A comparison between persistence to therapy in ALLHAT and in everyday clinical practice: a generalizability issue.
Bibliographic record
Abstract
BACKGROUND: Persistence to therapy was very high in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) and was similar between treatment arms. Most patients were already on antihypertensive therapy before the trial began. Clinically, the results from this trial are more likely to be applied when antihypertensive therapy is initiated. OBJECTIVES: To assess whether the conclusions drawn from ALLHAT could be applied to the initiation of antihypertensive therapy. METHODS: A MEDLINE literature search was performed using the key words 'persistence', 'persistence to therapy', 'compliance' and 'adherence', and these were each linked with 'hypertension'. Studies from pharmaceutical databases were selected when they reported persistence to any antihypertensive therapy at one year according to which initial drug class (calcium channel blockers, angiotensin-converting enzyme inhibitors and thiazides) was initially prescribed. From the reported persistence rates, the number of patients was determined in whom treatment of hypertension results in a waste of health resources when each initial drug class was prescribed. RESULTS: Persistence to antihypertensive therapy at one year reported in the pharmaceutical databases varies from 5% to 75%. It was lower when the initial drug that was prescribed was a diuretic versus an angiotensin-converting enzyme inhibitor or a calcium channel blocker. The number of patients in whom treatment of hypertension resulted in a waste of resource was also higher when a diuretic was initially prescribed. CONCLUSION: Persistence to antihypertensive therapy is low for all the agents initiated and the lowest with diuretics. This should be considered as a word of caution when the ALLHAT conclusions are applied to the clinical 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 | 0.247 | 0.477 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.012 | 0.017 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".