Abstract 15722: Proton Pump Inhibitors and Risk of Myocardial Infarction: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Introduction: Proton Pump Inhibitors (PPIs) are generally considered safe, but recent evidence suggests otherwise. Objective: This systematic review and meta-analysis assessed the association between PPIs and the risk of myocardial infarction (MI), using both clinical trials and observational studies. Methods: A systematic search was performed in December 2019 to retrieve all potential studies using PubMed, PsycInfo, International Pharmaceutical Abstracts, Web of Science, and Clinicaltrials.gov. This search initially identified any published studies describing any adverse event (AE) or outcomes related to PPI. Records were included in this study if 1) studies were published in English, 2) study design was clinical trials or observational studies, 3) PPI use was the exposure or treatment, and 4) study outcome was the incidence of MI. Two researchers independently reviewed all identified records, performed full article review, extracted data into structured evidence table, and conducted quality assessment using Newcastle-Ottawa Scale and Quality Assessment Tool for Quantitative Studies. Meta-analysis was performed using the RStudio software to assess the risk of MI with PPI use. Results: A total of 4,507 abstracts meeting the inclusion criteria were identified, and 20 full articles were included in this study, among which 10 were cohort, 3 were case-control, 3 were RCT post-hoc analysis, and 4 were RCT studies. The pooled Odds Ratio (OR)=1.40 with 95% CI=1.20-1.63 for all studies indicated the presence of an association between PPI use and increased risk of MI compared to PPI non-users. Meta-analysis found a similar association between PPI use and increased risk of MI in observational studies (OR=1.40; 95% CI=1.20, 1.64) but no association (OR=0.90; 95% CI=0.47, 1.73) in RCT-studies. Heterogeneity was high (I 2 > 75%) for all analyses except for RCTs (I 2 =0%). Conclusion: Although our meta-analysis identified the association between PPI use and increased risk of MI, results from RCTs did not agree with observational studies. Due to the mixed findings by study designs and high variation of heterogeneity among studies, the pharmacovigilance system should evaluate different levels of evidence to support decision making in safety of drug products.
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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 | 0.023 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.038 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".