Proton pump inhibitors and the risk of acute kidney injury in older patients: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Proton pump inhibitors (PPIs) cause interstitial nephritis and are an underappreciated cause of acute kidney injury. We examined the risk of acute kidney injury and acute interstitial nephritis in a large population of older patients receiving PPIs. METHODS: We conducted a population-based study involving Ontario residents aged 66 years and older who initiated PPI therapy between Apr. 1, 2002, and Nov. 30, 2011. We used propensity score matching to establish a highly comparable reference group of control patients. The primary outcome was hospital admission with acute kidney injury within 120 days, and a secondary analysis examined acute interstitial nephritis. We used Cox proportional hazards regression to adjust for differences between groups. RESULTS: We studied 290 592 individuals who commenced PPI therapy and an equal number of matched controls. The rates of acute kidney injury (13.49 v. 5.46 per 1000 person-years, respectively; hazard ratio [HR] 2.52, 95% CI 2.27 to 2.79) and acute interstitial nephritis (0.32 vs. 0.11 per 1000 person-years; HR 3.00, 95% CI 1.47 to 6.14) were higher among patients given PPIs than among controls. INTERPRETATION: In our study population of older adults, those who started PPI therapy had an increased risk of acute kidney injury and acute interstitial nephritis. These are potentially reversible conditions that may not be readily attributed to drug treatment. Clinicians should appreciate the risk of acute interstitial nephritis during treatment with PPIs, monitor patients appropriately and discourage the indiscriminate use of these drugs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".