The Global Incidence of Peptic Ulcer Disease Is Decreasing Since the Turn of the 21st Century: A Study of the Organisation for Economic Co-Operation and Development (OECD)
Bibliographic record
Abstract
INTRODUCTION: Peptic ulcer disease (PUD) is a common cause of hospitalization worldwide. We assessed temporal trends in hospitalization for PUD in 36 Organisation for Economic Co-operation and Development (OECD) countries since the turn of the 21st century. METHODS: The OECD database contains data on PUD-related hospital discharges and mortality for 36 countries between 2000 and 2019. Hospitalization rates for PUD were expressed as annual rates per 100,000 persons. Joinpoint regression models were used to calculate the average annual percent change (AAPC) with 95% confidence intervals (CIs) for each country, which were pooled using meta-analyses. The incidence of PUD was forecasted to 2021 using autoregressive integrated moving average and Poisson regression models. RESULTS: The overall median hospitalization rate was 42.4 with an interquartile range of 29.7-60.6 per 100,000 person-years. On average, hospitalization rates (AAPC = -3.9%; 95% CI: -4.4, -3.3) and morality rates (AAPC = -4.7%; 95% CI: -5.6, -3.8) for PUD have decreased from 2000 to 2019 globally. The forecasted incidence of PUD hospitalizations in 2021 ranged from 3.5 per 100,000 in Mexico to 92.1 per 100,000 in Lithuania. Across 36 countries in the OECD, 329,000 people are estimated to be hospitalized for PUD in 2021. DISCUSSION: PUD remains an important cause of hospitalization worldwide. Reassuringly, hospitalizations and mortality for PUD have consistently been falling in OECD countries in North America, Latin America, Europe, Asia, and Oceania. Identifying underlying factors driving these trends is essential to sustaining this downward momentum.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| 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".