Baseline Severity and Early Multiorgan Failure to Predict In-Hospital Mortality in Critically Ill COVID-19 Patients: A Retrospective Cohort Study
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Background Intensive Care Unit (ICU) mortality remains high among patients with severe coro-navirus disease. Static admission severity scores may fail to capture the dynamic clinical trajectory of critically ill patients. We hypothesized that early multiorgan failure (MOF) at 24 hours would improve mortality discrimination beyond static admission severity alone. Methods Retrospective, single-center cohort study of 345 adults with severe COVID-19 pneumonia admitted to a Spanish ICU (March 2020–December 2022). The primary outcome was all-cause in-hospital mortality. Univariate comparisons between survivors and non-survivors were performed, followed by multivariable logistic regression to identify independent predictors of mortality. Three sequential models were constructed and compared by Area Under the Receiver Operating Characteristic Curve (AUC-ROC) discrimination. Results Overall, in-hospital mortality was 20.6%. Non-survivors were older and had higher Simplified Acute Physiology Score (SAPS) II and Acute Physiology and Chronic Health Evaluation (APACHE) II scores (p<0.001). MOF at 24 hours was more frequent among non-survivors than survivors (88.4% vs. 61.7%, p<0.001). The baseline model (age, sex, Chronic Obstructive Pul-monary Disease (COPD), hypertension, and SAPS II) achieved an AUC of 0.798 (95% CI 0.742– 0.852). The final model incorporating MOF at 24 hours achieved an AUC of 0.812 (95% CI 0.754– 0.860); early MOF nearly tripled the odds of death (OR 2.78, 95% CI 1.22–6.33, p=0.015). Conclusions Combining baseline severity with early multiorgan dysfunction provides a simple, interpretable approach to mortality risk stratification in critically ill COVID-19 patients; however, external validation is needed before it can inform escalation-of-care or treatment-limitation decisions in clinical practice.
Source: medRxiv
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7225329658