Effect of Diaphragmatic Breathing Training on the Esophagogastric Junction and Esophageal Motility in Patients With Reflux Symptoms
Bibliographic record
Abstract
BACKGROUND: Diaphragmatic breathing training (DBT) improves symptoms in patients with gastroesophageal reflux disease; however, the effect of DBT on the anti-reflux barrier and esophageal motility is unclear. This study aimed to evaluate the changes in specific parameters of EGJ function and esophageal motility before and after DBT using high-resolution manometry (HRM) in patients with reflux symptoms. METHODS: Prospectively collected data from adult patients with persistent reflux symptoms who underwent initial and follow-up HRM after at least 3 months of DBT were analyzed. Esophagogastric junction (EGJ) function was assessed using basal lower esophageal sphincter (LES) pressure (LESP), the EGJ contractile integral (EGJ-CI), and integrated relaxation pressure (IRP). Esophageal motility was assessed using the distal contractile integral (DCI) and percentage of ineffective esophageal motility (IEM). KEY RESULTS: Data from 53 patients with a median age of 45 years (range 25-77) were analyzed. LES pressure increased after DBT (mean LES pressure 25.6 [SE 1.3] vs. 29.1 [SE 1.4] mmHg after DBT; p = 0.02). This effect was also observed in patients with an initially hypotensive LES, but no effect was found on the size of hiatus hernia. There was a trend to increased EGJ-CI (mean EGJ-CI 52.8 [SE 3.7] vs. 59.9 [SE 4.3] mmHg·cm after DBT, p = 0.07). Esophageal contractility improved (mean DCI 1046.6 [SE 112] vs. 1264.1 [SE 137] mmHg·s·cm after DBT; p < 0.01) with the prevalence of IEM reduced from 38.0% [SE 5] to 29.2% [SE 4] after DBT; p = 0.03. CONCLUSION AND INFERENCES: Diaphragmatic breathing training increased LES pressure and esophageal peristaltic vigor in patients with reflux symptoms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".