percentage) of the patients received different mode of therapy.

Regarding single therapy, the level of liver enzyme of 14 patients has increased and mean level of AST, ALT and ALP were 47.15, 42 and 231.88, respectively. Similarly, the levels of respected enzymes of patients (n = 36) on multiple therapies were also increased to become 55.96, 58.1 and 198.33 in the same order as shown in (Figure 5).

JPPR-18-104_F5

Figure 5. Effect of mode of therapy in the level of liver enzymes.

According to the present finding, it seems more likely that there is no marked change between AST and ALT levels in both mode of therapy. Although the level of ALP of patients on single therapy was higher than that who received more than one AED, however, with no marked difference. It has found that receiving more than one AEDs may decrease inducing enzyme liver but remain higher than normal range. Therefore it could said that mode of therapy did not affect the level of respected enzymes. However, there is no clear answer on whether to combine AEDs but different strategies are needed in different patients to control epilepsy and adverse effects [9, 10].

Conclusion and Recommendation

In Libya, male patients were more admitted to neurology unit and age of the patients was ranged from four months to five years old. Multiple therapies have been used to control epilepsy more than single treatment. Sodium valproate was the most frequent drug used followed by phenytoin and carbamazepine. Mode of therapy and age did not show any effect in level of enzyme during the treatment with AEDs. On contrast, the difference in gender has a marked effect in the level of respected enzyme as male was more susceptible to liver injury during AEDs treatment. Elevation in the levels of liver enzyme (AST and ALP) to 2-3 fold during AEDs was confirmed and precautions should be taken when using anti-epileptic drugs in Libyan epileptic patients. Routine screening of hepatic enzymes level during chronic use of anti-epileptic drugs is recommended and the need for obtaining baseline liver function tests is essential before starting antiepileptic therapy.

References

  1. Kumar H, Chandi M, Kandar C, Das S K, Lakshmkanta Ghosh L, et al. (2012) Epilepsy and its management: A review. J Pharma Sci Tech 1: 20–26.
  2. Naithani M, Chopra S, Lsomani B, Ksingh R (2010) Studies on adverse metabolic effects of antiepileptics and their correlation with blood components. Curr Neurobiol 1: 117–120.
  3. Tatum WO (2010) Antiepileptic drugs: adverse effects and drug interactions. Continuum (Minneap Minn) 16: 136–158. [crossref]
  4. Stein MA, Kanner AM (2009) Management of newly diagnosed epilepsy: a practical guide to monotherapy. Drugs 69: 199–222. [crossref]
  5. Farhat G, Yamout B, Mikati MA, Demirjian S, Sawaya R, et al. (2002) Effect of antiepileptic drugs on bone density in ambulatory patients. Neurology 58: 1348–1353. [crossref]
  6. Arroyo S, de la Morena A (2001) Life-threatening adverse events of antiepileptic drugs. Epilepsy Res 47: 155–174. [crossref]
  7. Ahmed SN, Siddiqi ZA (2006) Antiepileptic drugs and liver disease. Seizure 15: 156–164. [crossref]
  8. Hussein RS, Soliman RH, Ali AM, Tawfeik MH, Abdelhaleem ME (2013) Effect of anti-epileptic drugs on liver enzymes. Beni-suef Univ J Basic App Sci 2: 14–19.
  9. Sherif FM (2015) Pharmacological profile of the GABA-transaminase inhibitor vigabatrin. World Journal Pharmacy Pharmaceutical Sciences 4: 139–148.
  10. Stephen LJ, Brodie MJ (2012) Antiepileptic drug monotherapy versus polytherapy: pursuing seizure freedom and tolerability in adults. Curr Opin Neurol 25: 164–172. [crossref]

General Practitioners’ Current and Emerging Views about Pay for Performance Schemes

DOI: 10.31038/JCRM.2018122

Abstract

In many healthcare system, General Practitioners play a crucial role for those requiring medical services. Using financial incentives to directly reward “performance” and “quality” is a new compensation method developed in more countries.

One of the biggest examples of payment for performance is the Quality and Outcome Framework (QOF) started in United Kingdom in 2004.

Despite the proliferation of these different programs across the world, the evidence to support their use is widely debated.

The main aim of this study was to provide an overview about different General Practitioners perceptions related to the design and implementation of pay-for-performance initiatives. To achieve this aim we reviewed recent studies published from 2004, with a particular focus on general practitioners’ views about pay for performance remuneration schemes.

The results suggest that despite pay for performance is successfully accepted, in few cases does appear to have had a negative impact on some aspects of medical professionalism, and reduced clinical autonomy.

Keywords

Pay for performance; General practitioners; primary care; financial incentives

Introduction

In several healthcare systems, General Practitioners (GPs) are the primary contact for those requiring health care and act as gatekeepers to hospital services. Therefore, they play a vital role to healthcare system performance.[1]

The use of different ways of paying primary care physicians in an attempt to increase quality of care, including the use of financial incentives to directly reward “performance” and “quality”, is increasing in many countries.[2]

The rationale of pay for performance schemes is based on the premise that income is a key motivating factor for GPs. [1]

One of the biggest examples of payment for performanc­e anywhere in the world is the Quality and Outcome Framework (QOF), a new contract for family practices in United Kingdom (UK).[3]

The scheme attached financial rewards for meeting 146 quality targets in relation to clinical, organizational, and patient experience indicators and in 2006 it was modified to 135 indicators.[4]

QOF payments represented up to 20% of GPs’ income in the first year of its introduction.[5]

Despite the proliferation of P4P programs, the evidence to support their use is still inconclusive. [6, 7] one of the reasons may be the differences between P4P programs. Incentives in current programs vary in terms of number and type of indicators, professional standards and quality domains (clinical care, patient experience, organization of care).[5, 8]

The size of the incentive and the unit of assessment in P4P programs can influence their effectiveness.[9]

The intended consequences of the new contractual arrangements were to reward quality of care rather than numbers of registered patients, to improve data capture and care processes, and to improve patient outcomes and doctors’ working conditions.[3, 10]

Financial incentives can change behavior and policy-makers have sought to improve quality by making more payments to health professionals dependent on performance against predetermined standards.[11]

The main aim of this study was to provide an overview about different General Practitioners perceptions related to the design and implementation of pay-for-performance initiatives. To achieve this aim we reviewed recent studies published from 2004, with a particular focus on general practitioners’ views about pay for performance remuneration schemes.

GPs views toward quality based compensation scheme

Despite perceptions of the negative consequences on workload and autonomy before the introduction of the scheme, some authors reported that GPs were more positive than they had anticipated on its impact on the quality of care. About that, Whalley et al., [12]evaluated physicians’ views in United kingdom of their working life and quality of care before and after the new contract and showed that overall job satisfaction increased, from 4.58 out of 7 in 2004 to 5.17 in 2005; the average worked hours reported decreased from 44.5 to 40.8 and average income rose from £ 73 400 in 2004 to £ 92 600 in 2005, contrary to what they had anticipated before the introduction of the QOF.

Also Beckman et al.,[13] demonstrated that despite primary care physicians were skeptical, after the introduction of the new remuneration scheme created by United States Excellus BlueCross BlueShield and its individual practice association (IPA) partner, the Rochester Individual Practice Association (RIPA), were positive influenced on making improvements in quality, satisfaction, and practice efficiency.

Attitudes towards the contract were largely positive, McDonald et al.,[14]explored the impact of financial incentives for quality of care on practice organization, clinical autonomy, and internal motivation of doctors and nurses working in primary care over a five month period after the introduction of the contract. They showed that there was an increase in the use of templates to collect data on quality of care, although discontent was higher in the practice with a more intensive surveillance regimen. Nurses expressed more concern than doctors about changes to their clinical practice but also appreciated being given responsibility for delivering on targets in particular disease areas.

Physicians and nurses interviewed by Campbell et al., [10] in 22 nationwide representative practices across England between February and August 2007 believed that the objectives of the scheme were achieved in terms of improvements in the specific processes for the patient’s care and their income, as well as better data acquisition. However, it also led to side effects, such as the emergence of a double QOF-patient program in consultations, a decline in personal / relational continuity of care between doctors and patients and resentment by group members who do not benefit of payments.

In addition, GPs and practice managers described a sense of decreased clinical autonomy and loss of professionalism.[15]

Participants to the study by Maisey et al., [16] reported substantial improvements in teamwork and in the organization, consistency and recording of care for conditions incentivized under QOF scheme, but not for non-incentivized activities and patients’ concerns may receive less clinical attention.

A Scottish study by Feng et al., [17] investigated whether and how a change in performance-related payment motivated GPs and evaluated the effect of increases in the performance thresholds required for maximum payment under the QOF. They found that the increase in the maximum performance thresholds increased GPs’ performance by 1.77% on average. Low-performing GPs improved significantly more (13.22%) than their high-performing counterparts (0.24%).

Kirschner and Grol, [18]conducted a qualitative study in 29 general practices in the Netherlands in order to explore general practices’ experiences with pay-for- performance in primary care about feasibility, feedback and the bonus and spending of the bonus. They found that the feasibility of the program was questioned due to the substantial time investment. The feedback on clinical care, practice management and patient experience was mostly discussed in the team, and used for improvement plans. The bonus was considered a stimulus to improve quality of care and was mainly spent on new equipment or team building.

A key factor in designing pay-for-performance programs is determining what entity the incentive should be awarded to individual clinicians or to groups of clinicians working in teams. The study of Greene et al., [19] examined primary care clinicians’ perceptions of a team-based quality incentive awarded at the clinic level. Clinicians reported the strengths of the clinic-based quality incentive were quality improvement for the team and less patient “dumping,” or shifting patients with poor outcomes to other clinicians.

Allen et al., [1] used data on 1920 GPs in order to verify correlation between changes in GPs’ job satisfaction before and after the introduction of the QOF and the proportion of their income. They found no significant effects of P4P exposure on overall job satisfaction .The level of exposure to P4P does not harm job satisfaction or other aspects of working lives such as: working hours; intentions to quit; life satisfaction.

Contrary, Krauth et al.,.,[20]showed that among 2493 general practitioners (GPs) in Lower Saxony the participation rate to P4P increased from 28% (at a bonus of 2.5%) to 50% (at a bonus of 20%).

Discussion

There has been a growing interest in the use of financial incentives in order to improve quality of healthcare.[21]

In this article, the authors reviewed different GPs perceptions relate to the design and implementation of pay-for-performance initiatives.

A crucial element for the successful implementation of P4P is to gain acceptance with health care providers.[20]

The impact of these new remuneration schemes is also likely to be influenced by a number of other factors such as levels of physician understanding of the purpose and involvement in the development of the scheme; the nature, appropriateness, and adequacy of measures used; the feasibility of implementation; and the magnitude of an incentive necessary to produce the behavioral change required to achieve targets. Other factors include the balance between team and individual incentives.[6, 22–24]

Most practices considered the bonus a stimulus to improve quality of care, in addition to compensation for their effort and time invested.[18]

Our study provides qualitative evidence that practices incentivized had made substantial changes in systems, and that the changes were focused on delivering improved care.

