Proportion and risk indicators of nonadherence to antihypertensive therapy: a meta-analysis
Bibliographic record
Abstract
PURPOSE: The World Health Organization (WHO) concluded that poor adherence to treatment is the most important cause of uncontrolled high blood pressure, with approximately 75% of patients not achieving optimum blood pressure control. The WHO estimates that between 20% and 80% of patients receiving treatment for hypertension are adherent. As such, the first objective of our study was to quantify the proportion of nonadherence to antihypertensive therapy in real-world observational study settings. The second objective was to provide estimates of independent risk indicators associated with nonadherence to antihypertensive therapy. MATERIALS AND METHODS: We performed a systematic literature review and meta-analysis of all studies published between database inception and December 31, 2011 that reviewed adherence, and risk indicators associated with nonadherence, to antihypertensive medications. RESULTS: In the end, 26 studies met our inclusion and exclusion criteria and passed our methodological quality evaluation. Of the 26 studies, 48.5% (95% confidence interval 47.7%-49.2%) of patients were adherent to antihypertensive medications at 1 year of follow-up. The associations between 114 variables and nonadherence to antihypertensive medications were reviewed. After meta-analysis, nine variables were associated with nonadherence to antihypertensive medications: diuretics in comparison to angiotensin-converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARBs) and calcium channel blockers (CCBs), ACE inhibitors in comparison to ARBs, CCBs in comparison to ARBs, those with depression or using antidepressants, not having diabetes, lower income status, and minority cultural status. CONCLUSION: This study clarifies the extent of adherence along with determining nine independent risk indicators associated with nonadherence to antihypertensive medications.
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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 | 0.029 | 0.057 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.074 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".