Effectiveness of the online-eLearning program KeepCoool at improving the vaccine cold chain in general practices.

BACKGROUND: Protecting vaccines from freeze damage is a poorly addressed problem. We describe the effectiveness of the eLearning KeepCoool on cold chain maintenance in general practices. METHODS: For this intervention study, temperatures of vaccine refrigerators were logged at one-minute intervals. Personnel from practices with cold chain breaches was offered the eLearning. The primary outcome was the intervention's effectiveness to achieve temperatures in the target range (2 to 8°C) in the sixth week (follow-up) compared to the first (baseline). Using continuous temperature data, a generalized additive model for location, scale and shape was estimated. RESULTS: The practice response rate was 38% (64 of 168). At baseline, 73% of the practices and 68% of the refrigerators (51 of 75) showed cold chain breaches. 47% of the practices (n = 22 with 24 refrigerators) participated in the eLearning (55 physicians and practice assistants). At follow-up, 17% of those refrigerators were in the target range continuously, 38% reached targets 95% of the time while always >0°C, and temperatures ≤0°C decreased by 63%. Based on 2 million temperature data, the average Euclidian distance based on regression showed a significant improvement (p<0.05). CONCLUSION: The eLearning KeepCoool improved the practices´ vaccine cold chain. It is freely available at https://keepcoool.ukbonn.de.

Development of a clinical algorithm to predict phenotypic switches between atopic dermatitis and psoriasis (the "Flip-Flop" phenomenon).

BACKGROUND: Atopic dermatitis (AD) and psoriasis vulgaris (PV) are almost mutually exclusive diseases with different immune polarizations, mechanisms and therapeutic targets. Switches to the other disease ("Flip-Flop" [FF] phenomenon) can occur with or without systemic treatment and are often referred to as paradoxical reactions under biological therapy. METHODS: The objective was to develop a diagnostic algorithm by combining clinical criteria of AD and PV to identify FF patients. The algorithm was prospectively validated in patients enrolled in the CK-CARE registry in Bonn, Germany. Afterward, algorithm refinements were implemented based on machine learning. RESULTS: Three hundred adult Caucasian patients were included in the validation study (n = 238 with AD, n = 49 with PV, n = 13 with FF; mean age 41.2 years; n = 161 [53.7%] female). The total FF scores of the PV and AD groups differed significantly from the FF group in the validation data (p < .001). The predictive mean generalized Youden-Index of the initial model was 78.9% [95% confidence interval 72.0%-85.6%] and the accuracy was 89.7%. Disease group-specific sensitivity was 100% (FF), 95.0% (AD), and 61.2% (PV). The specificity was 89.2% (FF), 100% (AD), and 100% (PV), respectively. CONCLUSION: The FF algorithm represents the first validated tool to identify FF patients.

Modifications in ocular microperfusion after transcatheter aortic valve implantation.

Cerebral embolization is a known complication of transcatheter aortic valve implantation (TAVI) but the effect of the procedure on the ocular perfusion is currently unclear. Thus, we investigated post-procedural morphologic and perfusion changes of the retina and choroid, using optical coherence tomography angiography (OCTA) and color fundus photography (CFP) in a prospective cohort study. Ophthalmic examinations were conducted pre- and post-TAVI. OCTA images were analyzed quantitatively based on vessel density and skeleton density of the superficial and deep retinal plexus as well as the signal intensity and flow deficits in the choriocapillaris. CFP images were assessed for presence of acute retinal ischemia, optic nerve swelling, vessel emboli, hemorrhages and cotton wool spots. Data was analyzed using linear mixed models. Twenty patients (9 women; 11 men) at a mean age of 81 ± 6 years were included. Pre- and post-interventional ocular imaging data were available for 32 eyes. The analysis revealed a significant impairment of the choriocapillaris perfusion after TAVI with an increased proportion of flow deficits (p = 0.044). When controlling for blood pressure, the average size of choriocapillaris flow voids was significantly increased (systolic and diastolic, p = 0.039 and 0.029). Qualitatively, focal areas of retinal ischemia were detected on OCTA in 33% of participants. Silent emboli or cotton wool spots were identified on CFP in 21%. Our findings indicate a reduced choroidal perfusion as well as areas of retinal ischemia and embolization in a considerable proportion of patients following TAVI. Pending confirmation in a larger sample, these complications merit monitoring as well as inclusion in consent procedures for TAVI.

