Clinical trial: factors associated with freedom from relapse of heartburn in patients with healed reflux oesophagitis ‐ results from the maintenance phase of the EXPO study
Bibliographic record
Abstract
BACKGROUND: Ability to predict freedom from heartburn relapse during maintenance therapy for healed reflux oesophagitis may facilitate optimal treatment choices for individual patients. AIM: To determine factors predicting freedom from heartburn relapse during maintenance proton pump inhibitor therapy in patients with healed reflux oesophagitis. METHODS: This post-hoc analysis used data from the maintenance phase of the EXPO study (AstraZeneca study code: SH-NEG-0008); 2766 patients with healed reflux oesophagitis and resolved heartburn received once-daily esomeprazole 20 mg or pantoprazole 20 mg for 6 months. Multiple logistic regression analysis determined factors associated with freedom from heartburn relapse. RESULTS: Heartburn relapse rates were lower with esomeprazole than pantoprazole in all subgroups analysed. Esomeprazole treatment was the factor most strongly associated with freedom from heartburn relapse (odds ratio 2.08; P < 0.0001). Other factors significantly associated with freedom from heartburn relapse were Helicobacter pylori infection, greater age, non-obesity, absence of epigastric pain at baseline, pre-treatment nonsevere heartburn and GERD symptom duration < or =5 years. CONCLUSIONS: Several factors predict freedom from heartburn relapse during maintenance proton pump inhibitor therapy for healed reflux oesophagitis, the strongest being choice of proton pump inhibitor. These findings outline the importance of optimizing acid control and identifying predictors of relapse for effective long-term symptom management in reflux oesophagitis patients.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".