Abstract The C-Reactive Protein-to-Albumin Ratio (CAR) demonstrates associations with cerebrovascular disease outcomes. However, its prognostic value in critically ill ischemic stroke (IS) patients intensive care unit (ICU) admission remains unclear. This study aimed to investigate the association between CAR and clinical prognosis in critically ill IS patients.In this retrospective cohort study, clinical data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database (serving as the training set) and externally validated using the eICU Collaborative Research Database (eICU-CRD). The primary outcomes were 28-day, 60-day, and 90-day all-cause mortality. The association between CAR and mortality was evaluated using multivariable logistic regression and restricted cubic splines (RCS). Machine learning algorithms were employed to develop prediction models incorporating CAR. Model performance was assessed using the Boruta algorithm for feature importance and the Integrated Discrimination Improvement (IDI).A total of 2,664 critically ill IS patients were analyzed (mean CAR: 22.173 ± 26.011). After adjusting for confounders, multivariable logistic regression confirmed CAR as an independent predictor of mortality: the adjusted odds ratios (95% confidence intervals) were 1.006 (1.003–1.010, P = 0.033) for 28-day, 1.005 (1.001–1.008, P = 0.005) for 60-day, and 1.004 (1.001–1.007, P = 0.016) for 90-day mortality. RCS analysis indicated a monotonically increasing association between CAR and mortality risk. Machine learning models incorporating CAR demonstrated superior fit and higher area under the curve (AUC) values compared to models without it. In conclusions,In critically ill patients with ischemic stroke, a higher CAR is significantly associated with increased short- and medium-term all-cause mortality risk.
Binyang et al. (Fri,) studied this question.
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