Associations of anemia and blood transfusions with mortality in old, critically ill COVID-19 patients - Results from the prospective COVIP Study.

AIMS: Anemia is common in the old and often observed in critically ill patients. Increased age is associated with higher mortality following a COVID-19 infection, making old patients prone to poor outcomes. We investigated whether anemia at admission to the ICU or the need for blood transfusion was associated with 90-day mortality in older, critically ill COVID-19 patients. METHODS: In this prospective multicenter study, the 90-day mortality of COVID-19 patients≥70 years treated in 138 intensive care units (ICU) was analyzed. Associations between anemia (WHO definition) at admission and discharge from ICU and the use of red blood cell (RBC) transfusions with mortality were assessed. Hemoglobin thresholds of RBC transfusions in old, critically ill COVID-19 patients were recorded. RESULTS: In 493 patients (350 anemic, 143 non-anemic), anemia (WHO definition) at the time of ICU admission was not associated with impaired overall survival. Transfusion and severe anemia (hemoglobin≤10 g/dL) at ICU discharge were independently associated with a higher risk of 90-day mortality. CONCLUSION: The need for red blood cell transfusions and severe anemia at ICU discharge, but not at the timepoint of admission, were independently associated with 90-day mortality in critically-ill old COVID-19 patients.

Mobilisation practices during the SARS-CoV-2 pandemic: A retrospective analysis (MobiCOVID).

BACKGROUND: Corona Virus Disease 2019 (COVID-19) patients display risk factors for intensive care unit acquired weakness (ICUAW). The pandemic increased existing barriers to mobilisation. This study aimed to compare mobilisation practices in COVID-19 and non-COVID-19 patients. METHODS: This retrospective cohort study was conducted at Charité-Universitätsmedizin Berlin, Germany, including adult patients admitted to one of 16 ICUs between March 2018, and November 2021. The effect of COVID-19 on mobilisation level and frequency, early mobilisation (EM) and time to active sitting position (ASP) was analysed. Subgroup analysis on COVID-19 patients and the ICU type influencing mobilisation practices was performed. Mobilisation entries were converted into the ICU mobility scale (IMS) using supervised machine learning. The groups were matched using 1:1 propensity score matching. RESULTS: A total of 12,462 patients were included, receiving 59,415 mobilisations. After matching 611 COVID-19 and non-COVID-19 patients were analysed. They displayed no significant difference in mobilisation frequency (0.4 vs. 0.3, p = 0.7), maximum IMS (3 vs. 3; p = 0.17), EM (43.2% vs. 37.8%; p = 0.06) or time to ASP (HR 0.95; 95% CI: 0.82, 1.09; p = 0.44). Subgroup analysis showed that patients in surge ICUs, i.e., temporarily created ICUs for COVID-19 patients during the pandemic, more commonly received EM (53.9% vs. 39.8%; p = 0.03) and reached higher maximum IMS (4 vs. 3; p = 0.03) without difference in mobilisation frequency (0.5 vs. 0.3; p = 0.32) or time to ASP (HR 1.15; 95% CI: 0.85, 1.56; p = 0.36). CONCLUSION: COVID-19 did not hinder mobilisation. Those treated in surge ICUs were more likely to receive EM and reached higher mobilisation levels.

Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave: the global UNITE-COVID study.

PURPOSE: To accommodate the unprecedented number of critically ill patients with pneumonia caused by coronavirus disease 2019 (COVID-19) expansion of the capacity of intensive care unit (ICU) to clinical areas not previously used for critical care was necessary. We describe the global burden of COVID-19 admissions and the clinical and organizational characteristics associated with outcomes in critically ill COVID-19 patients. METHODS: Multicenter, international, point prevalence study, including adult patients with SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) and a diagnosis of COVID-19 admitted to ICU between February 15th and May 15th, 2020. RESULTS: 4994 patients from 280 ICUs in 46 countries were included. Included ICUs increased their total capacity from 4931 to 7630 beds, deploying personnel from other areas. Overall, 1986 (39.8%) patients were admitted to surge capacity beds. Invasive ventilation at admission was present in 2325 (46.5%) patients and was required during ICU stay in 85.8% of patients. 60-day mortality was 33.9% (IQR across units: 20%-50%) and ICU mortality 32.7%. Older age, invasive mechanical ventilation, and acute kidney injury (AKI) were associated with increased mortality. These associations were also confirmed specifically in mechanically ventilated patients. Admission to surge capacity beds was not associated with mortality, even after controlling for other factors. CONCLUSIONS: ICUs responded to the increase in COVID-19 patients by increasing bed availability and staff, admitting up to 40% of patients in surge capacity beds. Although mortality in this population was high, admission to a surge capacity bed was not associated with increased mortality. Older age, invasive mechanical ventilation, and AKI were identified as the strongest predictors of mortality.

Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia.

In a pandemic with a novel disease, disease-specific prognosis models are available only with a delay. To bridge the critical early phase, models built for similar diseases might be applied. To test the accuracy of such a knowledge transfer, we investigated how precise lethal courses in critically ill COVID-19 patients can be predicted by a model trained on critically ill non-COVID-19 viral pneumonia patients. We trained gradient boosted decision tree models on 718 (245 deceased) non-COVID-19 viral pneumonia patients to predict individual ICU mortality and applied it to 1054 (369 deceased) COVID-19 patients. Our model showed a significantly better predictive performance (AUROC 0.86 [95% CI 0.86-0.87]) than the clinical scores APACHE2 (0.63 [95% CI 0.61-0.65]), SAPS2 (0.72 [95% CI 0.71-0.74]) and SOFA (0.76 [95% CI 0.75-0.77]), the COVID-19-specific mortality prediction models of Zhou (0.76 [95% CI 0.73-0.78]) and Wang (laboratory: 0.62 [95% CI 0.59-0.65]; clinical: 0.56 [95% CI 0.55-0.58]) and the 4C COVID-19 Mortality score (0.71 [95% CI 0.70-0.72]). We conclude that lethal courses in critically ill COVID-19 patients can be predicted by a machine learning model trained on non-COVID-19 patients. Our results suggest that in a pandemic with a novel disease, prognosis models built for similar diseases can be applied, even when the diseases differ in time courses and in rates of critical and lethal courses.

Symptoms of burnout in intensive care unit specialists facing the COVID-19 outbreak.

BACKGROUND: The COVID-19 pandemic has resulted in an unprecedented healthcare crisis with a high prevalence of psychological distress in healthcare providers. We sought to document the prevalence of burnout syndrome amongst intensivists facing the COVID-19 outbreak. METHODS: Cross-sectional survey among intensivists part of the European Society of Intensive Care Medicine. Symptoms of severe burnout, anxiety and depression were collected. Factors independently associated with severe burnout were assessed using Cox model. RESULTS: Response rate was 20% (1001 completed questionnaires were returned, 45 years [39-53], 34% women, from 85 countries, 12 regions, 50% university-affiliated hospitals). The prevalence of symptoms of anxiety and depression or severe burnout was 46.5%, 30.2%, and 51%, respectively, and varied significantly across regions. Rating of the relationship between intensivists and other ICU stakeholders differed significantly according to the presence of anxiety, depression, or burnout. Similar figures were reported for their rating of the ethical climate or the quality of the decision-making. Factors independently associated with anxiety were female gender (HR 1.85 [1.33-2.55]), working in a university-affiliated hospital (HR 0.58 [0.42-0.80]), living in a city of > 1 million inhabitants (HR 1.40 [1.01-1.94]), and clinician's rating of the ethical climate (HR 0.83 [0.77-0.90]). Independent determinants of depression included female gender (HR 1.63 [1.15-2.31]) and clinician's rating of the ethical climate (HR 0.84 [0.78-0.92]). Factors independently associated with symptoms of severe burnout included age (HR 0.98/year [0.97-0.99]) and clinician's rating of the ethical climate (HR 0.76 [0.69-0.82]). CONCLUSIONS: The COVID-19 pandemic has had an overwhelming psychological impact on intensivists. Follow-up, and management are warranted to assess long-term psychological outcomes and alleviate the psychological burden of the pandemic on frontline personnel.

International variation in the management of severe COVID-19 patients.

BACKGROUND: There is little evidence to support the management of severe COVID-19 patients. METHODS: To document this variation in practices, we performed an online survey (April 30-May 25, 2020) on behalf of the European Society of Intensive Care Medicine (ESICM). A case vignette was sent to ESICM members. Questions investigated practices for a previously healthy 39-year-old patient presenting with severe hypoxemia from COVID-19 infection. RESULTS: A total of 1132 ICU specialists (response rate 20%) from 85 countries (12 regions) responded to the survey. The survey provides information on the heterogeneity in patient's management, more particularly regarding the timing of ICU admission, the first line oxygenation strategy, optimization of management, and ventilatory settings in case of refractory hypoxemia. Practices related to antibacterial, antiviral, and anti-inflammatory therapies are also investigated. CONCLUSIONS: There are important practice variations in the management of severe COVID-19 patients, including differences at regional and individual levels. Large outcome studies based on multinational registries are warranted.