Early heart rate predicts 3-month outcomes in acute ischemic stroke patients receiving intravenous thrombolysis: a machine learning approach
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 in thrombolysis-treated AIS patients.
Authors
- Yuehuan Yuan
- Yong‐Lin Liu (ORCID: https://orcid.org/0000-0002-6204-4231)
- Min-Yi Yao (ORCID: https://orcid.org/0000-0002-6524-3797)
- Mian-Xuan Yao
- Yang‐Kun Chen
- Ting Gao (ORCID: https://orcid.org/0009-0003-4684-5156)
- Jia Gu
Institutions
- Guangdong Medical College (CN)
- Dongguan People’s Hospital (CN)
- Dynamic Systems (United States) (US)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-09-09
- DOI
- https://doi.org/10.3389/fneur.2025.1668901
- Primary Topic
- Heart Rate Variability and Autonomic Control
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China