Publications by authors named "T Wiesmann"

63 Publications

Results of the CAPSID randomized trial for high-dose convalescent plasma in severe COVID-19 patients.

J Clin Invest 2021 Aug 31. Epub 2021 Aug 31.

Institute for Clinical Transfusion Medicine and Immunogenetics Ulm, University of Ulm, Ulm, Germany.

Background: COVID-19 convalescent plasma (CCP) has been considered a treatment option in COVID-19. This trial assessed the efficacy of neutralizing antibody containing high-dose CCP in hospitalized adults with COVID-19 requiring respiratory support or intensive care treatment.

Methods: Patients (n=105) were randomized 1:1 to either receive standard treatment and 3 units of CCP or standard treatment alone. Control group patients with progress on day 14 could cross over to the CCP group. Primary outcome was a dichotomous composite outcome of survival and no longer fulfilling criteria for severe COVID-19 on day 21.

Results: The primary outcome occurred in 43.4% of patients in the CCP and 32.7% in the control group (p=0.32). The median time to clinical improvement was 26 days in the CCP group and 66 days in the control group (p=0.27). Median time to discharge from hospital was 31 days in the CCP and 51 days in the control group (p=0.24). In the subgroup that received a higher cumulative amount of neutralizing antibodies the primary outcome occurred in 56.0% (versus 32.1%), with significantly shorter intervals to clinical improvement (20 versus 66 days)(p<0.05), and to hospital discharge (21 versus 51 days, p=0.03) and better survival (day-60 probability of survival 91.6% versus 68.1%; p=0.02) compared to the control group.

Conclusion: CCP added to standard treatment was not associated with significant improvement in the primary and secondary outcomes. A pre-defined subgroup analysis showed a significant benefit for CCP among those who received a larger amount of neutralizing antibodies.

Trial Registration: ClinicalTrials.gov, NCT04433910FUNDING. German Federal Ministry of Health.
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http://dx.doi.org/10.1172/JCI152264DOI Listing
August 2021

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort.

Crit Care 2021 Aug 17;25(1):295. Epub 2021 Aug 17.

Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany.

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.
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http://dx.doi.org/10.1186/s13054-021-03720-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8370055PMC
August 2021

The janus-kinase inhibitor ruxolitinib in SARS-CoV-2 induced acute respiratory distress syndrome (ARDS).

Leukemia 2021 Aug 12. Epub 2021 Aug 12.

Klinik für Anästhesiologie und Intensivmedizin, Philipps Universität and UKGM, Marburg, Germany.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 (coronavirus disease 2019), which is associated with high morbidity and mortality, especially in elder patients. Acute respiratory distress syndrome (ARDS) is a life-threatening complication of COVID-19 and has been linked with severe hyperinflammation. Dexamethasone has emerged as standard of care for COVID-19 associated respiratory failure. In a non-randomized prospective phase II multi-center study, we asked whether targeted inhibition of Janus kinase-mediated cytokine signaling using ruxolitinib is feasible and efficacious in SARS-CoV-2- induced ARDS with hyperinflammation. Sixteen SARS-CoV-2 infected patients requiring invasive mechanical ventilation for ARDS were treated with ruxolitinib in addition to standard treatment. Ruxolitinib treatment was well tolerated and 13 patients survived at least the first 28 days on treatment, which was the primary endpoint of the trial. Immediate start of ruxolitinib after deterioration was associated with improved outcome, as was a lymphocyte-to-neutrophils ratio above 0.07. Together, treatment with the janus-kinase inhibitor ruxolitinib is feasible and might be efficacious in COVID-19 induced ARDS patients requiring invasive mechanical ventilation. The trial has been registered under EudraCT-No.: 2020-001732-10 and NCT04359290.
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http://dx.doi.org/10.1038/s41375-021-01374-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8358255PMC
August 2021

Repurposing CPAP machines as stripped-down ventilators.

Sci Rep 2021 06 9;11(1):12204. Epub 2021 Jun 9.

Faculty of Physics and Material Sciences Centre, Philipps-Universität Marburg, Marburg, Germany.

The worldwide shortage of medical-grade ventilators is a well-known issue, that has become one of the central topics during the COVID-19 pandemic. Given that these machines are expensive and have long lead times, one approach is to vacate them for patients in critical conditions while patients with mild to moderate symptoms are treated with stripped-down ventilators. We propose a mass-producible solution that can create such ventilators with minimum effort. The central part is a module that can be attached to CPAP machines and repurpose them as low-pressure ventilators. Here, we describe the concept and first measurements which underline the potential of our solution. Our approach may serve as a starting point for open-access ventilator technologies.
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http://dx.doi.org/10.1038/s41598-021-91673-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190155PMC
June 2021
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