The impact of fixed‐dose combination versus free‐equivalent combination therapies on adherence for hypertension: a meta‐analysis
Bibliographic record
Abstract
Nonadherence to antihypertensive medication is considered as a reason of inadequate control of blood pressure. This meta-analysis aimed to systemically evaluate the impact of fixed-dose combination (FDC) therapy on hypertensive medication adherence compared with free-equivalent combination therapies. Articles were retrieved from MEDLINE and Embase databases using a combination of terms "fixed-dose combinations" and "adherence or compliance or persistence" and "hypertension or antihypertensive" from January 2000 to June 2017 without any language restriction. A meta-analysis was performed to parallel compare the impact of FDC vs free-equivalent combination on medicine adherence or persistence. Studies were independently reviewed by two investigators. Data from eligible studies were extracted and a meta-analysis was performed using R version 3.1.0 software. A total of nine studies scored as six of nine to eight of nine for Newcastle-Ottawa rating with 62 481 patients with hypertension were finally included for analysis. Results showed that the mean difference of medication adherence for FDC vs free-equivalent combination therapies was 14.92% (95% confidence interval, 7.38%-22.46%). Patients in FDC group were more likely to persist with their antihypertensive treatment, with a risk ratio of 1.84 (95% confidence interval, 1.00-3.39). This meta-analysis confirmed that FDC therapy, compared with free-equivalent combinations, was associated with better medication adherence or persistence for patients with hypertension. It can be reasonable for physicians, pharmacists, and policy makers to facilitate the use of FDCs for patients who need to take two or more antihypertensive drugs.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.064 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".