Impact of telmisartan on cardiovascular outcome in hypertensive patients at high risk
Bibliographic record
Abstract
BACKGROUND: In the Telmisartan Randomised AssessmeNt Study in ACE iNtolerant subjects with cardiovascular Disease, all patients were at high cardiovascular risk, and a substantial proportion were hypertensive. We performed a post-hoc analysis to explore the hypothesis that telmisartan has a differential action in hypertensive vs. nonhypertensive patients. METHODS: The primary four-fold endpoint (composite of cardiovascular death, myocardial infarction (MI), stroke, or hospitalization for heart failure), the secondary three-fold endpoint (cardiovascular death, MI, and stroke), the individual components, new onset of left ventricular hypertrophy (LVH), and new onset of albuminuria were analyzed. RESULTS: There was no evidence for a significantly differential treatment effect of telmisartan in hypertensive and nonhypertensive patients for any endpoints, although the occurrence of the secondary three-fold endpoint was significantly lower in the telmisartan group (13.0%) compared with placebo (15.0%, P < 0.05) only in hypertensive patients. Moreover, data from this post-hoc analysis suggest that MI may be less frequent in hypertensive patients treated with telmisartan (3.8 vs. 5.1%; P < 0.05). Telmisartan may also reduce new onset of LVH (nonhypertensive patients P < 0.05; hypertensive patients P < 0.001) in both subgroups, and new onset of microalbuminuria and macroalbuminuria in hypertensive patients (P < 0.001 and P < 0.01, respectively).The effect of telmisartan in hypertensive and nonhypertensive patients at high cardiovascular risk was not different. This post-hoc analysis suggests that MI may be further reduced by telmisartan in hypertensive patients. Further investigations are needed to study the hypotheses raised by this explanatory analysis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".