Nevertheless, the efficiency of this additional payment is debated, and the need to implement target payment schemes is questionable because the relationship between pay and performance has not been well understood.[1]

This study suggests that despite pay for performance is successfully accepted, in few cases does appear to have had a negative impact on some aspects of medical professionalism, with a perception that it was, in part, responsible for GPs prioritizing their own pay rather than patients’ interests and reduced clinical autonomy.

In order to convince GPs to participate in P4P, better evidence for the effectiveness of P4P is required and program implementation must be well communicated and thoroughly discussed with health care providers.[20]

References

  1. Allen T, Whittaker W, Sutton M (2017) Does the proportion of pay linked to performance affect the job satisfaction of general practitioners?.Social Science & Medicine. 1;173: 9–17. [crossref]
  2. Scott A, Sivey P, Ait Ouakrim D, Willenberg L et al. (2011) The effect of financial incentives on the quality of health care provided by primary care physicians. In Cochrane Database of Systematic Reviews. John Wiley&Sons,Ltd. Retrieved from http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD008451.pub2/ abstract [crossref]
  3. Martin Roland D. (2004) Linking physicians’ pay to the quality of care—a major experiment in the United Kingdom. New England Journal of Medicine. 351: 1448–54.27;355(4): 375–84. [crossref]
  4. Campbell S, Reeves D, Kontopantelis E, Middleton E et al. (2007) Quality of primary care in England with the introduction of pay for performance. New England Journal of Medicine. 12;357(2): 181–90.
  5. Doran T, Fullwood C, Gravelle H, Reeves D,et al.(2006) Pay-for-performance programs in family practices in the United Kingdom. New England Journal of Medicine.
  6. Rosenthal MB, Frank RG, Li Z, Epstein AM. (2005) Early experience with pay-for-performance: from concept to practice. Jama. 294(14): 1788–93. [crossref]
  7. Petersen LA, Woodard LD, Urech T, Daw C, et al. (2006) Does pay-for-performance improve the quality of health care?. Annals of internal medicine. 145(4): 265–72. [crossref]
  8. Campbell SM, Reeves D, Kontopantelis E, Sibbald B, et al. (2009) Effects of pay for performance on the quality of primary care in England. New England Journal of Medicine. 361(4): 368–78.
  9. Kirschner K, Braspenning J, Jacobs JA, Grol R. (2012) Design choices made by target users for a pay-for-performance program in primary care: an action research approach. BMC Family Practice. 13(1): 25.
  10. Campbell SM, McDonald R, Lester H. (2008) The experience of pay for performance in English family practice: a qualitative study. The Annals of Family Medicine. 6(3): 228–34. [crossref]
  11. Chaix-Couturier C, Durand-Zaleski I, Jolly D, Durieux P (2000) Effects of financial incentives on medical practice: results from a systematic review of the literature and methodological issues. International Journal for Quality in Health Care. 12(2): 133–42. [crossref]
  12. Whalley D, Gravelle H, Sibbald B (2008) Effect of the new contract on GPs’ working lives and perceptions of quality of care: a longitudinal survey. Br J Gen Pract. 58(546): 8–14. [crossref]
  13. Beckman H, Suchman AL, Curtin K, Greene RA (2006) Physician reactions to quantitative individual performance reports. American Journal of Medical Quality. 21(3): 192–9.
  14. McDonald R, Harrison S, Checkland K, Campbell SM, et al. (2007) Impact of financial incentives on clinical autonomy and internal motivation in primary care: ethnographic study. Bmj. 334(7608): 1357.
  15. Lester H, Matharu T, Mohammed MA, Lester D,et al.(2013) Implementation of pay for performance in primary care: a qualitative study 8 years after introduction. Br J Gen Pract. 63(611): e408–15. [crossref]
  16. Maisey S, Steel N, Marsh R, Gillam S, et al. (2008) Effects of payment for performance in primary care: qualitative interview study. Journal of health services research & policy. 13(3): 133–9. [crossref]
  17. Feng Y, Ma A, Farrar S, Sutton M. (2015) The Tougher the Better: an economic analysis of increased payment thresholds on the performance of General Practices. Health economics. 24(3): 353–71.
  18. Kirschner K, Braspenning J, Jacobs JA, Grol R. (2013) Experiences of general practices with a participatory pay-for-performance program: a qualitative study in primary care. Australian journal of primary health. 19(2): 102–6.
  19. Greene J, Hibbard JH, Overton V. (2015) Large performance incentives had the greatest impact on providers whose quality metrics were lowest at baseline. Health Affairs. 34(4): 673–80. [crossref]
  20. Krauth C, Liersch S, Jensen S, Amelung VE. (2016) Would German physicians opt for pay-for-performance programs? A willingness-to-accept experiment in a large general practitioners’ sample. Health Policy. 120(2): 148–58. [crossref]
  21. Christianson JB, Leatherman S, Sutherland K (2008) Lessons from evaluations of purchaser pay-for-performance programs. Medical Care Research and Review. 65(6_suppl): 5S-35S. [crossref]
  22. Young GJ, White B, Burgess Jr JF, Berlowitz D, et al. (2005) Conceptual issues in the design and implementation of pay-for-quality programs. American Journal of Medical Quality. 20(3): 144–50. [crossref]
  23. Town R, Kane R, Johnson P, Butler M (2005) Economic incentives and physicians’ delivery of preventive care: a systematic review. American journal of preventive medicine. 28(2): 234–40. [crossref]
  24. Fisher ES. (2006) Paying for performance—risks and recommendations. New England Journal of Medicine. 355(18): 1845–7.

