Objective:

This study uses propensity score matching (PSM) to reduce selection and confounding bias and aims to accurately identify predictors of stroke recurrence and 1-year survival.

Background:

Stroke recurrence poses a significant challenge to the management of long-term outcomes in stroke survivors. Traditional studies are often limited by residual bias and a narrow focus on isolated risk factors, potentially obscuring the complex interplay between clinical outcomes and patient characteristics.

Design/Methods:

We retrospectively analyzed 39,947 ischemic stroke patients from the Regional Center Stroke Registry in Korea. Using PSM, patients were stratified into categories (>5, >16, >21) according to their discharge NIHSS score to ensure balanced comparisons. Logistic regression was used to assess the effect of NIHSS scores and other covariates on the probability of one-year recurrence, while Kaplan-Meier estimates were used to assess survival probabilities.

Results:

The incidence of early ischemic stroke recurrence was 3.83% (n=1,531). Higher discharge NIHSS scores significantly correlated with increased risk of recurrence within one year. Specifically, patients with scores above 16 and especially above 21 had the highest risk. Kaplan-Meier analysis showed a significant decrease in survival with higher NIHSS thresholds, underscoring their prognostic importance.

Conclusions:

Discharge NIHSS score is an important and reliable predictor of stroke recurrence and survival, confirming its utility in post-stroke prognosis. The use of PSM has improved the reliability of these findings, highlighting the importance of NIHSS for risk stratification and management in stroke care.