S2304 Temporal Trends in the Incidence of Peptic Ulcer Disease in Canada Over the Past 3 Decades
Bibliographic record
Abstract
Introduction: Peptic ulcer disease (PUD) is among the most prevalent gastrointestinal diseases worldwide with considerable variation in incidence among regions and nations. Additionally, PUD results in considerable global health burden due to the resultant morbidity and diminished quality of life. Accordingly, the identification of temporal trends in the incidence of PUD is of paramount significance in the introduction of effective interventions, both preventative and therapeutic, and healthcare policies. Methods: The incidence of PUD in Canada over the past 30 years was initially evaluated by retrieving the relevant data from the Global Burden of Diseases 2019 database. The temporal trends in the incidence were evaluated through the use of Joinpoint Regression Analysis software that was utilized to calculate the annual percentage change (APC) and average annual percentage change (AAPC) stratified by gender and age. Results: Over the period 1990-2019, a total of 452,089 PUD cases were reported in Canada with a female predominance of 54.1%. Stratification by age revealed a statistically significant decline in PUD incidence, with the most prominent decline being reported in individuals aged 75 years and older with an AAPC of -2.96 (95%confidence interval [CI] -3.00 to -2.92; P< 0.001). A similar, but slightly less, decrease in PUD incidence was observed in the 50-74 years old age group with an AAPC of -2.63 (95%CI -2.66 to -2.60; P< 0.001). Younger individuals also observed a decline, but smaller, in the incidence of PUD with an AAPC of -0.28 (95%CI -0.30 to -0.26; P< 0.001). Upon stratification by gender, statistically significant decrements in PUD incidence were noted in both males and females, with males having an AAPC of -1.02 (95%CI -1.04 to -1.00; P< 0.001) while females had an AAPC of -0.88 (95%CI -0.90 to -0.86; P< 0.001). Conclusion: Over the span of 3 decades, the incidence of PUD in Canada witnessed a significant decline across all age groups and in both men and women. These findings in Canada are consistent with other developed nations due to improved hygienic practices, and cautious use of NSAIDs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".