Evidence map›Paper›PMID 41877777›Full record

ArticleFrontiers in medicine2026

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

Zhiyuan Chu, Xinzheng Fu, Zhouming Ren, Tian Le, Xuyan Zhang, Yueyue Zhang, Wei Yao

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Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zhiyuan ChuHaining People's Hospital, Haining, China.
Xinzheng FuHaining People's Hospital, Haining, China.
Zhouming RenHaining People's Hospital, Haining, China.
Tian LeHaining People's Hospital, Haining, China.
Xuyan ZhangHaining People's Hospital, Haining, China.
Yueyue ZhangHaining People's Hospital, Haining, China.
Wei YaoHaining People's Hospital, Haining, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 = NIHSS_baseline-NIHSS_24h). 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.

Indexed as

acute ischemic strokeearly neurological improvementfunctional outcomeNIHSSnomogramprognosis

Identifiers

PMID41877777
PMCPMC13006309

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