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1.
Z Herz Thorax Gefasschir ; : 1-5, 2022 Apr 26.
Article in German | MEDLINE | ID: covidwho-1826452

ABSTRACT

Background: The novel coronavirus disease 2019 (COVID-19) can cause a severe and therapy-refractory acute respiratory distress syndrome. Temporary mechanical assistance by veno-venous extracorporeal membrane oxygenation (v.v.-EMCO) is a well-established supportive therapy, but is still associated with a high mortality. Objective: This work aimed to identify potential effects of the ECMO cannulation strategy on the outcome in COVID-19 patients. Material and methods: All patients who were treated in a single center between March 2020 and November 2021 for COVID-19-related ARDS (n = 75) were prospectively entered into an institutional database. The patients were assigned into two groups with respect to the ECMO cannulation (femorofemoral: n = 20, femorojugular: n = 55) and the outcome was retrospectively analyzed. Results: We observed severe therapy-related adverse events in both groups in more than 70% of patients with sepsis being the most common (> 50% each). The outcome (successful ECMO weaning, in-hospital death, 6­month survival) was comparable in both groups. In-hospital mortality was about 70% each; however, the duration of event-free ECMO support seemed to be prolonged in the femorojugular group. Conclusion: Regardless of the support duration, v.v.-ECMO therapy for COVID-19 is associated with high mortality rates. The cannulation strategy did not impact on the outcome; however, femorojugular cannulation might prolong the event-free support duration and facilitate the mobilization of the patients during ECMO support.

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-316141

ABSTRACT

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: . 1,039 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

4.
Crit Care ; 25(1): 295, 2021 Aug 17.
Article in English | MEDLINE | ID: covidwho-1362062

ABSTRACT

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.


Subject(s)
COVID-19/epidemiology , Critical Illness/epidemiology , Electronic Health Records/statistics & numerical data , Intensive Care Units , Machine Learning , Adult , Aged , COVID-19/therapy , Cohort Studies , Critical Illness/therapy , Emergency Service, Hospital , Female , Germany , Humans , Male , Middle Aged , Outcome Assessment, Health Care
5.
Lancet Reg Health Eur ; 8: 100164, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1309324

ABSTRACT

BACKGROUND: Monoclonal antibodies (mAb) have been introduced as a promising new therapeutic approach against SARS-CoV-2. At present, there is little experience regarding their clinical effects in patient populations underrepresented in clinical trials, e.g. immunocompromised patients. Additionally, it is not well known to what extent SARS-CoV-2 treatment with monoclonal antibodies could trigger the selection of immune escape viral variants. METHODS: After identifying immunocompromised patients with viral rebound under treatment with bamlanivimab, we characterized the SARS-CoV-2-isolates by whole genome sequencing. Viral load measurements and sequence analysis were performed consecutively before and after bamlanivimab administration. FINDINGS: After initial decrease of viral load, viral clearance was not achieved in five of six immunocompromised patients treated with bamlanivimab. Instead, viral replication increased again over the course of the following one to two weeks. In these five patients, the E484K substitution - known to confer immune escape - was detected at the time of viral rebound but not before bamlanivimab treatment. INTERPRETATION: Treatment of SARS-CoV-2 with bamlanivimab in immunocompromised patients results in the rapid development of immune escape variants in a significant proportion of cases. Given that the E484K mutation can hamper natural immunity, the effectiveness of vaccination as well as antibody-based therapies, these findings may have important implications not only for individual treatment decisions but may also pose a risk to general prevention and treatment strategies. FUNDING: All authors are employed and all expenses covered by governmental, federal state, or other publicly funded institutions.

6.
Clin Case Rep ; 9(5): e04068, 2021 May.
Article in English | MEDLINE | ID: covidwho-1242709

ABSTRACT

This case of secondary sclerosing cholangitis (SSC-CIP) emphasizes the need to provide follow-up care for patients that have recovered from COVID-19 in order to understand the complexity of SARS-CoV-2 associated sequela.

7.
PLoS One ; 16(4): e0248813, 2021.
Article in English | MEDLINE | ID: covidwho-1172873

ABSTRACT

Healthcare personnel are at risk to aquire the corona virus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated the prevalence of SARS-CoV-2 antibodies and positive nasopharyngeal reverse transcriptase polymerase-chain reaction (RT-PCR) tests in German intensive care and emergency physicians. Physicians attending intensive care and emergency medicine training courses between June 16th and July 2nd 2020 answered a questionnaire and were screened for SARS-CoV-2 antibodies via automated electrochemiluminiscence immunoassay. We recruited 516 physicans from all parts of Germany, 445/516 (86%) worked in high risk areas, and 379/516 (73%) had treated patients with COVID-19. The overall positive rate was 18/516 (3.5%), 16/18 (89%) had antibodies against SARS-COV-2, another 2 reported previous positive RT-PCR results although antibody testing was negative. Of those positive, 7/18 (39%) were unaware of their infection. A stay abroad was stated by 173/498 (35%), mostly in Europe. 87/516 (17%) reported a febrile respiratory infection after January 1st 2020 which was related to SARS-CoV-2 in 4/87 (4.6%). Contact to COVID-19 positive relatives at home was stated by 22/502 (4.4%). This was the only significant risk factor for Covid-19 infection (Fisher´s exact test, p = 0.0005). N95 masks and eye protection devices were available for 87% and 73%, respectively. A total of 254/502 (51%) had been vaccinated against seasonal influenza. The overall SARS-CoV-2 infection rate of german physicians from intensive care and emergency medicine was low compared to reports from other countries and settings. This finding may be explained by the fact that the German health care system was not overwhelmed by the first wave of the SARS-CoV-2 pandemic.


Subject(s)
Antibodies, Viral/blood , COVID-19 Serological Testing , COVID-19 , Critical Care , Physicians , SARS-CoV-2/metabolism , Adult , Aged , COVID-19/blood , COVID-19/diagnosis , COVID-19/epidemiology , Female , Germany/epidemiology , Humans , Male , Middle Aged , Prevalence , Seroepidemiologic Studies
8.
Front Neurol ; 11: 574004, 2020.
Article in English | MEDLINE | ID: covidwho-940194

ABSTRACT

Objective: The affection of both the peripheral (PNS) and central nervous system (CNS) by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been assumed to play a direct role in the respiratory failure of patients with Corona virus disease 2019 (COVID-19) through affection of medullary cardiorespiratory centers resulting in neurological complications and sequelae. Methods: We used a multimodal electrophysiological approach combined with neuropsychological investigations to study functional alteration of both the PNS and CNS in four patients with severe COVID-19. Results: We found electrophysiological evidence for affection of both the PNS and CNS, and particularly affection of brain stem function. Furthermore, our neuropsychological investigations provide evidence of marked impairment of cognition independent of delirium, and outlasting the duration of acute infection with SARS-CoV-2. Conclusion: This case series provides first direct electrophysiological evidence for functional brain stem involvement in COVID-19 patients without evident morphological changes supporting the notion of the brain stem contributing to respiratory failure and thus promoting severe courses of the disease. Moreover, sustained neuropsychological sequelae in these patients may be of particular psychosocial and possibly also economic relevance for society.

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