Genome and Epigenomic Study of Psoriasis

DOI: 10.31038/JMG.2018115

Abstract

Genome-wide association studies (GWAS) of psoriasis have identified 86 susceptibility loci. Most of these loci are located in non-coding regions,which makes it difficult for researchers to determine the functional effect of these risk-associated variants. One hypothesis is that these single nucleotide polymorphisms (SNPs) cause changes in gene expression levels rather than changes in protein function. In this review, we will focus on advances in psoriasis genomics and introduce epigenomic approaches that incorporate functional annotation of regulatory elements to prioritize the disease risk-associated SNPs which are located in non-coding regions of the genome.

Keywords

GWAS, psoriasis, SNP, epigenomic, ATAC-seq

Psoriasis (Ps) is a common inflammatory skin disorder caused by genetic and epigenetic factors with various environmental triggers in predisposed individuals.[1] The first study that sought to illuminate the genetic architecture of psoriasis is based on linkage analysis. Up to now, nine different regions have been identified (known as Psoriasis Susceptibility (PSORS)1-9).[2] The PSORS1 locus maps to the Major Histocompatibility Complex (MHC) on chromosome 6p21, has been robustly validated in all examined cohorts. [2] PSORS2 and PSORS 4 have been found to show weaker linkage signals, [3,4] while linkage to the remaining PSORS regions (PSORS-3, -5, -6, -7, -8, -9) could not be replicated in independent studies.[2]

In the early 2000s, researchers witnessed important advances in the effort to catalogue human genetic variation and in the development of high-throughput genotyping technology. In 2009, we reported the first large GWAS in a Chinese population, identified a new susceptibility locus within the LCE gene.[5] By now, the number of susceptibility loci had grown to 86. Meanwhile, samples sizes grew at a steady pace, with the latest published GWAS reporting the analysis of 19,000 cases and 280,000 controls.[6] The candidate genes identified so far tend to cluster around immune pathways. These include antigen presentation (HLA-C and ERAP1), innate antiviral signaling (IFIH1DDX58TYK2RNF114) and most notably, the interleukin 23 (IL-23)/T-helper 17 (TH17) pathway.[7]

Genetic studies of psoriasis have revealed robust and reproducible signals that implicate genes involved in core immunologic processes,[8] but only a small number of these genomic segments span a single gene, with the majority encompassing multiple transcripts and some mapping to gene deserts. What is the most relevant path for psoriasis genetics research going forward? Finding more genes through ever-larger case-control studies, with smaller and smaller detectable effects, remains a useful pursuit, however, it has been proven that in addition to genetic predisposition factors, epigenetic factors also play a role in the onset and progression of Ps. Additionally, most noncoding risk variants, including those that alter gene expression, affect non-canonical sequence determinants which are not well-explained. Thus, it is of key importance to use epigenomics engineering to understand the pathogenesis of Ps, armed with the genetic information we have.

In 2016, we first present epigenome-wide association analysis in large samples size in Chinese Han Ps patients, identified nine skin DNA methylation loci for psoriasis. We found that 11 of 93 SNP-CpG pairs, composed of 5 unique SNPs and 3 CpG sites, presented a methylation-mediated relationship between SNPs and psoriasis. Which supported the evidence that DNA methylation can be controlled by genetic factors.[9, 10]

 According to data, above 90% of index SNPs in the GWAS catalog that have been associated with specific diseases or traits lie within non-coding regions. This holds true even when we employ fine mapping techniques to pinpoint the location of these risk-associated variants. Besides, as we attempt to sift through the long list of SNPs, we require some criteria for determining which SNPs are most deserving of follow-up analysis. One such criterion is to determine whether a given SNP falls within a functional region of the genome. Recently, a great progress in genome-wide epigenomic technique, make large-scale epigenetic biomarker annotation of diseases possible, these techniques including (i) Bisulfite sequencing to determine DNA methylation at base-pair resolution, (ii) Chip-Seq to identify protein binding sites on the genome, (iii) DNasel-Seq /ATAC-Seq to profile open chromatin and (iv) 4C-Seq and HiC-Seq to determine the spatial organization of chromosomes.[11]

One kind of functional SNP are the SNPs located in regulatory regions of the genome (regulatory SNPs). Recently, ATAC-seq, a method that employs an engineered Tn5 transposase to measure chromatin accessibility, has been used to define genomic maps of open chromatin. The entire set of DHSs (DNase-hypersensitive) includes promoter regions, distal enhancer regions, and sites of binding of structural TFs. Chip-seq and antibodies specific to histone modifications can be used to further refine the set of distal DHSs to include only active enhancers. Several studies have shown that index and corrected SNPs are enriched in enhancers, and several of these index SNPs created or disrupted TF motifs in the identified enhancers.[12]

Another way to identify risk-associated SNPs is to focus on the subset that show allele-specific gene expression differences, based on expression quantitative trait loci (eQTL). Which are defined as genomic regions that harbor one or more nucleotide variants that correlate with differences in gene expression.[13] For eQTL analyses, SNPs are mapped using a genotyping array and mRNA abundance is measured by RNA-seq using hundreds of samples from cell lines or tissues. Statistical methods are then used to associate SNPs with transcripts to identify eQTLs.[14] Expression associated SNPs can be statistically significantly associated with genes that are located in a genomic region near to or far from the SNP in question, named cis- and trans- eQTL separately. Most studies focus on cis-eQTL because trans-eQTL require multiple testing to gain statistical power.[15] One compensatory technique of finding genes affected by a risk-associated effect far away is Circular chromosome confirmation capture (4C-seq) assay or Hi-C.