Prevalence and Incidence of Registered Severe Visual Impairment and Blindness Due to Uveitis in Germany.

PURPOSE: To assess prevalence and incidence of severe visual impairment (VI) and blindness due to uveitis in Northrhine, Germany. METHODS:  A random sample of 5088 out of 20 390 cases of the blindness registry in Northrhine was evaluated. The number of cases of severe VI and blindness were projected up to the year 2030. RESULTS: The prevalence of registered severe VI and blindness due to uveitis was 1123.9 (95% CI: 1059.5 to 1191.2) per 100 000 in our study cohort and 550.31 (95% CI: 365.98-794.38) per 100 000 in Northrhine, respectively. The incidence of registered severe VI and blindness due to uveitis was 311.8 per 100 000 PYs (95% CI: 149.6-572.7) in our study cohort and 11.1 per 100 000 (95% CI: 5.6-19.8) in Northrhine, respectively. CONCLUSIONS: We report prevalence and incidence of severe VI and blindness due to uveitis in a large German cohort.

IL-13, periostin and dipeptidyl-peptidase-4 reveal endotype-phenotype associations in atopic dermatitis.

BACKGROUND: The heterogeneous (endo)phenotypes of atopic dermatitis (AD) require precision medicine. Currently, systemic therapy is recommended to patients with an Eczema Area and Severity Index (EASI)≥16. Previous studies have demonstrated an improved treatment response to the anti-interleukin (IL)-13 antibody tralokinumab in AD subgroups with elevated levels of the IL-13-related biomarkers dipeptidyl-peptidase (DPP)-4 and periostin. METHODS: Herein, 373 AD patients aged≥12 years were stratified by IL-13high , periostinhigh and DPP-4high endotypes using cross-sectional data from the ProRaD cohort Bonn. "High" was defined as >80th quantile of 47 non-atopic controls. We analyzed endotype-phenotype associations using machine-learning gradient boosting compared to logistic regression. RESULTS: AD severity and eosinophils correlated with IL-13 and periostin levels. Correlations of IL-13 with EASI were stronger in patients with increased (rs=0.482) than with normal (rs=0.342) periostin levels. We identified eosinophilia>6% and an EASI range of 5.5-17 dependent on the biomarker combination to be associated with increasing probabilities of biomarkerhigh endotypes. Also patients with mild-to-low-moderate severity (EASI<16) featured increased biomarkers (IL-13high : 41%, periostinhigh : 48.4%, DPP-4high : 22.3%). Herthoge sign (adjusted Odds Ratio (aOR)=1.89, 95% Confidence Interval (CI) [1.14-3.14]) and maternal allergic rhinitis (aOR=2.79-4.47) increased the probability of an IL-13high -endotype, "dirty neck" (aOR=2.83 [1.32-6.07]), orbital darkening (aOR=2.43 [1.08-5.50]), keratosis pilaris (aOR=2.21 [1.1-4.42]) and perleche (aOR=3.44 [1.72-6.86]) of a DPP-4high -endotype. CONCLUSIONS: A substantial proportion of patients with EASI<16 featured high biomarker levels suggesting systemic impact of skin inflammation already below the current cut-off for systemic therapy. Our findings facilitate the identification of patients with distinct endotypes potentially linked to response to IL-13-targeted therapy.

Dementia risk predictions from German claims data using methods of machine learning.

INTRODUCTION: We examined whether German claims data are suitable for dementia risk prediction, how machine learning (ML) compares to classical regression, and what the important predictors for dementia risk are. METHODS: We analyzed data from the largest German health insurance company, including 117,895 dementia-free people age 65+. Follow-up was 10 years. Predictors were: 23 age-related diseases, 212 medical prescriptions, 87 surgery codes, as well as age and sex. Statistical methods included logistic regression (LR), gradient boosting (GBM), and random forests (RFs). RESULTS: Discriminatory power was moderate for LR (C-statistic = 0.714; 95% confidence interval [CI] = 0.708-0.720) and GBM (C-statistic = 0.707; 95% CI  = 0.700-0.713) and lower for RF (C-statistic = 0.636; 95% CI  = 0.628-0.643). GBM had the best model calibration. We identified antipsychotic medications and cerebrovascular disease but also a less-established specific antibacterial medical prescription as important predictors. DISCUSSION: Our models from German claims data have acceptable accuracy and may provide cost-effective decision support for early dementia screening.

