Predictors of treatment response in patients with non‐erosive reflux disease
Bibliographic record
Abstract
BACKGROUND: Up to 40% of patients with non-erosive reflux disease (NERD) fail to respond to proton pump inhibitor therapy. AIM: To determine useful prognostic factors for response to and suppression in NERD. METHODS: A pooled analysis from three multicentre, double-blind trials of patients with a normal endoscopy and heartburn for 4 days or more during the 7 days prior to the start of each treatment. Patients received omeprazole 20 mg, esomeprazole 20 mg or esomeprazole 40 mg/day for 4 weeks. Complete resolution of heartburn was defined as no heartburn during the last week. RESULTS: Of 2458 patients included, complete heartburn resolution was achieved in 63% at the end of 4 weeks treatment. Response on days 5-7 provided an 85% probability of complete resolution of heartburn at 4 weeks; the probability of complete heartburn resolution at 4 weeks in those with moderate to severe symptoms on days 5-7 was 22%. Sensitivity and specificity of no heartburn on days 5-7 was 55% and 83% respectively. Patient demographics, duration of symptoms, medications used, other symptoms and body mass index were not predictors. CONCLUSION: Assessment of heartburn resolution during the first week of therapy was the best predictor of treatment success at 4 weeks in non-erosive reflux disease, but was suboptimal as a test.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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 | 0.001 | 0.001 |
| 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".