Cardiovascular Effects of Angiotensin Converting Enzyme Inhibition or Angiotensin Receptor Blockade in Hemodialysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Cardiovascular (CV) disease causes significant morbidity and mortality among the hemodialysis (HD) population. This meta-analysis was performed to determine whether angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) reduce fatal and nonfatal CV events and left ventricular (LV) mass in patients receiving HD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Studies were identified by searching electronic databases, bibliographies, and conference proceedings. Two reviewers independently selected randomized controlled trials using ACEIs or ARBs compared with control among patients receiving HD. Studies were independently assessed for inclusion, quality, and data extraction. Random-effects models were used to estimate the pooled relative risk (RR) for CV outcomes and the weighted mean difference (WMD) for pooled change-from-baseline comparisons for LV mass for ACEI or ARB treated patients compared with control. RESULTS: Compared with control, the RR of CV events associated with ACEI or ARB use was 0.66 [95% confidence interval (CI) 0.35 to 1.25; P = 0.20]. ACEI or ARB use resulted in a statistically significant reduction in LV mass, with a WMD of 15.4 g/m(2) (95% CI 7.4 to 23.3; P < 0.001). CONCLUSIONS: Treatment with an ACEI or ARB reduced LV mass in patients receiving HD. However, their use was not associated with a statistically significant reduction in the risk of fatal and nonfatal CV events. Larger, high-quality trials in the HD population are required to determine if the effects of ACEI or ARB therapy on LV mass translate into decreased CV morbidity and mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.014 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".