Delayed Cerebral Ischemia after Aneurysmal Subarachnoid Hemorrhage: The Results of Induced Hypertension Only after the IMCVS Trial-A Prospective Cohort Study.

Delayed cerebral ischemia (DCI) is a predictor of poor outcome after aneurysmal subarachnoid hemorrhage (SAH). Treatment strategies vary and include induced hypertension and invasive endovascular treatment. After the IMCVS trial (NCT01400360), which failed to demonstrate a benefit of endovascular treatment for cerebral vasospasm (CVS) and resulted in a significantly worse outcome, we changed our treatment policy in patients with diagnosed CVS to induced hypertension only, and we present our prospective results in the subgroup of SAH patients meeting inclusion criteria of the IMCVS trial. All patients underwent screening for DIND when conscious and for CVS using CT-A/-P at day 6-8 after SAH. In the case of CVS, arterial hypertension was induced and continued until re-assessment. In total, 149 of 303 patients developed CVS. DCI developed in 35 patients (23.5%). In multivariate analyses, CVS was a predictor for the development of new infarctions. Poor admission status, re-bleeding before treatment, and DCI predicted poor outcome. The omittance of invasive endovascular rescue therapies in SAH patients with CVS, additional to induced hypertension, does not lead to a higher rate of DCI. Potential benefits of additional endovascular treatment for CVS need to be addressed in further studies searching for a subgroup of patients who may benefit.

Aneurysmal Subarachnoid Hemorrhage during the Shutdown for COVID-19.

The aim was to evaluate hospitalization rates for aneurysmal subarachnoid hemorrhage (SAH) within an interdisciplinary multicenter neurovascular network (NVN) during the shutdown for the COVID-19 pandemic along with its modifiable risk factors. In this multicenter study, admission rates for SAH were compared for the period of the shutdown for the COVID-19 pandemic in Germany (calendar weeks (cw) 12 to 16, 2020), the periods before (cw 6-11) and after the shutdown (cw 17-21 and 22-26, 2020), as well as with the corresponding cw in the years 2015-2019. Data on all-cause and pre-hospital mortality within the area of the NVN were retrieved from the Department of Health, and the responsible emergency medical services. Data on known triggers for systemic inflammation, e.g., respiratory viruses and air pollution, were analyzed. Hospitalizations for SAH decreased during the shutdown period to one-tenth within the multicenter NVN. There was a substantial decrease in acute respiratory illness rates, and of air pollution during the shutdown period. The implementation of public health measures, e.g., contact restrictions and increased personal hygiene during the shutdown, might positively influence modifiable risk factors, e.g., systemic inflammation, leading to a decrease in the incidence of SAH.

Altered Serum Phospholipids in Atopic Dermatitis and Association with Clinical Status.

Circulating phospholipids have been considered as biomarkers and therapeutic targets in multiple disorders. Atopic dermatitis (AD) is the most common inflammatory skin disease. Although there are numerous studies having addressed stratum corneum lipids in the context of epidermal barrier, little is known about the circulating lipids in patients with AD. In this study, we explored the changes of serum phospholipids in AD using liquid chromatography coupled to tandem mass spectrometry and sought serum lipids' contribution to clinical status. Several serum levels of phospholipids were altered in the AD group (n = 179) compared with that in healthy controls (n = 47) and patients without AD with atopic comorbidities (n = 22); lipids exhibiting the apparent changes included increased sphingosine, multiple variants of phosphatidylcholine, and decreased ceramide (16:0) in patients with AD. Moreover, serum levels of sphingosine correlated with the severity of AD, and sphingosine and ceramide(16:0) were also detected as the risk-increasing effect and risk-reduction effect of AD, respectively. In summary, alterations in the serum concentration of phospholipids are seen in patients with AD. Although more detailed investigations will be needed to evaluate the significance of the changes in circulating lipids in AD, these findings can provide, to our knowledge, previously unreported insight into AD's pathogenesis and therapeutic strategies.

Benchmark of filter methods for feature selection in high-dimensional gene expression survival data.

Feature selection is crucial for the analysis of high-dimensional data, but benchmark studies for data with a survival outcome are rare. We compare 14 filter methods for feature selection based on 11 high-dimensional gene expression survival data sets. The aim is to provide guidance on the choice of filter methods for other researchers and practitioners. We analyze the accuracy of predictive models that employ the features selected by the filter methods. Also, we consider the run time, the number of selected features for fitting models with high predictive accuracy as well as the feature selection stability. We conclude that the simple variance filter outperforms all other considered filter methods. This filter selects the features with the largest variance and does not take into account the survival outcome. Also, we identify the correlation-adjusted regression scores filter as a more elaborate alternative that allows fitting models with similar predictive accuracy. Additionally, we investigate the filter methods based on feature rankings, finding groups of similar filters.

