Progressive effects of valsartan compared with amlodipine in prevention of diabetes according to categories of diabetogenic risk in hypertensive patients: The VALUE trial
Bibliographic record
Abstract
We have previously shown that the angiotensin receptor blocker valsartan is associated with a lower incidence of new-onset type 2 diabetes than that with the calcium-channel antagonist amlodipine in the treatment of hypertensive patients at high cardiovascular risk. We have now investigated the benefits of valsartan vs amlodipine in patients of different categories of diabetogenic risk. Some 9995 patients without diabetes at onset participated in VALUE, with average follow-up of 4.2 years. Predictors of new diabetes were analyzed by stepwise logistic regression. A diabetes risk score for each patient was calculated based on a multivariate model. The risk of developing new diabetes in quartiles of risk for the disease was calculated as an odds ratio (OR) with 95% confidence intervals (CI). New diabetes was reported in 580 (11.5%) patients on valsartan and in 718 (14.5%) patients on amlodipine (p<0.0001). There was a more than sevenfold rise in the development of new diabetes from the lowest to the highest quartile of risk. When study treatment was included in the risk model, the odds in favor of valsartan in preventing new diabetes progressively increased with higher risk. Fifty-two (4.03%) patients developed diabetes on valsartan and 50 (4.14%) patients on amlodipine in the lowest quartile of risk, 73 (5.70%) patients on valsartan and 83 (6.81%) patients on amlodipine in the second quartile, and 126 (10.27%) patients on valsartan and 160 (12.58%) patients on amlodipine in the third quartile. The difference between treatments was highly significant in quartile 4 with 329 (26.68%) patients developing new diabetes on valsartan vs 425 (33.57%) patients on amlodipine (OR = 0.72, 95% CI 0.61-0.86, p = 0.0002). The number of patients needed for treatment for the duration of the trial in order to gain the benefit of valsartan over amlodipine in preventing one new case of diabetes was 43 in the third quartile and 15 in the fourth quartile of risk categories. We conclude that valsartan compared with amlodipine reduces the risk of developing diabetes mellitus, particularly in hypertensive patients with the highest susceptibility for development of diabetes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".