Heartburn and regurgitation have different impacts on life quality of patients with gastroesophageal reflux disease
Bibliographic record
Abstract
AIM: To investigate the impact of heartburn and regurgitation on the quality of life among patients with gastroesophageal reflux disease (GERD). METHODS: Data from patients with GERD, who were diagnosed according to the Montreal definition, were collected between January 2009 and July 2010. The enrolled patients were assigned to a heartburn or a regurgitation group, and further assigned to an erosive esophagitis (EE) or a non-erosive reflux disease (NERD) subgroup, depending on the predominant symptoms and endoscopic findings, respectively. The general demographic data, the scores of the modified Chinese version of the GERDQ and the Short-form 36 (SF-36) questionnaire scores of these groups of patients were compared. RESULTS: About 108 patients were classified in the heartburn group and 124 in the regurgitation group. The basic characteristics of the two groups were similar, except for male predominance in the regurgitation group. Patients in the heartburn group had more sleep interruptions (22.3% daily vs 4.8% daily, P = 0.021), more eating or drinking problems (27.8% daily vs 9.7% daily, P = 0.008), more work interferences (11.2% daily vs none, P = 0.011), and lower SF-36 scores (57.68 vs 64.69, P = 0.042), than patients in the regurgitation group did. Individuals with NERD in the regurgitation group had more impaired daily activities than those with EE did. CONCLUSION: GERD patients with heartburn or regurgitation predominant had similar demographics, but those with heartburn predominant had more severely impaired daily activities and lower general health scores. The NERD cases had more severely impaired daily activity and lower scores than the EE ones did.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".