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

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.