Nonadherence Is Common in Patients With Apparent Resistant Hypertension: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: The prevalence of medication nonadherence in the setting of resistant hypertension (RH) varies from 5% to 80% in the published literature. The aim of this systematic review was to establish the overall prevalence of nonadherence and evaluate the effect of the method of assessment on this estimate. METHODS: MEDLINE, EMBASE, Cochrane, CINAHL, and Web of Science (database inception to November 2020) were searched for relevant articles. We included studies including adults with a diagnosis of RH, with some measure of adherence. Details about the method of adherence assessment were independently extracted by 2 reviewers. Pooled analysis was performed using the random effects model and heterogeneity was explored with metaregression and subgroup analyses. The main outcome measured was the pooled prevalence of nonadherence and the prevalence using direct and indirect methods of assessment. RESULTS: Forty-two studies comprising 71,353 patients were included. The pooled prevalence of nonadherence was 37% (95% confidence interval [CI] 27%-47%) and lower for indirect methods (20%, 95% CI 11%-35%), than for direct methods (46%, 95% CI 40%-52%). The study-level metaregression suggested younger age and recent publication year as potential factors contributing to the heterogeneity. CONCLUSIONS: Indirect methods (pill counts or questionnaires) are insufficient for diagnosis of nonadherence, and report less than half the rates as direct methods (direct observed therapy or urine assays). The overall prevalence of nonadherence in apparent treatment RH is extremely high and necessitates a thorough evaluation of nonadherence in this setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.042 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".