The combination of methods discussed above offer a general methodology for the investigation of risk-associated SNPs in non-coding regions of the genome. One article which demonstrates this approach is “genetic determinants of co-accessible chromatin regions in activated T cells across humans” published in Nature Genetics. To understand how variants in non-coding regions modulate gene regulation in health and disease, the authors carried out ATAC-seq, RNA-seq and Hi-C, in T helper cells with a large sample size. They showed that 15% percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have their largest effects on co-accessible peaks, are associated with gene expression, and are enriched for autoimmune disease variants. This research shed light on the epigenomic study of autoimmune diseases.

Finally, we must bear in mind the overall rationale for the use of GWAS experiments. This is to help us better understand the complete set of genes which contribute to the predisposition to, and pathogenesis of Ps. We must be cognizant of the fact that non-coding SNPs can affect the expression of downstream genes both directly and indirectly. For this reason, multi-layered experimental designs, which include identification of risk-associated loci, genomic manipulation, and subsequent gene expression analyses are of particular importance as we continue to search for novel diagnostic and therapeutic targets.

References

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  2. International Psoriasis Genetics Consortium. The International Psoriasis Genetics Study: Assessing linkage to 14 candidate susceptibility loci in a cohort of 942 affected sib pairs. Am J Hum Genet. 2003 Aug 73. DOI:10.1086/377159
  3. Enlund F, Samuelsson L, Enerback C, Inerot A, et al. Analysis of three suggested psoriasis susceptibility loci in a large Swedish set of families: Confirmation of linkage to chromosome 6p (HLA region), and to 17q, but not to 4q. Hum Hered. 1999 Jan 49. DOI: 10.1159/000022832.
  4. Capon F, Novelli G, Semprini S, Clementi M, et al. Searching for psoriasis susceptibility genes in Italy: Genome scan and evidence for a new locus on chromosome 1. J. Investig. Dermatol. 1999 Jan 112. DOI: 10.1046/j.1523-1747.1999.00471.x.
  5. Zhang XJ, Huang W, Yang S, Sun LD et al. Psoriasis genome-wide association study identifies susceptibility variants within LCE gene cluster at 1q21. Nat Genet. 2009 Feb 41. DOI: 10.1038/ng.310.
  6. Tsoi LC, Stuart PE, Tian C, Gudjonsson JE, et al. Large scale meta-analysis characterizes genetic architecture for common psoriasis associated variants. Nat. Commun. 2017 May 24,DOI: 10.1038/ncomms15382.
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  8. Tsoi LC, Stuart PE, Tian C, Gudjonsson JE, et al. Large scale meta-analysis characterizes genetic architecture for common psoriasis associated variants. Nat Commun. 2017 May 24. DOI: 10.1038/ncomms15382.
  9. Zhou F#1,2,3, Shen C#1,4, et al. (2016) Epigenome-wide association data implicates DNA methylation-mediated genetic risk in psoriasis. Clin Epigenetics 8: 131. [crossref]
  10. Zhou F1, Wang W2, Shen C2, Li H2, Zuo X2, et al. (2016) Epigenome-Wide Association Analysis Identified Nine Skin DNA Methylation Loci for Psoriasis. J Invest Dermatol 136: 779–787. [crossref]
  11. Dirks RA1, Stunnenberg HG1, Marks H1 (2016) Genome-wide epigenomic profiling for biomarker discovery. Clin Epigenetics 8: 122. [crossref]
  12. Ernst J1, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, et al. (2011) Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473: 43–49. [crossref]
  13. Albert FW1, Kruglyak L2 (2015) The role of regulatory variation in complex traits and disease. Nat Rev Genet 16: 197–212. [crossref]
  14. Gibson G, Powell JE2, Marigorta UM1. Expression quantitative trait locus analysis for translational medicine. Genome Med. 2015 Jun 24. DOI: 10.1186/s13073-015-0186-7.
  15. Westra HJ, Peters MJ, Esko T, Yaghootkar H, et al., Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat Genet. 2013 Oct 45. DOI: 10.1038/ng.2756.

Functional Assessment for Decision-Making Regarding Return to Sports Following ACL Reconstruction: A Comparison of Football Players with Normative Data

DOI: 10.31038/IJOT.2018112

Abstract

Context

In order to objectively evaluate knee function after anterior cruciate ligament reconstruction and a patient’s possible return to sport, a standardized and easy-to-use test battery has been developed.

Objective

The aim of this study was to compare the outcomes of a test battery in football players with data of are ference group.

Design

Cross-sectional study.

Setting

Strength training facility and university laboratory.

Participants

Thirty-four male football players (21. 4 ± 4. 1years, 179. 9 ± 4. 9cm, 73. 6 ± 6. 1kg) of a professional football club and a cohort (n = 52) of healthy, physical active population (24. 8 ± 3years, 179. 0 ± 5. 7cm, 74. 8 ± 6. 3kg) were included in the study.

Intervention

Participants completed a test battery consisting of seven functional tests; a two-legged and one-legged stability test, a two-legged and one-legged counter movement jump with height and power calculations, speedy jumps, plyometric jumps and a quick feet test.

Main outcome measures

Balance score, jump height, contact time, time to complete jump tasks.

Results

Football players differed in regard to jump height in the two-legged counter movement jump (45. 2 ± 5cm vs. 42. 0 ± 6cm; p = 0. 009) and the one-legged counter movement jump with the non-dominant leg (25. 0 ± 3cm vs. 29. 4 ± 6; p<0. 001), and showed higher jump heights in the plyometric jumps (39. 0 ± 6cm vs. 33. 5 ± 9cm; p = 0. 001). Contact time was shorter in the reference group (141 ± 22ms vs. 186 ± 36ms; p<0. 001), whereas Football players completed the jump parkour quicker.