A consistent version of distance covariance for right-censored survival data and its application in hypothesis testing.

Distance covariance is a powerful new dependence measure that was recently introduced by Székely et al. and Székely and Rizzo. In this work, the concept of distance covariance is extended to measuring dependence between a covariate vector and a right-censored survival endpoint by establishing an estimator based on an inverse-probability-of-censoring weighted U-statistic. The consistency of the novel estimator is derived. In a large simulation study, it is shown that induced distance covariance permutation tests show a good performance in detecting various complex associations. Applying the distance covariance permutation tests on a gene expression dataset from breast cancer patients outlines its potential for biostatistical practice.

Sedation versus General Anesthesia for Cardiac Catheterization in Infants: A Retrospective, Monocentric, Cohort Evaluation.

BACKGROUND: Children with congenital heart disease require repeated catheterization. Anesthetic management influences the procedure and may influence outcome; however, data and recommendations are lacking for infants. We studied the influence of sedation versus general anesthesia (GA) on adverse events during catheterization for children <2 years old. METHODS: We conducted a monocentric, retrospective study of all catheterization procedures (2008-2013). High-severity adverse event (HSAE) rates were compared using propensity-score-adjusted models, including pre- and intra-procedural variables. RESULTS: 803 cases (619 patients) (368 (46%) GA, 435 (54%) sedation) with a mean age of 6.9 ± 6.1 months were studied. The conversion rate (GA after sedation) was 18 (4%). Hospital stay was 4.9 ± 4.0 and 4.1 ± 2.5 (p = 0.01) after GA or sedation, respectively. HSAE occurred in 75 (20%) versus 40 (9%) (p < 0.01) in GA versus sedation procedures, respectively. Risk factors (multivariable analysis) were older patients (p = 0.05), smaller weights (p < 0.01), palliated status (OR 3.2 [1.2-8.9], p = 0.02), two-ventricle physiology (OR 7.3 [2.7-20.2], p < 0.01), cyanosis (OR 4.6 [2.2-9.8], p < 0.01), pulmonary hypertension (OR 5.6 [2.0-15.5], p < 0.01), interventional catheterization (OR 1.8 [1.1-3.2], p = 0.02) and procedure-type risk category 4 (OR 28.9 [1.8-455.1], p = 0.02). Sedation did not increase the events rate and decreased the requirement for hemodynamic support (OR 5.2 [2.2-12.0], p < 0.01). CONCLUSION: Sedation versus GA for cardiac catheterization in children <2 years old is safe and effective with regard to HSAE. Sedation also decreases the requirement for hemodynamic support. Paradoxical effects (older age and two-ventricle physiology) on risk have been found for this specific age cluster.

Machine Learning-Based Deep Phenotyping of Atopic Dermatitis: Severity-Associated Factors in Adolescent and Adult Patients.

