Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain

Background The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. Methods Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 ICUs in Spain. The objective was to utilize an unsupervised clustering analysis to derive clinical COVID-19 phenotypes and to analyze patient’s factors associated with mortality risk. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. Results The database included a total of 2022 patients (mean age 64 [IQR 5–71] years, 1423 (70.4%) male, median APACHE II score (13 [IQR 10–17]) and SOFA score (5 [IQR 3–7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the A (mild) phenotype (537; 26.7%) included older age ( 65 years), high severity of illness and a higher likelihood of development shock. Crude ICU mortality was 20.3%, 25% and 45.4% for A, B and C phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications. Conclusion The presented machine learning model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a “one-size-fits-all” model in practice

The INTOXICATE study: methodology and preliminary results of a prospective observational study

Background There is currently no practice-based, multicenter database of poisoned patients admitted to intensive care units (ICUs). The INTOXICATE study, endorsed by the ESICM and EAPCCT, aimed to determine the rate of eventful admissions among acutely intoxicated adult ICU patients. Methods Ethical approval was obtained for this multicenter, prospective observational study, and data-sharing agreements were signed with each participating center. An electronic case report form was used to collect data on patient demographics, exposure, clinical characteristics, investigations, treatment, and in-hospital mortality data. The primary outcome, ‘eventful admission’, was a composite outcome defined as the rate of patients who received any of the following treatments in the first 24 h after the ICU admission: oxygen supplementation with a FiO2 > 40%, mechanical ventilation, vasopressors, renal replacement therapy (RRT), cardiopulmonary resuscitation, antidotes, active cooling, fluid resuscitation (> 1.5 L of intravenous fluid of any kind), sedation, or who died in the hospital. Results Seventy-eight ICUs, mainly from Europe, but also from Australia and the Eastern Mediterranean, participated. A total of 2,273 patients were enrolled between November 2020 and June 2023. The median age of the patients was 41 years, 72% were exposed to intoxicating drugs. The observed rate of patients with an eventful ICU admission was 68% (n = 1546/2273 patients). The hospital mortality was 4.5% (n = 103/2273). Conclusions The vast majority of patients survive, and approximately one third of patients do not receive any ICU-specific interventions after admission in an intensive care unit for acute intoxication. High-quality detailed clinical data have been collected from a large cohort of acutely intoxicated ICU patients, providing information on the pattern of severe acute poisoning requiring intensive care admission and the outcomes of these patients. Trial registration: OSF registration ID: osf.io/7e5uy