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Measurement differences explain much of the variation in adherence and persistence after ischemic stroke, and standardized estimates are lower: a systematic review with meta-regression

In brief

Standardized estimates put post-stroke medication adherence at 54%, persistence at 48%

Across 101 studies, conventional pooled estimates suggested that about three-quarters of patients took secondary prevention medicines as intended and continued them, but estimates standardized for how studies measured these outcomes fell to 53.7% and 48.2%. Measurement methods explained more variation than patient characteristics, and standardized persistence dropped to 28.1% beyond 30 months. The model-based figures underscore the need for consistent long-term tracking.

Journal
Journal of clinical epidemiology (Q1)
Published
22 October 2026
Study design
Systematic review of cohort studies
Evidence level
Level 2, Moderate (CEBM 2a)
Authors
Youli Jiang, Jingfang Chen, Linlin Liu, Wan Ling Lee, Rongjia Pan, Qiuyang Qian, et al.
PMID
42914064
DOI
10.1016/j.jclinepi.2026.112571

Why clinicians should know about it

  • Picked for Epidemiology (paper of the day, 25 October 2026): Methods-focused review quantifies measurement-related heterogeneity and bias

Abstract

OBJECTIVE: Continued use of secondary prevention medications after ischemic stroke or transient ischemic attack is an important component of long-term management. Reported estimates of adherence and persistence vary considerably across studies, limiting comparison and interpretability. Although some variation may reflect differences in patient behavior, inconsistencies in operational definitions and measurement approaches are also likely to contribute. We sought to examine sources of heterogeneity and to derive standardized estimates using a common reference measurement framework. STUDY DESIGN AND SETTING: We searched bibliographic databases, dissertations, and trial registries from inception to September 10, 2025, for routine-care studies reporting adherence or persistence to secondary prevention medications after ischemic stroke or transient ischemic attack. Cutoff-based proportions were extracted. We used 3-level hierarchical Bayesian models to characterize heterogeneity and multivariable meta-regression to evaluate associations with measurement specifications, follow-up window, medication class, region, and study-level characteristics. From the fitted model, we derived estimates standardized to a prespecified reference specification: pharmacy or administrative data, moderate definition stringency, and a 9- to 15-month follow-up window. RESULTS: The review included 141 studies; 101 (432 estimates; 976,020 participants) contributed to the quantitative synthesis. Unstandardized pooled estimates suggested that 74.1% of patients were adherent and 76.8% were persistent. Heterogeneity was substantial, with explained variation concentrated more in the measurement-related Assessment and Administration domains than in reported Patient characteristics. Under the common reference specification, the model-based estimates were lower, at 53.7% for adherence and 48.2% for persistence. Standardized persistence declined from 63.3% at 1 to 4 months to 28.1% beyond 30 months. Adjusted estimates were generally lower in Asia; persistence was numerically lowest for anticoagulants, although credible intervals were wide and overlapping. CONCLUSION: A large proportion of the heterogeneity reported in medication adherence and persistence after ischemic stroke or transient ischemic attack appears to be attributable to methodological non-equivalence in how these outcomes are defined and measured. When evaluated within a standardized framework, suboptimal medication continuation appears more common than conventional pooled estimates indicate. Meaningful surveillance and benchmarking require longitudinal, standardized, and transparent measures of medication continuation rather than reliance on discharge prescribing alone.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.