Polypharmacy and Proton Pump Inhibitor Use Independently Predict One-Year Mortality in Critical COVID-19: An Explainable AI-Based Survival Analysis

Mortality among patients admitted to intensive care with coronavirus disease 2019 (COVID-19) remains substantial despite advances in management. The contribution of pre-admission medication profiles to long-term survival is poorly defined. We analysed 497 adults with confirmed COVID-19 admitted to six intensive care units in southern Sweden between May 2020 and May 2021. Clinical and laboratory data were combined with prescription information from the national drug registry; drugs dispensed at least twice within eight months before admission were classified by Anatomical Therapeutic Chemical code. Polypharmacy was defined as the use of five or more medications. An XGBoost survival model with a Cox partial-likelihood objective was trained to predict one-year mortality and interpreted using SHapley Additive exPlanations (SHAP). The model achieved a concordance index of 0.74. Age was the strongest predictor of mortality, followed by the number of medications per patient, which ranked above the Charlson Comorbidity Index and Clinical Frailty Scale. Proton pump inhibitors were the only individual drug class among the top predictors, showing a modest positive association with mortality, whereas angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers had negligible contributions. These findings identify cumulative medication burden as an independent and clinically relevant marker of vulnerability in critical COVID-19.