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Introduction: Recommendations for venous thromboembolism and deep venous thrombosis (DVT) prophylaxis using graduated compression stockings (GCS) is historically based and has been critically examined in current publications. Existing guidelines are inconclusive as to recommend the general use of GCS.
Patients/Methods: 24 273 in-patients (general surgery and orthopedic patients) undergoing surgery between 2006 and 2016 were included in a retrospectively analysis from a single center. From January 2006 to January 2011 perioperative GCS was employed additionally to drug prophylaxis and from February 2011 to March 2016 patients received drug prophylaxis alone. According to german guidelines all patients received venous thromboembolism prophylaxis with weight-adapted LMWH. Risk stratification (low risk, moderate risk, high risk) was based on the guideline of the American College of Chest Physicians. Data analysis was performed before and after propensity matching (PM). The defined primary endpoint was the incidence of symptomatic or fatal pulmonary embolism (PE). A secondary endpoint was the incidence of deep venous thromboembolism (DVT).
Results: After risk stratification (low risk n = 16 483; moderate risk n = 4464; high risk n = 3326) a total of 24 273 patient were analyzed. Before to PM the relative risk for the occurrence of a PE or DVT was not increased by abstaining from GCS. After PM two groups of 11 312 patients each, one with and one without GCS application, were formed. When comparing the two groups, the relative risk (RR) for the occurrence of a pulmonary embolism was: Low Risk 0.99 [CI95% 0.998–1.000]; Moderate Risk 0.999 [CI95% 0.95–1.003]; High Risk 0.996 [CI95% 0.992–1.000] (p > 0.05). The incidence of PE in the total group LMWH alone was 0.1% (n = 16). In the total group using LMWH + GCS, the incidence was 0.3% (n = 29). RR after PM was 0.999 [CI95% 0.998–1.00].
Conclusion: In comparison to prior studies with only small numbers of patients our trial shows in a large group of patients with moderate and high risk developing VTE we can support the view that abstaining from GCS-use does not increase the incidence of symptomatic or fatal PE and symptomatic DVT.
Background: Epileptic seizures are common clinical features in patients with acute subdural hematoma (aSDH); however, diagnostic feasibility and therapeutic monitoring remain limited. Surface electroencephalography (EEG) is the major diagnostic tool for the detection of seizures but it might be not sensitive enough to detect all subclinical or nonconvulsive seizures or status epilepticus. Therefore, we have planned a clinical trial to evaluate a novel treatment modality by perioperatively implanting subdural EEG electrodes to diagnose seizures; we will then treat the seizures under therapeutic monitoring and analyze the clinical benefit.
Methods: In a prospective nonrandomized trial, we aim to include 110 patients with aSDH. Only patients undergoing surgical removal of aSDH will be included; one arm will be treated according to the guidelines of the Brain Trauma Foundation, while the other arm will additionally receive a subdural grid electrode. The study's primary outcome is the comparison of incidence of seizures and time-to-seizure between the interventional and control arms. Invasive therapeutic monitoring will guide treatment with antiseizure drugs (ASDs). The secondary outcome will be the functional outcome for both groups as assessed via the Glasgow Outcome Scale and modified Rankin Scale both at discharge and during 6 months of follow-up. The tertiary outcome will be the evaluation of chronic epilepsy within 2-4 years of follow-up.
Discussion: The implantation of a subdural EEG grid electrode in patients with aSDH is expected to be effective in diagnosing seizures in a timely manner, facilitating treatment with ASDs and monitoring of treatment success. Moreover, the occurrence of epileptiform discharges prior to the manifestation of seizure patterns could be evaluated in order to identify high-risk patients who might benefit from prophylactic treatment with ASDs.
Trial registration: ClinicalTrials.gov identifier no. NCT04211233.
Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.
Background: The development of robotic systems has provided an alternative to frame-based stereotactic procedures. The aim of this experimental phantom study was to compare the mechanical accuracy of the Robotic Surgery Assistant (ROSA) and the Leksell stereotactic frame by reducing clinical and procedural factors to a minimum.
Methods: To precisely compare mechanical accuracy, a stereotactic system was chosen as reference for both methods. A thin layer CT scan with an acrylic phantom fixed to the frame and a localizer enabling the software to recognize the coordinate system was performed. For each of the five phantom targets, two different trajectories were planned, resulting in 10 trajectories. A series of five repetitions was performed, each time based on a new CT scan. Hence, 50 trajectories were analyzed for each method. X-rays of the final cannula position were fused with the planning data. The coordinates of the target point and the endpoint of the robot- or frame-guided probe were visually determined using the robotic software. The target point error (TPE) was calculated applying the Euclidian distance. The depth deviation along the trajectory and the lateral deviation were separately calculated.
Results: Robotics was significantly more accurate, with an arithmetic TPE mean of 0.53 mm (95% CI 0.41–0.55 mm) compared to 0.72 mm (95% CI 0.63–0.8 mm) in stereotaxy (p < 0.05). In robotics, the mean depth deviation along the trajectory was −0.22 mm (95% CI −0.25 to −0.14 mm). The mean lateral deviation was 0.43 mm (95% CI 0.32–0.49 mm). In frame-based stereotaxy, the mean depth deviation amounted to −0.20 mm (95% CI −0.26 to −0.14 mm), the mean lateral deviation to 0.65 mm (95% CI 0.55–0.74 mm).
Conclusion: Both the robotic and frame-based approach proved accurate. The robotic procedure showed significantly higher accuracy. For both methods, procedural factors occurring during surgery might have a more relevant impact on overall accuracy.
