What question did this study set out to answer?

This study aims to evaluate the role of early neurological improvement as a predictor for functional outcomes 90 days post-acute ischemic stroke.

March 12, 2026Open Access

Early neurological improvement as a dynamic predictor for 90-day functional outcome in acute ischemic stroke: a prospective cohort study

Key Points

This study aims to evaluate the role of early neurological improvement as a predictor for functional outcomes 90 days post-acute ischemic stroke.
Conducted a prospective observational cohort study with 200 acute ischemic stroke patients.
Collected data on demographic, clinical, laboratory, imaging, and treatment variables at admission.
Defined early neurological improvement as the change in NIHSS from baseline to 24 hours.
Developed two logistic regression models: one with baseline variables and another incorporating ΔNIHSS.
Assessed discrimination with the area under the receiver operating characteristic curve and calibration with bootstrap-corrected calibration plots.
59% of patients achieved good functional outcomes at 90 days (mRS 0–2).
Model 1 showed strong discrimination (AUC 0.863) with specific independent predictors identified.
Incorporating ΔNIHSS optimized model calibration, reducing prediction error by 47%.
Greater early neurological improvement was linked to better outcomes with an adjusted odds ratio of 1.48 per 5-point ΔNIHSS increase.

Abstract

Background Early neurological improvement (ENI) within the first 24 h after acute ischemic stroke (AIS) has been proposed as a rapid dynamic predictor for treatment response. However, the prognostic value of ENI for 90-day functional recovery in real-world clinical practice remains uncertain, especially in heterogeneous stroke populations receiving mixed reperfusion treatments. We aimed to evaluate the association between 24-h neurological change and 90-day functional outcome in a contemporary single-center AIS cohort. Methods We conducted a prospective observational cohort study including 200 consecutive AIS patients between January 2023 and December 2024. Baseline demographic, vascular risk factor, clinical, laboratory, imaging, and treatment variables were collected at admission. ENI was defined as the change in NIHSS between baseline and 24 h (ΔNIHSS = NIHSSbaseline–NIHSS₂4h). Two logistic regression models were developed: Model 1, using only baseline clinical and imaging variables, and Model 2, which incorporated ΔNIHSS as a dynamic predictor. Discrimination was evaluated using the area under the receiver operating characteristic curve (AUC), and calibration was assessed using bootstrap-corrected calibration plots. Nomograms were constructed for bedside application. Results Among 200 patients, 118 (59. 0%) achieved good functional outcome at 90 days (mRS 0–2). In Model 1, age, baseline NIHSS, and ASPECTS were independently associated with 90-day outcomes, whereas hypertension was negatively associated. Model 1 demonstrated strong discrimination (AUC 0. 863). While discrimination reached a prognostic plateau (AUC 0. 863 vs. 0. 855), the incorporation of ΔNIHSS significantly optimized model calibration, reducing the mean absolute prediction error by 47% (0. 051–0. 027). This indicates that the dynamic model provides substantially more accurate probability estimates for individual patients. Greater early neurological improvement was independently associated with good outcome (adjusted OR per 5-point ΔNIHSS increase, 1. 48; 95% CI 1. 11–1. 97). Corresponding ROC curves, calibration plots, and nomograms for both models are presented. Conclusion Early neurological improvement within 24 h after AIS serves as a reliable and rapid dynamic predictor for 90-day functional recovery. While baseline clinical and imaging variables provide strong prognostic value, incorporating early neurological change enhances model calibration and clinical usefulness. This dynamic paradigm supports integrating short-term neurological change into prognostic assessment and individualized post-stroke care.

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