Early heart rate predicts 3-month outcomes in acute ischemic stroke patients receiving intravenous thrombolysis - a machine learning approach

Q: What question does the study address about early heart rate in AIS after IVT?

The study evaluates whether heart rate variability within 24 hours after IVT predicts early neurological deterioration and 3-month functional outcomes using machine learning.

Q: Which patient group and data window were analyzed in the methods?

The analysis included AIS patients without atrial fibrillation who received IVT at Dongguan People’s Hospital between January 2017 and December 2022, using hourly HR metrics during the first 24 hours.

Q: Which HR metrics were significant for predicting poor 3-month outcomes?

Independent predictors included admission NIHSS, maximum HR, minimum HR, and HR SD, while HR CV was also significant though strongly correlated with SD.

Q: Did any HR metrics predict early neurological deterioration (END)?

No HR metrics were significantly associated with END in this study.

Aug 4, 2026

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Early heart rate (HR) dynamics may guide risk assessment in acute ischemic stroke (AIS) receiving intravenous thrombolysis (IVT), yet their prognostic value remains unclear. A retrospective cohort of AIS patients without atrial fibrillation assessed hourly HR metrics within 24 hours post-IVT. Machine-learning models evaluated prediction of early neurological deterioration and 3-month functional outcomes based on receiver operating characteristic performance.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages11

Reading Time28 min

AccessFree to download

Background

Methods

Results

Conclusion

Key findings

TYPE Original Research PUBLISHED 09 September 2025 DOI 10.3389/fneur.2025.1668901 OPEN ACCESS EDITED BY Adnan Mujanovic, University Hospital Bern Inselspital, Switzerland REVIEWED BY Mark Stephen Kindy, United States Department of Veterans Affairs, United States Luwen Zhu, Heilongjiang University of Chinese Medicine, China *CORRESPONDENCE Yong-Lin Liu [ly_twins@126.com](ly_twins@126.com) †These authors share first authorship RECEIVED 18 July 2025 ACCEPTED 24 August 2025 PUBLISHED 09 September 2025 CITATION Yao M-X, Yao M-Y, Gu J, Gao T, Yuan Y-M, Chen Y-K and Liu Y-L (2025) Early heart rate predicts 3-month outcomes in acute ischemic stroke patients receiving intravenous thrombolysis: a machine learning approach. Front. Neurol. 16:1668901 . doi: 10.3389/fneur.2025.1668901 COPYRIGHT © 2025 Yao, Yao, Gu, Gao, Yuan, Chen and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Early heart rate predicts 3-month outcomes in acute ischemic stroke patients receiving intravenous thrombolysis: a machine learning approach Mian-Xuan Yao 1†, Min-Yi Yao 1†, Jia Gu 2, Ting Gao 2,3,4, Yi-Mian Yuan 5, Yang-Kun Chen 1,4,6 and Yong-Lin Liu 1,4,6* 1 Department of Neurology, The Tenth Affiliated Hospital of Southern Medical University (Dongguan People’s Hospital), Dongguan, China, 2School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, China, 3Center for Mathematical Sciences, Huazhong University of Science and Technology, Wuhan, China, 4Guangdong Provincial Key Laboratory of Mathematical and Neural Dynamical Systems, Great Bay University, Dongguan, China, 5 First School of Clinical Medicine, Guangdong Medical University, Zhanjiang, China, 6 Intelligent Brain Imaging and Brain Function Laboratory (Dongguan Key Laboratory), Dongguan People’s Hospital, Dongguan, China Background: The predictive role of early heart rate (HR) dynamics in acute ischemic stroke patients (AIS) receiving intravenous thrombolysis (IVT) remains unclear. This study aimed to evaluate whether HR variability within 24 h postIVT predicts early neurological deterioration (END) and 3-month functional outcomes using machine learning. Methods: This retrospective analysis included AIS patients without atrial fibrillation (AF) who received IVT at Dongguan People’s Hospital between January 2017 and December 2022. Hourly HR metrics (mean HR, SD, coefficient of variation [CV]) were analyzed. Primary outcomes were END (≥4-point NIHSS increase within 72 h) and poor 3-month outcomes (mRS ≥ 3) . Machine learning models were developed and validated via receiver operating characteristic (ROC) analysis. Results: Among 381 patients, logistic regression identified NIHSS on admission (OR = 1. 287, p < 0.001), maximum HR (OR = 0.956, p = 0.023), minimum HR (OR = 1.027, p = 0.001), and HR SD (OR = 1.356, p = 0.002) as independent predictors of poor 3-month outcomes. HR CV also showed significance but correlated strongly with SD. A machine learning model integrating onset-totreatment time, NIHSS, and HR parameters (max/min HR, mean HR, SD) achieved an area under the ROC curve (AUC) of 0.82 for predicting 3-month outcomes. No HR metrics were significantly associated with END. Conclusion: In AIS patients without AF, early HR dynamics—particularly maximum HR, minimum HR, SD, and CV—strongly correlate with 3-month functional outcomes after IVT. The machine learning model demonstrated high predictive accuracy, highlighting the potential of real-time HR monitoring for risk stratification and personalized management i

FAQs

What question does the study address about early heart rate in AIS after IVT?

The study evaluates whether heart rate variability within 24 hours after IVT predicts early neurological deterioration and 3-month functional outcomes using machine learning.

Which patient group and data window were analyzed in the methods?

The analysis included AIS patients without atrial fibrillation who received IVT at Dongguan People’s Hospital between January 2017 and December 2022, using hourly HR metrics during the first 24 hours.

Which HR metrics were significant for predicting poor 3-month outcomes?

Independent predictors included admission NIHSS, maximum HR, minimum HR, and HR SD, while HR CV was also significant though strongly correlated with SD.

Did any HR metrics predict early neurological deterioration (END)?

No HR metrics were significantly associated with END in this study.

Aug 4, 2026

Upload by Evangeline