Predictors of All-Cause Mortality among Stroke Patients in Kazakhstan A Retrospective Study

Abstract

Aim: To examine all-cause mortality predictors among lab indicators and drugs administered to stroke patients in Kazakhstan. Materials and methods: This retrospective study analyzed data from 272 patient records derived from the UNEHS database (2014-2019). Stroke patients were identified using ICD codes; the GPT-4o model was trained to dissect the records and assist in the extraction of lab and medication data; other clinical and demographic data were derived from the previous study using RPN IDs. Statistical analyses included univariate, multivariate, and imputed multivariate logistic regressions (STATA version 16.1). Results: In our cohort, deceased patients were older (66.1 vs. 58.6, p < 0.0001). Adjusted logistic regression revealed age (OR 1.04), hemoglobin (OR 0.97), and piracetam (OR 3.17) as independent predictors. After multiple imputation, Russian ethnicity (OR 2.79), PTI (OR 0.97), and dopamine (OR 5.23) became independent predictors, while piracetam lost its significance. Conclusions: Findings suggest the importance of future research on stroke predictors in bigger cohorts to facilitate the introduction of innovations to stroke patients’ care to potentially decrease the burden on the Kazakhstani population.