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◆ Journal of visualized experiments : JoVE2026-08-11

Longitudinal Monitoring and Predictive Modeling of Medication Adherence in Ischemic Stroke Patients.

Linxue Hu, Xiaoyan Wu, Ming Li, Zhiqiang Deng, Yan Liang, Dezhi Chen, Rong Yang

原始摘要(英文原文)· Original abstract
Medication adherence is central to secondary prevention after ischemic stroke, but self-reported adherence may change during follow-up. In this single-center longitudinal framework, 210 participants were enrolled, and 191 completed the 180-day assessment. Medication-taking was assessed using a structured telephone interview for days 1-30, 31-90, and 91-180, and was classified as good when the exposure-day-weighted composite adherence percentage was at least 80%. The Chinese BMQ-Specific and Family APGAR were administered at day 30, day 90, and day 180. A four-predictor logistic model used residence, sex, day-30 BMQ-NCD, and day-30 Family APGAR and was internally validated with 1,000 bootstrap resamples. Among 191 complete cases, good adherence was 84.3% (95% CI, 78.3%-89.1%) at day 30, 77.0% (95% CI, 70.3%-82.7%) at day 90, and 72.8% (95% CI, 65.9%-79.0%) at day 180. Urban residence, male sex, day-30 BMQ-NCD, and day-30 Family APGAR score were associated with day-180 adherence. The apparent AUC was 0.879 (95% CI, 0.821-0.928), and the optimism-corrected AUC was 0.867. The protocol provides a reproducible framework for longitudinal assessment of self-reported adherence and an internally validated day-30 prediction model. External validation and objective adherence measures are required before clinical implementation.
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Longitudinal Monitoring and Predictive Modeling of Medication Adherence in Ischemic Stroke Patients. — 科研速览 Science Skim