Conclusions

A higher jump and agility test performance in football players is indicating training specific adaptations related to the demand of the game. Establishing football specific norm data might be of interest for future research.

Keywords

Football (soccer), Test Battery, Return to play, Performance Diagnostic, Hop performance, Knee function

Introduction

After rupture of the Anterior Cruciate Ligament (ACL), most athletes are advised to undergo ACL reconstruction (ACLR) when they wish to continue in their sports [1, 2]. In a high risk full contact sport such as football, ACLR rate is high [3]. Clearance for most athletes after ACLR is typically given within the first year after surgery [4, 5]. In post-surgery treatment and rehabilitation, every individual needs closer examination, as longstanding deficits in strength and neuromuscular control of the lower extremity were reported on average 3 years after an ACLR [6]. Research has been intensified in the last decade and training methods were improved, however, injury incidence remains on an unchanged level [7]. Risk factors for a re-rupture or a secondary injury of the lower extremity may be attributed to deficits in muscle function compared to the pre-injury level [8]. Athletes who do not successfully return to their pre injury level of competition after an ACL injury is another aspect [1, 4, 9].

Many test batteries have been developed in the last decade, in order to assess functional capabilities in ACLR patients and to support decision-making for return to sports [10–13]. Usually they contain isokinetic strength tests, hop tests for height and distance, side hop tests, and jump- landing tasks [2, 10, 11, 14, 15]. A standardized and easy-to-use test battery has been developed to support clinicians in their decision regarding a patient’s return to sport, enabling an objective evaluation of knee function. [12, 13] This test battery includes seven functional tests, norm data from healthy individuals were also established and the tests showed a moderate-to-high reliability [13]

However, it is questionable if norm data from healthy, athletically active individuals also apply for football specific groups. Therefore, norms should be available for every specific sport group. Additionally, if an athlete’s performance outcome of the test battery is registered regularly, personal performance data are available in the case of an injury. The purpose of this study was to compare norm data of a test battery with the performance data of football players achieved with the same test battery. It was hypothesized that football players had better outcomes in the functional tests than norm data from healthy and physical active individuals, which would argue in favor to the need of population specific norms.

Materials and methods

A two cohort design was used to evaluate data from a functional test battery in football players with normative data. Data for the normative cohort were obtained from a previous study which followed a comparable methodological approach as the present investigation (shortly outlined below) [13]. Only data from male participants were used for data analysis. For the football cohort, a total of 34 male, healthy football players aged between 17 and 32 years participated in the study. Detailed description of the participants is shown in Table 1.

Study sample compromised two teams of one professional football club playing in the second highest national league and in the highest amateur league (3rd tier). Sample size resulted from the available players of the team squad. Functional testing was conducted in the fitness facilities prior to team training with at least 72 hours between the last match. Participants completed a standardized warm up program on a stationary bicycle (8 minutes cycling with 1 Watt/kg body weight) and 2 minutes of rope skipping at their own pace. When needed, participants were allowed to conduct squats, lunges, dynamic stretching prior to testing. To determine the dominant leg participants were asked which leg they preferred for kicking, which leg they preferred for jumping and a push-forward test (participants were pushed from behind and the leg which they used in the first step was recorded) was conducted. Dominant side was defined when at least two test matched accordingly. All subjects were evaluated by the same examiners. Subjects wore their training clothes without shoes and socks. The study was approved by the institutional review board for ethical questions in science of the University of Innsbruck (9/2015) and was conducted according to the Declaration of Helsinki [16]. The study staff was trained in good clinical practice and all participants granted written informed consent prior to participation.

Table 1. Descriptive participant demographics.

All participants

(N = 85)

Football players

(n = 34)

Norm population

(n = 51)

p-value

Age (years)

23.4 ± 4

21.3 ± 4

24.8 ± 3

<0.001

Height (cm)

179.4 ± 5

180.0 ± 5

179.0 ± 6

n.s.

Mass (kg)

74.3 ± 6

73.4 ± 6

74.8 ± 6

n.s.

BMI (kg/m2)

22.7 ± 1

22.6 ± 1

22.7 ± 2

n.s.

Functional Testing

The Back in Action (BIA) test battery (CoRehab, Trento, Italy) is designed for sportive users in healthy conditions or in any phase of a recovery period after an injury. The test measures dynamically the balance, the speed and the strength in respect to normative data from a large group of healthy individuals. As a further optional outcome, a back to sport indicator (BIA indicator) is also provided. This BIA indicator compares the test score with the individual score of an athlete if the test battery has been conducted pre-injury, otherwise a comparison with an age-matched reference group will be made. The test battery “Back in Action” can be accomplished within 45 min, needs little equipment and only one room. It consisted of the following subtests: a two-legged (TL-ST) and one- legged stability test (OL-ST), a two-legged (TL-CMJ) and one-legged counter movement jump with height and power calculations (OL-CMJ), speedy jumps (OL-SY), plyometric jumps (TL-PJ) and a quick feet test (TL-QFT) [12, 13]. The TL-ST and the OL-ST is used to assess postural control and the tests were performed on an MFT Challenge Disc (TST Trendsport, Grosshöflein, Austria) connected to a PC. The disc is free to move in all directions. While balancing on the disc, the software provides instant feedback about the position of the disc. To avoid the influence of different shoe types, all trials were performed without shoes. Subjects were instructed to stand in the center with their arms at their sides [13]. In TL-ST, subjects had to stand with both legs on the disc while maintaining their balance for 30 seconds. Data collection was immediately stopped in the case of a loss of balance whereas the OL-ST was performed with one leg. The subject was not allowed to stabilize the raised leg against the plate or standing leg [13]. In the TL-CMJ subjects quickly bent their knees from an upright position and then immediately jumped upward, attempting to maximize their height. During this hop, arms were placed on the hips while the OL-CMJ was similar to the two-leg test, but this test was performed with one leg [13]. In the TL-PJ, the subject had to perform three consecutive two-leg jumps, focusing on a maximum jump height and a fast ground contact time. Arms could be used to assist with the jump [13]. For the OL-SY, the Speedy Basic Jump Set (TST Trendsport, Grosshöflein, Austria) was used to create the jump coordination path. The subjects performed one-footed jumps through the course of red (forward backward–forward jumps) and blue (sideway jumps) hurdles, completing 16 jumps. This had to be performed as quickly as possible by jumping on one leg without a rest between the hurdles. Twisting of the hip was not allowed, and the test was immediately stopped when the raised leg touched the ground or the subject had direct contact with the speedy basic jump hurdles. The test was performed for both legs separately. Time was measured using a stopwatch beginning as soon as the subject started to jump and ending when players reached the finish line with one leg. The mean value was recorded for each jump [13]. For the TL-QFT, the Speedy Basic Jump Set (TST Trendsport, Grosshöflein, Austria) was also used to create a tapping zone. The subject had to step in and out with one foot after the other until 15 repetitions were completed. One repetition was finished when the starting leg returned to its initial position. The test was stopped if the subject reversed the order of the steps. Arms could be used to maintain balance, and stepping on the speedy pole was not allowed [13]. Again, time was measured using a stopwatch. In TL-ST and OL-ST, low values represent a better outcome. For the TL-CMJ, the OL-CMJ, and the TL-PJ higher values are preferable, whereas contact time in TL-PJ should be as short as possible. For OL-SY and TL-QFT quick times represent a better result. The order of the applied tests was held constant between the two cohorts. None of the cohorts conducted a special familiarization session, however the first trial in each subtest served as a test trial and the results were not recorded. Test–retest reliability for each sub-test was determined using the intraclass correlation coefficient (ICC 1/1) in the one-way random effects model. The ICC indicated a high reproducibility for the TL-CMJ (0. 921) and a moderate reproducibility for the TL-ST (0. 688). All other tests showed good test–retest reliabilities [13]. With respect to the jump tests, the reference group was measured with the Myotest System (Myotest, Sion, Switzerland), whereas the football players were measured with the accelerometer device and its software solution provided from the BIA test battery company (CoRehab, Trento, Italy). Comparison of the two jump sensors detected a mean error of approximately 0. 7 cm, and a maximum error of 1. 6 cm in the countermovement jump [17].

Statistical analysis

All variables were displayed descriptively including mean, standard deviation (SD), 95% confidence interval (95% CI) and proportion, respectively. Normality of distribution was checked with the Kolmogorov-Smirnov test and box plots. Independent t-tests were used to compare data of the football players with data of the reference group. Statistical significance was accepted for p ≤0. 05. All statistical analyses were performed with IBM SPSS Statistics for Windows, Version 24. 0 (Armonk, NY: IBM Corp). G*Power 3. 1. 9. 2 (Franz Paul, Kiel, Germany) was used to calculate Cohens d effect size.

Results

Football player and the normal population showed a similar body stature (p>0. 05), however, football players on average were somewhat younger than the normal population (p<0. 001, Table 1). A significant difference in the TL-CMJ for height with higher values in the norm population (p = 0. 009) were measured. Higher values in football players were found in the OL-CMJ for height in the dominant leg (p<0. 001). Football players jumped significantly higher in the TL-PJ (p = 0. 002), whereas the norm population showed significantly shorter contact time (p<0. 001). OL-SY showed significant differences in the dominant (p = 0. 022) and the non-dominant leg (p = 0. 018) with quicker times in football players. No differences in the other functional tests were present. Detailed results of the functional tests are displayed in Table 2.

Discussion

The main finding of this study is that several tests differed between football players and the reference group. Participants of the healthy and athletically active reference group jumped significantly higher than football players in the TL-CMJ, although power output showed no differences. Football players jumped significantly higher in the OL-CMJ with the non-dominant leg, and higher power output were observed in football players in both the dominant and non-dominant leg. They showed higher jump heights in the plyometric jumps, however, contact time was shorter in the norm population. Football players completed the jump parkour in a faster time, while no differences in the quick feet test were present.

For sports in general, and especially for injury protection, it is important to produce high force quickly. [18] With its dynamic explosive force production capacity, the CMJ is used to possibly assess knee extensor strength. [19, 20] In the present study, higher jump heights in the TL-CMJ were recorded in the reference group. These results are somehow unexpected, as the football cohort consisted of professional and semi-professional football players with a daily training regime and at least 8h/week or more of training. Moreover, professional football squad members are typically more exposed to physical testing [21] and thus should be experienced with testing methods, especially with the countermovement jump. The use of two different jump sensors might have led to this apparent discrepancy. Additionally, it could be argued that the TL-CMJ as a test is not able to discriminate football players from a healthy and physical active population. However, football players showed higher jump values in the one-legged CMJ, supporting the assumption that football players reach higher values due to the specifity of training and the physical demand of their sport.

Table 2. Results of the test battery.