Background: IL28B gene polymorphism is the best baseline predictor of response to interferon alfa-based antiviral therapies in chronic hepatitis C. Recently, a new IFN-L4 polymorphism was identified as first potential functional variant for induction of IL28B expression. Individualization of interferon alfa-based therapies based on a combination of IL28B/IFN-L4 polymorphisms may help to optimize virologic outcome and economic resources.
Methods: Optimization of treatment outcome prediction was assessed by combination of different IL28B and IFN-L4 polymorphisms in patients with chronic HCV genotype 1 (n = 385), 2/3 (n = 267), and 4 (n = 220) infection treated with pegylated interferon alfa (PEG-IFN) and ribavirin with (n = 79) or without telaprevir. Healthy people from Germany (n = 283) and Egypt (n = 96) served as controls.
Results: Frequencies of beneficial IL28B rs12979860 C/C genotypes were lower in HCV genotype 1/4 infected patients in comparison to controls (20–35% vs. 46–47%) this was also true for ss469415590 TT/TT (20–35% vs. 45–47%). Single interferon-lambda SNPs (rs12979860, rs8099917, ss469415590) correlated with sustained virologic response (SVR) in genotype 1, 3, and 4 infected patients while no association was observed for genotype 2. Interestingly, in genotype 3 infected patients, best SVR prediction was based on IFN-L4 genotype. Prediction of SVR with high accuracy (71–96%) was possible in genotype 1, 2, 3 and 4 infected patients who received PEG-IFN/ribavirin combination therapy by selection of beneficial IL28B rs12979860 C/C and/or ss469415590 TT/TT genotypes (p<0.001). For triple therapy with first generation protease inhibitors (PIs) (boceprevir, telaprevir) prediction of high SVR (90%) rates was based on the presence of at least one beneficial genotype of the 3 IFN-lambda SNPs.
Conclusion: IFN-L4 seems to be the best single predictor of SVR in genotype 3 infected patients. For optimized prediction of SVR by treatment with dual combination or first generation PI triple therapies, grouping of interferon-lambda haplotypes may be helpful with positive predictive values of 71–96%.
After myocardial infarction in the adult heart the remaining, non-infarcted tissue adapts to compensate the loss of functional tissue. This adaptation requires changes in gene expression networks, which are mostly controlled by transcription regulating proteins. Long non-coding transcripts (lncRNAs) are now recognized for taking part in fine-tuning such gene programs. We identified and characterized the cardiomyocyte specific lncRNA Sweetheart RNA (Swhtr), an approximately 10 kb long transcript divergently expressed from the cardiac core transcription factor coding gene Nkx2-5. We show that Swhtr is dispensable for normal heart development and function, but becomes essential for the tissue adaptation process after myocardial infarction. Re-expressing Swhtr from an exogenous locus rescues the Swhtr null phenotype. Genes depending on Swhtr after cardiac stress are significantly occupied, and therefore most likely regulated by NKX2-5. Our results indicate a synergistic role for Swhtr and the developmentally essential transcription factor NKX2-5 in tissue adaptation after myocardial injury.
Triple therapy of chronic hepatitis C virus (HCV) infection with boceprevir (BOC) or telaprevir (TVR) leads to virologic failure in many patients which is often associated with the selection of resistance-associated variants (RAVs). These resistance profiles are of importance for the selection of potential rescue treatment options. In this study, we sequenced baseline NS3 RAVs population-based and investigated the sensitivity of NS3 phenotypes in an HCV replicon assay together with clinical factors for a prediction of treatment response in a cohort of 165 German and Swiss patients treated with a BOC or TVR-based triple therapy. Overall, the prevalence of baseline RAVs was low, although the frequency of RAVs was higher in patients with virologic failure compared to those who achieved a sustained virologic response (SVR) (7% versus 1%, P = 0.06). The occurrence of RAVs was associated with a resistant NS3 quasispecies phenotype (P<0.001), but the sensitivity of phenotypes was not associated with treatment outcome (P = 0.2). The majority of single viral and host predictors of SVR was only weakly associated with treatment response. In multivariate analyses, low AST levels, female sex and an IFNL4 CC genotype were independently associated with SVR. However, a combined analysis of negative predictors revealed a significantly lower overall number of negative predictors in patients with SVR in comparison to individuals with virologic failure (P<0.0001) and the presence of 2 or less negative predictors was indicative for SVR. These results demonstrate that most single baseline viral and host parameters have a weak influence on the response to triple therapy, whereas the overall number of negative predictors has a high predictive value for SVR.
After myocardial infarction in the adult heart the remaining, non-infarcted tissue adapts to compensate the loss of functional tissue. This adaptation requires changes in gene expression networks, which are mostly controlled by transcription regulating proteins. Long non-coding transcripts (lncRNAs) are taking part in fine-tuning such gene programs. We describe and characterize the cardiomyocyte specific lncRNA Sweetheart RNA (Swhtr), an approximately 10 kb long transcript divergently expressed from the cardiac core transcription factor coding gene Nkx2-5. We show that Swhtr is dispensable for normal heart development and function but becomes essential for the tissue adaptation process after myocardial infarction in murine males. Re-expressing Swhtr from an exogenous locus rescues the Swhtr null phenotype. Genes that depend on Swhtr after cardiac stress are significantly occupied and therefore most likely regulated by NKX2-5. The Swhtr transcript interacts with NKX2-5 and disperses upon hypoxic stress in cardiomyocytes, indicating an auxiliary role of Swhtr for NKX2-5 function in tissue adaptation after myocardial injury.