Generation of dyspeptic symptoms by direct acid infusion into the stomach of healthy Japanese subjects
Bibliographic record
Abstract
OBJECTIVE: The relationship between acid and dyspeptic symptoms has not been fully understood. AIM: To investigate the type and severity of dyspeptic symptoms induced by direct acid infusion into the stomach of Japanese healthy subjects. METHODS: This was a multi-centre, cross-over, randomized, double-blind study in 27 healthy subjects (mean age 27). Each fasted subject received two tests with 150 mL of 0.1 mol/L hydrochloric acid infusion (15 mL/min for 10 min) and the same volume of pure water infusion. The type and severity of symptoms were assessed by a 10 cm visual analogue scale administered every 2 min up to 30 min. RESULTS: Various symptoms were reported after both acid and water infusions. Most of the symptoms were more severe after acid infusion compared with water infusion (acid vs. water: discomfort 1.8 +/- 0.4 vs. 0.5 +/- 0.1, pain 0.6 +/- 0.3 vs. 0.1 +/- 0.1, reflux 1.0 +/- 0.3 vs. 0.3 +/- 0.1 and satiety 1.1 +/- 0.4 vs. 0.2 +/- 0.1). The area under curve for dysmotility like symptoms (heavy feeling in the stomach, bloating, nausea or feeling sick, and belching) was significantly higher in acid infusion, and symptoms continued after infusion of the acid. CONCLUSION: Acid induced into stomach induced dysmotility-like predominant dyspeptic symptoms in Japanese healthy control subjects, demonstrating the possible importance of acid in symptom generation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| 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".