Prevalence and incidence of gastroduodenal ulcers during treatment with vascular protective doses of aspirin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Aspirin is valuable for preventing vascular events, but information about ulcer frequency is necessary to inform risk-benefit decisions in individual patients. AIM: To determine ulcer prevalence and incidence in a population representative of those given aspirin therapy and evaluate risk predictors. METHODS: Patients taking aspirin 75-325 mg daily were recruited from four countries. Exclusions included use of gastroprotectant drugs or other non-steroidal anti-inflammatory drugs. We measured point prevalence of endoscopic ulcers, after quantitating dyspeptic symptoms. Incidence was assessed 3 months later in those eligible to continue (no baseline ulcer or reason for gastroprotectants). RESULTS: In 187 patients, ulcer prevalence was 11% [95% confidence interval (CI) 6.3-15.1%]. Only 20% had dyspeptic symptoms, not significantly different from patients without ulcer. Ulcer incidence in 113 patients followed for 3 months was 7% (95% CI 2.4-11.8%). Helicobacter pylori infection increased the risk of a duodenal ulcer [odds ratio (OR) 18.5, 95% CI 2.3-149.4], as did age >70 for ulcers in stomach and duodenum combined (OR 3.3, 95% CI 1.3-8.7). CONCLUSIONS: Gastroduodenal ulcers are found in one in 10 patients taking low-dose aspirin, and most are asymptomatic; this needs considering when discussing risks/benefits with patients. Risk factors include older age and H. pylori (for duodenal ulcer).
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it