Determinants of the Association between Non-Cardiac Chest Pain and Reflux
Bibliographic record
Abstract
OBJECTIVES: Gastroesophageal reflux is considered to be the most common gastrointestinal cause of non-cardiac chest pain (NCCP). It remains unclear why some reflux episodes in the same patient cause chest pain while others do not. To understand more about the mechanisms by which reflux elicits chest pain, we aimed to identify factors which are important in triggering chest pain. METHODS: In this multicenter study, 120 patients with NCCP were analyzed using 24-h pH-impedance monitoring. In the patients with a positive association between reflux and chest pain, the characteristics of the reflux episodes which were followed by a chest pain episode were compared with chest pain-free reflux episodes. RESULTS: Using 24-h pH-impedance monitoring, 40% of the NCCP patients were identified as having reflux as a possible cause of their chest pain. Reflux episodes that were associated with chest pain had a higher proximal extent (P=0.007), a higher volume clearance time (P=0.030), a higher 15-minute acid burden (P=0.041), were more often acidic (P=0.011), had a lower nadir pH (P=0.044), and had a longer acid duration time (P=0.027) than reflux episodes which were not followed by chest pain. Patients who experienced typical reflux symptoms were more likely to have reflux as the cause of their chest pain (52 vs. 31.4%, P=0.023). CONCLUSIONS: The presence of a larger volume of acid refluxate for a longer period of time appears to be an important determinant of perceiving a reflux episode as chest pain. 24-h pH-impedance monitoring is an important tool in identifying gastroesophageal reflux as a potential cause of symptoms in patients with NCCP.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".