Ace-inhibitor treatment corrects the defect in vascular insulin resistance in hypertension
Bibliographic record
Abstract
Insulin resistance is a risk factor for hypertension, although the causality of the relationship has not been proved. Systemic insulin resistance parallels resistance to the vasodilating effect of insulin. Systemic insulin resistance has been shown to be improved by both lifestyle modification as well as some specific antihypertensive therapies—including ACE-inhibition. Whether insulin resistance can be improved by antihypertensive therapy was unknown. Therefore, we determined the effect of therapy with the ACE-inhibitor, quinapril, on vascular sensitivity to insulin (assessed by the dorsal hand vein linear variable differential transformer—LVDT technique) in 12 hypertensive subjects using a randomized double-blinded, crossover design. At the baseline LVDT assessment, vascular sensitivity to insulin was found to be significantly inversely correlated with BMI and significantly positively correlated with urinary sodium excretion. Three months of therapy with quinapril was associated with a significant improvement in vascular sensitivity to insulin, as determined by a decrease in the ED50 for insulin (Placebo=501±189 μU/min; Quinapril=276±100 μU/min, p<0.05). Also, maximal isoproterenol-mediated relaxation was enhanced (Placebo=92±15% of baseline distension; Quinapril=151±31% p<0.05). There was no effect of ACE-inhibition on nitroglycerin-mediated relaxation. Phenylephrine-mediated vasoconstriction was not altered. ACE-inhibitors have been shown, in both hypertensive patients, and those at high risk of atherosclerotic disease, to delay the appearance of diabetes as well as its complications. The current study suggests the hypothesis that this beneficial effect of ACE-inhibitors may be related to their beneficial effects on vascular function in general, and on insulin-mediated vascular responses, in particular.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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".