The effect of angiotensin‐converting enzyme inhibitor/angiotensin receptor blocker use on mortality in patients with chronic kidney disease: a meta‐analysis of observational studies
Bibliographic record
Abstract
PURPOSE: There has been much controversy over the use of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs) on patients with renal dysfunction. The purpose of this study was to summarize the evidence regarding the effect of ACEIs/ARBs administration on mortality in patients with nondialysis-dependent chronic kidney disease (CKD) by using a meta-analytic approach. METHODS: We searched the PubMed, Embase, and Web of Science databases for studies on the effect of ACEIs/ARBs administration on mortality in patients with nondialysis-dependent CKD published before March 2015. Summary effect estimates with 95% confidence intervals were derived using the random-effects model, no matter whether the heterogeneity between the included studies was of statistical significance or not. Subgroup analyses, sensitivity analyses, and publication bias tests were performed. RESULTS: Up to 25 March 2015, 10 cohort studies were included in this meta-analysis. The hazard risk of the association between ACEIs/ARBs administration and overall mortality was 0.83 (95% confidence interval 0.78-0.87) using a random-effects model with no heterogeneity (heterogeneity test I(2) = 43.8%, p = 0.067) and publication bias (Egger's test, p = 0.763). The subgroup was divided according to estimated glomerular filtration rate, duration of follow-up, Newcastle-Ottawa Scale star, and proportion of patients with common complications including heart failure, diabetes mellitus, and hypertension. Improved survival outcomes were observed in all subgroups analysis. Sensitivity analysis proved that overall estimated effect was robust. CONCLUSION: This meta-analysis suggested that the use of ACEIs/ARBs in patients with nondialysis-dependent CKD was associated with improved survival. However, randomized studies are needed to confirm these findings and further establish causal relationship. Copyright © 2016 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.031 | 0.058 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.064 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".