Proton pump inhibitors use and risk of chronic kidney disease and end-stage renal disease
Bibliographic record
Abstract
INTRODUCTION: A possible association between long-term proton pump inhibitors (PPI) use and chronic kidney disease (CKD) has been recently described. Due to the potential health risk of this association, in the absence of proper clinical trials, we have decided to carry out a systematic review followed by meta-analysis. EVIDENCE ACQUISITION: PubMed, Cochrane Library, and Lilacs databases were searched. Studies that reported an association between PPI use and CKD or End-stage Renal Disease (ESRD) published until December 23, 2019, were included. All selected studies present high quality according to the New-Castle-Ottawa. The risk ratio (RR) and confidence interval (CI) were pooled using a random-effects model in CKD outcome analysis and fixed effects model for ESRD. A total of 10 observational studies were selected. EVIDENCE SYNTHESIS: Compared to patients who did not use PPI, the RR for CKD associated with PPI use was 1.35 (95% CI 1.15-1.56) with P<0.001, and the RR for ESRD associated with PPI use was 1.49 (95% CI 1.41-1.56) with P<0.001. CONCLUSIONS: This study indicates the presence of a significant association between PPI use and an increased risk of CKD and ESRD and reiterates the need for the medical prescription of this class of drugs to be made following the guidelines of the FDA.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".