The association of depression with adherence to antihypertensive medications: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To examine the strength and consistency of the evidence on the relationship between depression and adherence to antihypertensive medications. METHODS: The MEDLINE, CINAHL, PsycINFO, Embase, SCOPUS, and ISI databases were searched from inception until 11 December 2009 for published studies of original research that assessed adherence to antihypertensive medications and used a standardized interview, validated questionnaire, or International Classification of Diseases Ninth Revision code to assess depression or symptoms of depression in patients with hypertension. Manual searching was conducted on 22 selected journals. Citations of included articles were tracked using Web of Science and Google Scholar. Two investigators independently extracted data from the selected articles and discrepancies were resolved by consensus. RESULTS: Eight studies were identified that included a total of 42,790 patients. Ninety-five percent of these patients were from one study. Only four of the studies had the assessment of this relationship as a primary objective. Adherence rates varied from 29 to 91%. There were widely varying results within and across studies. All eight studies reported at least one significant bivariate or multivariate negative relationship between depression and adherence to antihypertensive medications. Insignificant findings in bivariate or multivariate analyses were reported in six of eight studies. CONCLUSION: All studies reported statistically significant relationships between depression and poor adherence to antihypertensive medications, but definitive conclusions cannot be drawn because of substantial heterogeneity between studies with respect to the assessment of depression and adherence, as well as inconsistencies in results both within and between studies. Additional studies would help clarify this relationship.
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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 | 0.011 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".