Proton pump inhibitor use and risk of dementia
Bibliographic record
Abstract
BACKGROUND: Proton pump inhibitors (PPIs) are an established kind of drugs used to the treatment of most acid-related diseases. Some prospective studies have noticed that PPI use was associated with increased dementia risk. However, the results of those studies were inconsistent and controversial. This meta-analysis aims to determine the association of PPI use and risk of dementia among older people. METHODS: Relevant articles were systematically identified by searching the PubMed, EMBASE, and Cochrane Library databases from inception to February 2018. Cohort studies that reported the risk of dementia or Alzheimer's disease (AD) among PPI users compared with non-PPI users were included. The quality of studies was assessed using the Newcastle-Ottawa Scale (NOS). The publication bias was detected by a funnel plot and Egger test. The meta-analysis will abstract risk estimates including relative risks (RRs), hazard ratios (HRs), and odds ratios (ORs) with a 95% confidence interval (CI) for the associations between PPI use and dementia or Alzheimer's risk. Study-specific results were pooled using a random-effects model. RESULTS: Six cohort studies were selected finally. The pooled RRs of dementia and AD were 1.23 (95% CI: 0.90-1.67) and 1.01 (95% CI: 0.78-1.32), respectively, compared with those of non-PPI use. The Egger test and funnel plot showed no existence of publication bias. Overall, there was no statistically significant association between PPI use and risk of dementia or AD (P >.05). CONCLUSIONS: This meta-analysis suggests that there was no statistical association between PPIs use and increased risk of dementia or AD.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.015 |
| Bibliometrics | 0.005 | 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) | 0.002 | 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".