Correlation Between Symptom Severity and Health-Related Life Quality of a Population With Gastroesophageal Reflux Disease
Bibliographic record
Abstract
BACKGROUND: Gastroesophageal reflux disease (GERD) is a chronic disease with a negative impact on the quality of life. The aim of this study was to investigate the reflux symptoms and the health-related quality of life in a population with GERD. METHODS: Data from patients with GERD, according to the Montreal definition, were collected between January and December 2009. The enrolled patients were classified by different reflux symptoms according to the modified Chinese GERDQ. The general demographic data, the modified GERD impact scores and the SF-36 questionnaire scores of these groups of patients were analyzed. RESULTS: A total of 173 patients were enrolled, and the general data, endoscopic findings and lifestyle habits of the participants with different severity of heartburn or regurgitation were all similar. The patients with moderate severity of reflux symptoms had significant lower SF-36 scores than those with mild severity. The cases with advanced heartburn severity owned the lowest scores among all cases. The impact on the daily activity of each affected individual had a positive association with the stronger severity of reflux symptom. CONCLUSION: The life quality of a population with GERD achieved the meaningful declination in participants with the moderate severity of heartburn or regurgitation. The severity of the reflux symptoms had a greater impact on the normal daily activity of the patients with GERD. The cases with advanced severity of heartburn had the worst well-being.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".