A249 PROTON PUMP INHIBITOR USE AND RISK OF DEMENTIA: AN UMBRELLA REVIEW OF SYSTEMATIC REVIEWS AND META-ANALYSES
Bibliographic record
Abstract
Abstract Background Clinical studies about the association between long term PPI use and dementia have been inconsistent, with systematic reviews and meta-analyses (SR/MA) reaching disparate conclusions. Aims This umbrella review of SR/MA attempts to clarify the current understanding of any possible association linking PPI use to dementia. Methods We searched Embase, Medline, CENTRAL and ISI Web of Science for fully published SR/MA in English up to June 2024 using controlled vocabulary and text words ((1) proton pump and (2) dementia (dementia and mild cognitive impairment, Alzheimer disease)). SR/MA methodological quality was scored using the AMSTAR-2 tool. Results Eleven SR/MA published (May 2016 - February 2023) described 21 studies (one randomized trial). Only one high-quality SR/MA significantly associated PPI use with dementia. None of six SR/MA investigating PPI use and Alzheimer’s disease showed a significant association. Significant associations with dementia in subgroup analyses were found in one SR/MA each for older patients (age > 65 years) (HR=1.39 (1.17;1.65)), long term PPI use (> 5 years) (HR=1.28 (1.12; 1.46)), short term PPI use (< 5 years) (RR=1.62 (1.40–1.86)), when only considering higher quality studies (RR=1.54 (1.12; 2.13)), and amongst European populations (HR=1.46 (1.23–1.73)). Two SR/MA found an association when only assessing prospective cohort studies (RR=1.36 (1.19; 1.55)), (RR=1.44 (1.36; 1.52)). Conclusions Most SR/MA suggest no link between PPI use and dementia. Only properly designed, adequately powered randomized trials can rule out a small but significant association possibly linking PPI use to dementia. N = study number in SR/MA, HR = hazards ratio, RR = relative risk, OR = odds ratio, NA = Not applicable Funding Agencies None
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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 | 0.048 | 0.130 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.025 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".