Identify mortality predictors in Hispanic patients with anterior circulation ischemic stroke (ACIS) who present outside the thrombolytic window.

Stroke is a leading cause of death worldwide, and timely access to thrombolytic therapy can significantly improve outcomes. However, in underserved communities, delays in diagnosis often prevent patients from receiving this treatment, making it critical to identify factors that impact mortality in those who arrive outside the thrombolytic window. Understanding these predictors is essential for improving stroke care in resource-limited settings.

A retrospective study was conducted among Hispanic patients with ACIS, confirmed by imaging, at a stroke care hospital in Ecuador. Data were obtained from medical records. Logistic regression analysis and 10,000 bootstrap samples were used to assess associations between mortality and clinical variables, including age, sex, comorbidities, neurological deficits, Intensive care unit (ICU) admission, and mechanical ventilation. Model accuracy and Nagelkerke R² were evaluated.

The study included 169 patients (mean age: 72 ± 13 years; 60.9% male). Mortality was 24.3% (41). Significant mortality predictors included loss of consciousness (OR 6.486, 95% CI 2.043–20.585, p=0.002), mechanical ventilation (OR 13.878, 95% CI 2.347–82.081, p=0.004), ICU admission (OR 36.918, 95% CI 3.781–360.487, p=0.002), and seizure occurrence (OR 0.041, 95% CI 0.003–0.523, p=0.014). Length of hospitalization was inversely associated with mortality (OR 0.926, 95% CI 0.883–0.971, p=0.001), while age was a modest predictor (OR 1.046, 95% CI 1.003–1.091, p=0.037). The model demonstrated an overall accuracy of 82.8% and a Nagelkerke R² of 0.499.

ICU admission, mechanical ventilation, loss of consciousness, and seizures are critical mortality predictors in Hispanic patients with ACIS. The model’s robust predictive accuracy and validated stability through bootstrapping highlight its potential for guiding clinical decision-making and improving patient outcomes in similar resource-limited settings, ultimately aiding in reducing stroke-related mortality in underserved populations.