Dynamic prediction of mortality in COVID-19 patients in the intensive care unit: A retrospective multi-center cohort study.

Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85; 0.88] and 0.86 [0.84; 0.88], respectively. The recalibrated model predictions showed a calibration intercept of -0.04 [-0.12; 0.04] and slope of 0.90 [0.85; 0.95] for logistic regression model and a calibration intercept of -0.19 [-0.27; -0.10] and slope of 0.89 [0.84; 0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research.

The first 100 COVID-19 patients admitted to the Elisabeth-Tweesteden hospital, Tilburg, the Netherlands

Here we describe the characteristics of the first 100 laboratory confirmed COVID-19 patients admitted to the Elisabeth-Tweesteden Hospital (Tilburg, The Netherlands). The median age was 72 years, 67% was male, approximately 80% had co-morbidity, approximately 50% of which consisted of hypertension, cardiac and or pulmonary conditions and 25% diabetes. At admission 61% of patients had fever and about 50% presented at day 6 or more after onset of symptoms. At the time of writing 38 patients were discharged, 19 admitted to the intensive care unit (ICU) and 20 patients had died. The median age of ICU patients was 67 years and 63% had co-morbidity. The median time to discharge or to death was 6 and 5.5 days, respectively.