IMPORTANCE: Atopic dermatitis (AD) is the most common chronic inflammatory skin disease and is driven by a complex pathophysiology underlying highly heterogeneous phenotypes. Current advances in precision medicine emphasize the need for stratification. OBJECTIVE: To perform deep phenotyping and identification of severity-associated factors in adolescent and adult patients with AD. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional data from the baseline visit of a prospective longitudinal study investigating the phenotype among inpatients and outpatients with AD from the Department of Dermatology and Allergy of the University Hospital Bonn enrolled between November 2016 and February 2020. MAIN OUTCOMES AND MEASURES: Patients were stratified by severity groups using the Eczema Area and Severity Index (EASI). The associations of 130 factors with AD severity were analyzed applying a machine learning-gradient boosting approach with cross-validation-based tuning as well as multinomial logistic regression. RESULTS: A total of 367 patients (157 male [42.8%]; mean [SD] age, 39 [17] years; 94% adults) were analyzed. Among the participants, 177 (48.2%) had mild disease (EASI ≤7), 120 (32.7%) had moderate disease (EASI >7 and ≤ 21), and 70 (19.1%) had severe disease (EASI >21). Atopic stigmata (cheilitis: odds ratio [OR], 8.10; 95% CI, 3.35-10.59; white dermographism: OR, 4.42; 95% CI, 1.68-11.64; Hertoghe sign: OR, 2.75; 95% CI, 1.27-5.93; nipple eczema: OR, 4.97; 95% CI, 1.56-15.78) was associated with increased probability of severe AD, while female sex was associated with reduced probability (OR, 0.30; 95% CI, 0.13-0.66). The probability of severe AD was associated with total serum immunoglobulin E levels greater than 1708 IU/mL and eosinophil values greater than 6.8%. Patients aged 12 to 21 years or older than 52 years had an elevated probability of severe AD; patients aged 22 to 51 years had an elevated probability of mild AD. Age at AD onset older than 12 years was associated with increased probability of severe AD up to a peak at 30 years; age at onset older than 33 years was associated with moderate to severe AD; and childhood onset was associated with mild AD (peak, 7 years). Lifestyle factors associated with severe AD were physical activity less than once per week and (former) smoking. Alopecia areata was associated with moderate (OR, 5.23; 95% CI, 1.53-17.88) and severe (OR, 4.67; 95% CI, 1.01-21.56) AD. Predictive performance of machine learning-gradient boosting vs multinomial logistic regression differed only slightly (mean multiclass area under the curve value: 0.71 [95% CI, 0.69-0.72] vs 0.68 [0.66-0.70], respectively). CONCLUSIONS AND RELEVANCE: The associations found in this cross-sectional study among patients with AD might contribute to a deeper disease understanding, closer monitoring of predisposed patients, and personalized prevention and therapy.

Effects of the dementia care toolbox on personnel's self-reported confidence in patient care: a CRT in general practices.

BACKGROUND: In rapidly aging populations, general practitioners (GPs) are challenged in dementia care of patients with and without migration background. Uncertainties in treating dementia in migrant patients due to language barriers or information deficits are reported. To address these deficits, we developed the Dementia Care Toolbox which was judged helpful by GP practice personnel. This two-armed cluster-randomised trial (CRT) investigated the effects of this toolbox on German GPs' and practice assistants' (PrAs) attitudes and confidence in dementia care, especially in patients with migration background. METHODS: A total of 32 GP practices were recruited and randomised into intervention (toolbox use for 3 months) and waiting-list control (toolbox after follow-up). After 3 months all participating GPs and PrAs received a standardised questionnaire addressing their levels of self-reported confidence in dementia care for patients with and without migration background. A generalized estimating equation model that took practice cluster effects into account was applied to assess GPs and PrAs self-reported confidence in dementia care in patients with and without migration background. RESULTS: Overall, the intervention had no significant effect on self-reported confidence in dementia care. However, the use of the dementia care toolbox showed a tendency for a learning effect on knowledge about local support structures for migrant patients with dementia (odds ratio 1.43; 95% CI 0.68-3.03, p = 0.35) and for less communication difficulties with dementia patients in general (odds ratio 0.72; 95% CI 0.33-1.56; p = 0.40). Moreover, intervention practices showed a tendency towards more awareness of own limitations: less self-confidence regarding answering questions (odds ratio 0.82; 95% CI 0.36-1.86, p = 0.64) and providing information for patients with migration background (odds ratio 0.60; 95% CI 0.25-1.45, p = 0.26). CONCLUSION: The Toolbox Dementia Care increased awareness on the respective topic. Given a small sample size, further studies on its effectiveness in primary care are needed. TRIAL REGISTRATION: German Clinical Trials Register, DRKS00014632. Registered 02/08/2018.

Analysis of cesarean section rates in two German hospitals applying the 10-Group Classification System.

OBJECTIVES: In Germany, cesarean section (CS) rates more than doubled within the past two decades. For analysis, auditing and inter-hospital comparison, the 10-Group Classification System (TGCS) is recommended. We used the TGCS to analyze CS rates in two German hospitals of different levels of care. METHODS: From October 2017 to September 2018, data were prospectively collected. Unit A is a level three university hospital, unit B a level one district hospital. The German birth registry was used for comparison with national data. We performed two-sample Z tests and bootstrapping to compare aggregated (unit A + B) with national data and unit A with unit B. RESULTS: In both datasets (national data and aggregated data unit A + B), Robson group (RG) 5 was the largest contributor to the overall CS rate. Compared to national data, group sizes in RG 1 and 3 were significantly smaller in the units under investigation, RG 8 and 10 significantly larger. Total CS rates between the two units differed (40.7 vs. 28.4%, p<0.001). The CS rate in RG 5 and RG 10 was different (p<0.01 for both). The most relative frequent RG in both units consisted of group 5, followed by group 10 and 2a. CONCLUSIONS: The analysis allowed us to explain different CS rates with differences in the study population and with differences in the clinical practice. These results serve as a starting point for audits, inter-hospital comparisons and for interventions aiming to reduce CS rates.

