Endoscopic pH Monitoring for Patients with Suspected or Refractory Gastroesophageal Reflux Disease
Bibliographic record
Abstract
BACKGROUND: Wireless pH studies can offer prolonged pH monitoring, which may potentially facilitate the diagnosis and management of patients with gastroesophageal reflux disease (GERD). The aim of the present study was to evaluate the detection rate of abnormal esophageal acid exposure using prolonged pH monitoring in patients with suspected or refractory GERD symptoms. METHODS: Patients undergoing prolonged ambulatory pH studies for the evaluation of GERD-related symptoms were assessed. Patients with a known diagnosis of GERD were tested on medical therapy, while patients with suspected GERD were tested off therapy. The wireless pH capsules were placed during upper endoscopy 6 cm above the squamocolumnar junction. RESULTS: One hundred ninety-one patients underwent a total of 198 pH studies. Fifty ambulatory pH studies (25%) were excluded from the analysis: 27 patients (14%) had insufficient data capture (less than 18 h on at least one day of monitoring), 15 patients had premature capsule release (7%), seven were repeat studies (3.5%) and one had intolerable pain requiring capsule removal (0.5%). There were 115 patients undergoing pH studies who were off medication, and 33 patients were on therapy. For the two groups of patients, results were as follows: 32 (28%) and 22 (67%) patients with normal studies on both days; 58 (50%) and five (15%) patients with abnormal studies on both days; 18 (16%) and three (9%) patients with abnormal studies on day 1 only; and seven (6%) and three (9%) patients with abnormal studies on day 2 only, respectively. CONCLUSIONS: Prolonged 48 h pH monitoring can detect more abnormal esophageal acid exposure but is associated with a significant rate of incomplete studies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".