Effect of calcium channels blockers and inhibitors of the renin-angiotensin system on renal outcomes and mortality in patients suffering from chronic kidney disease: systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The renoprotective effect of inhibitors of renin-angiotensin system (RAS) has been identified through placebo-controlled trials. However, the effect of calcium-channel blockers (CCBs) on renal system is still controversial. Our current meta-analysis includes available evidences to compare the effect of dihydropyridine CCBs and ACEIs or ARBs on renal outcomes and mortality. We also further investigate whether CCBs can be used in combination with inhibitors of RAS to improve the prognosis of patients with chronic kidney disease (CKD). METHODS AND RESULTS: Electronic databases were searched up to July 2012, for clinical randomized controlled trials, assessing the effect of dihydropyridine CCBs on the incidence of end-stage renal disease (ESRD) and all-cause mortality in contrast to ACEIs or ARBs. Eight clinical trials were included containing 25,647 participants. ESRD showed significantly higher frequency with CCBs therapy compared with ACEIs or ARBs therapy, though blood pressure was decreased similarly in both groups in every trial (OR, 1.25; 95% CI, 1.05-1.48; p = 0.01). In contrast, there was no significant difference in the incidence of all-cause mortality between these two groups, though ACEIs or ARBs exhibited better renoprotective effect compared to CCBs (OR, 0.96; 95% CI, 0.89-1.03; p = 0.24). CONCLUSIONS: CCBs did not increase all-cause mortality incidence in patients with CKD though they displayed weaker renoprotective, compared to ACEIs or ARBs therapy. Our results suggest the combination of a CCB and an ACEI or ARB should be a preferable antihypertensive therapy in patients with CKD, considering their higher effect in decreasing blood pressure and fewer adverse metabolic problems caused.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.027 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".