All participants (N = 85)

Football players (n = 34)

Norm population (n = 51)

Football vs. Norm

p-value

Effect size d

mean±SD

mean±SD

mean±SD

∆ (95% CI)

Two-legged stability test

2.71 ± 0.5

2.73 ± 0.5

2.69 ± 0.5

0.04

(±0.22)

n.s.

0.08

One- legged stability test

Dominant leg

2.5 ± 0.4

2.53 ± 0.4

2.48 ± 0.5

0.05

(±0.20)

n.s.

0.11

Non-dominant leg

2.49 ± 0.4

2.48 ± 0.4

2.49 ± 0.4

-0.01

(±0.17)

n.s.

0.025

Two-legged counter movement jump

Height (cm)

43.9 ± 6

42.0 ± 6

45.2 ± 5

-3.24

(± 2.42)

0.009

0.58

One-legged counter movement jump with height calculation (cm)

Dominant leg

28.3 ± 5

29.3 ± 5

27.6 ± 4

1.62

(±1.97)

n.s.

0.38

Non-dominant leg

26.8 ± 5

29.4 ± 6

25.0 ± 3

4.37

(±2.13)

<0.001

0.93

Plyometric jumps

Height (cm)

35.7 ± 8

39.0 ± 6

33.5 ± 9

5.51

(±3.44)

0.001

0.72

Time (ms)

159 ± 36

186 ± 36

141 ± 22

44.5

(±12.7)

<0.001

1.5

Reactive strength index
(mm/ms)

2.3 ± 0.5

2.1 ± 0.3

2.4 ± 0.5

-0.24

(±0.19)

0.011

0.73

Speedy jumps (s)

Dominant leg

5.71 ± 0.7

5.51 ± 0.5

5.84 ± 0.7

-0.33

(±0.28)

0.022

0.54

Although better proprioception in Olympic-level male football players compared to sex-matched non-athletes were found in a previous study [22], no statistically significant differences between football players and the reference group existed in the stability tests. The stability test used in this evaluation might not have been able to show possible differences as a rather general stability index is assessed with the test that might not necessarily represent specific adaptations to football training and play.

In regard to the plyometric jumps, football players showed higher jump, however, contact time was shorter in the reference group. Although both cohorts have been instructed the same way (jump as high as you can with as little contact time as possible), football players have intuitively increased contact time to increase force production and to consequently achieve a higher jump height. The Plyometric jump test reproduces the stretch-shortening cycle, which is important for movement initiation and acceleration performance [23]. Muscle–tendon behavior of the agonists is optimized with alteration in the neuromuscular activity and an increase in tendon stiffness during plyometric exercises, while there is a decrease in the neuromuscular activity of antagonists during a counter movement [24]. In football, players are required to repeatedly perform short, explosive efforts such as accelerations and decelerations during change of direction [25]. Reactive strength, specifically to change rapidly from eccentric to concentric action, affects these agility performance actions [23, 26]. As these actions are repeatedly linked to non-contact ACL injuries [25], the focus in football players should be on developing a better muscle activation pattern and therefore reducing contact time while maintaining the jump height. In the speedy jump test, football players showed faster time values than the reference group for both legs. Football training is aimed to develop speed and reactivity, which arguably may influence speedy jump test outcomes. The specific training regime adopted by football teams thus might explain the better speed jump test performance compared to the reference population. As this test is performed with one leg, the test provides single leg performance parameters and might also be useful to detect bilateral differences in the operated and non-operated leg. This might be of special importance when considering that long term deficits in strength and neuromuscular control of the lower extremity after an ACLR exist [6] which might be risk factors for a re-rupture or a secondary injury of the lower extremity [8]. Assessment of maximum speed in lower limb movement is typically recorded by a foot tapping test [27], with only little equipment the quick feet test offers a comparable result. As no differences between football players and the reference group were found in the quick feet test, it has to be questioned if this test specifically covers football relevant skills.

There are several advantages when clinically assessing functional performance. When it comes to detect possible asymmetries and therefor adapt training methods, objective data are advantageous. The test battery assesses balance, speed and strength, and a high level of both strength and power variables are preferable in football, on the one hand for a possible injury risk reduction, on the other hand for allowing more powerful jumps, kicks, tackles, and sprints [28, 29]. Once completed pre-injury, an objective evaluation about the functional readiness to return to sports after ACLR is possible. Using the amount of time postoperatively often as the only criterion [30, 31] and still lacking consensus for clearing patients to unrestricted sports activities after ACLR [2, 32], this test battery may support clinicians in their decision making regarding return to sports.

Some limitations of the study have to be acknowledged. Reference data were obtained from a prior study under slightly different conditions as outlined before. In this regard the usage of a different jump sensor in each cohort has to be recognized as a possible source of deviations in jump height assessment for the two-legged countermovement jump. However, comparable results were obtained in the evaluation of the two jump sensors. Further, football players were playing in the second and the third tier. Thus as data from amateur football players at a lower performance level were not recorded, the values established in this study are only valid for the specific group tested.

Conclusion

A comparison of the test battery in football players and the reference group detected several differences in performance. Establishing football specific norm data with this easy to use test battery might be of interest for future research. The test battery delivers valuable information about physical capabilities and side-to-side differences. Once completed pre-injury, functional readiness to return to sports may be evaluated objectively with the player’s data. Collecting pre-injury data in order to optimize the course of rehabilitation and decision-making for return to sports should be established as a best-practice strategy.

Conflict of Interest: The authors declare that they have no conflict of interest related to this study.

Acknowledgement: The study group would like to thank all of the study participants for their efforts. Special thanks to Karl Schwarzenbrunner for functional testing.

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