Techniques to improve ecological interpretability of black-box machine learning models.

Statistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects. Gradient boosted trees (GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous U.S., as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations of partial dependence plots (PDP), individual conditional expectation (ICE) curves and accumulated local effects (ALE) in their ability to identify covariate-response relationships. Additionally interaction effects were quantified according to interaction strength (IAS) and Friedman's H2 statistic. Interpretable machine learning techniques are useful tools to open the black-box of gradient boosted trees in the environmental sciences. This finding is supported by our case study on the effect of impervious surface on the benthic condition, which agrees with previous results in the literature. Overall the most important variables were ecoregion, bed stability, watershed area, riparian vegetation and catchment slope. These variables were also present in most identified interaction effects. In conclusion, graphical tools (PDP, ICE, ALE) enable visualization and easier interpretation of GBT but should be supported by analytical statistical measures. Future methodological research is needed to investigate the properties of interaction tests.

Multiple aneurysms in subarachnoid hemorrhage - identification of the ruptured aneurysm, when the bleeding pattern is not self-explanatory - development of a novel prediction score.

BACKGROUND: In aneurysmal subarachnoid hemorrhage (SAH) and multiple intracranial aneurysms (MIAs) identification of the bleeding source cannot always be assessed according to the hemorrhage pattern. Therefore, we developed a statistical model for the prediction of the ruptured aneurysm in patients with SAH and multiple potential bleeding sources at the time of ictus. METHODS: Between 2012 and 2015, 252 patients harboring 619 aneurysms were admitted to the authors' institution. Patients were followed prospectively. Aneurysm and patient characteristics, as well as radiological findings were entered into a computerized database. Gradient boosting techniques were used to derive the statistical model for the prediction of the ruptured aneurysm. Based on the statistical prediction model, a scoring system was produced for the use in the clinical setting. The aneurysm with the highest score poses the highest possibility of being the bleeding source. The prediction score was then prospectively applied to 34 patients suffering from SAH and harboring MIAs. RESULTS: According to the statistical prediction model the main factors affecting the rupture in patients harboring multiple aneurysms were: 1) aneurysm size, 2) aneurysm location and 3) aneurysm shape. The prediction score identified correctly the ruptured aneurysm in all the patients that were used in the prospective validation. Even in the five most debatable and challenging cases assessed in the period of prospective validation, for which the score was designed for, the ruptured aneurysm was predicted correctly. CONCLUSIONS: This new and simple prediction score might provide additional support for neurovascular teams for treatment decision in SAH patients harboring multiple aneurysms. In a small prospective sample, the prediction score performed with high accuracy but larger cohorts for external validation are warranted.

Human spermatozoa of male patients with subfertility express the interleukin-6 receptor.

Male subfertility has been associated with bacterial infections and chronic inflammation. In this context, several studies investigated cytokine levels in seminal plasma, whereas interleukin-6 (IL-6) appears to be crucial. However, little is known about its receptor, the IL-6R expression on human spermatozoa. Thus, the aim of the present study was to screen spermatozoa for IL-6R expression and to identify its localisation. Semen samples of 137 patients (median age 37.69, SD ± 7.82) with subfertility were analysed. Sperm analysis including determination of IL-6 was performed following the World Health Organization criteria. Also, flow cytometry was performed for sperm IL-6R expression. IL-6R+ cells were used for immunofluorescence staining to identify receptor localisation. The results showed positive staining for IL-6R in the midpiece of spermatozoa. Furthermore, a significant correlation between sperm IL-6R expression, seminal plasma IL-6 and total sperm count could be demonstrated, whereas a negative correlation was observed in sperm IL-6R expression and motility. However, no statistical significance could be observed between IL-6R expression, vitality and morphology. Moreover, incubation of spermatozoa with IL-6 led to a slight but significant decrease in motility after 24 hr. These data suggest that IL-6R expression may play a role in impaired sperm function during inflammation.