Efficacy of losartan for improving insulin resistance and vascular remodeling in hemodialysis patients
Bibliographic record
Abstract
Insulin resistance and vascular remodeling are prevalent and predict cardiovascular mortality in hemodialysis patients. Angiotensin II (Ang II) may be involved in both pathogenesis. In the present study, we investigated the effects of the Ang II receptor blocker losartan on insulin resistance, arterial stiffness, and carotid artery structure in hemodialysis patients. Seventy-two hemodialysis patients were randomly assigned to receive either losartan 50 mg qd (n = 36) or β-blocker bisoprolol 5 mg qd (n = 36). At the start and at month 12, ambulatory blood pressure (BP) monitoring, aortic pulse wave velocity (PWV) measurements, and carotid artery ultrasound were performed, and homeostasis model assessment index of insulin resistance (HOMA-IR) was determined. During the study period, bioimpedance method was used to evaluate volume status every 3 months. Home-monitored BPs were measured at least monthly. Ambulatory BP decreased significantly and similarly by either losartan or bisoprolol. Decreases in PWVs in losartan group at the end of month 12 were significantly greater than changes in PWV in bisoprolol group (0.9 ± 0.3 vs. 0.4 ± 0.5 m/s, P = 0.021). Common carotid artery intima-media cross-sectional area decreased significantly only in patients treated with losartan (20.3 ± 4.9 vs. 19.1 ± 5.1 mm(2) , P = 0.001), and HOMA-IR was also reduced in losartan group only (1.9 ± 1.0 vs. 1.7 ± 0.8, P = 0.003). Multiple regression analysis showed significant correlations between changes in PWV and changes in HOMA-IR. With comparable BP-lowering efficacy, losartan achieved better improvement in insulin sensitivity, arterial stiffness, and carotid artery hypertrophy in hemodialysis patients. The regression of arterial stiffness may be in part through attenuation in insulin resistance.
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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 | 0.001 |
| 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".