Association between proton pump inhibitors use and risk of asthma in Korea: A prevalent new-user cohort study
Bibliographic record
Abstract
There have been conflicting mechanisms that proton pump inhibitors (PPIs) may promote or prevent asthma development. However, the evidence on the association of PPI use with the risk of asthma and its exposure-response relationship has been limited. We aim to identify the association between the use of PPIs and the incidence of asthma, compared with use of histamine 2 receptor antagonists (H2RAs). A nationwide, prevalent new-user cohort study was conducted using Korea's National Sample Cohort database. Patients were defined as PPI or H2RA users between 2003 and 2019. PPI users matched to H2RA users based on time-conditional propensity score. Cox proportional hazards model was used to estimate adjusted hazard ratios with 95% confidence intervals of incident asthma associated with PPI use by duration of use, cumulative dose, and average dose per duration. Among the 250,041 pairs, PPI users (51.3% male; mean [SD] age, 42.6 [16.5]; mean follow-up, 6.7 years) showed a higher incidence rate of asthma (7.94 events per 1000 person-year) compared to H2RA users (3.70 events per 1000 person-year) with adjusted hazard ratio of 2.15 (95% confidence interval = 2.08-2.21). The risk of asthma was significantly increased across all observed groups of duration of use, cumulative dose, and average dose per duration. This study suggested that PPI use is associated with an increased risk of developing asthma compared to H2RA use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".