Bibliographic record
Abstract
Aim: A subset of functional dyspepsia patients respond to acid suppressive therapy, but the prevalence of non-erosive reflux disease in functional dyspepsia and its relevance to symptoms have never been established.The aim of the present study was to study 24 hour pH monitoring in consecutive functional dyspepsia patients.Methods: A total of 247 patients with dyspeptic symptoms (166 women, mean age 44 (SEM 1) year), with a negative upper gastrointestinal endoscopy and without dominant symptoms of heartburn participated in the study.In all patients, the severity of dyspeptic symptoms and the presence of heartburn was assessed by a questionnaire and a 24 hour oesophageal pH monitoring study was performed.All patients underwent a gastric emptying breath test and in 113 a gastric barostat study was performed.Results: Abnormal pH monitoring (acid exposure .5% of time) was found in 58 patients (23%).Of 21 patients with a positive heartburn questionnaire, 76% had pathological pH monitoring, while this was the case in only 18.5% of patients with a negative heartburn questionnaire.Demographic characteristics and the prevalence of other pathophysiological mechanisms did not differ between heartburn negative patients with normal or abnormal acid exposure.Pathological acid exposure in heartburn negative patients was associated with the presence of epigastric pain (65 v 84%, p,0.005) and of moderate or severe pain (48 v 69%, p = 0.005).Conclusion: Pathological oesophageal acid exposure is only present in a subset of heartburn negative functional dyspepsia patients, which are characterised by a higher prevalence of epigastric pain.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".