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

ABSTRACT:

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 post-IVT 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 characterist

SUBMITTER: Yao MX 

PROVIDER: S-EPMC12454040 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature