Impact of body mass index and gender on quality of life in patients with gastroesophageal reflux disease
Bibliographic record
Abstract
AIM: To investigate the symptom presentation and quality of life in obese Chinese patients with gastroesophageal reflux disease (GERD). METHODS: Data from patients diagnosed with GERD according to the Montreal definition, were collected between January 2009 to March 2010. The enrolled patients were assigned to the normal [body mass index (BMI) < 25 kg/m(2)], overweight (25-30 kg/m(2)), and obese (BMI > 30 kg/m(2)) groups. General demographic data, endoscopic findings, and quality of life of the three groups of patients were analyzed and compared. RESULTS: Among the 173 enrolled patients, 102, 56 and 15 patients were classified in the normal, overweight, and obese, respectively. There was significantly more erosive esophagitis (73.3% vs 64.3% vs 39.2%, P = 0.002), hiatal hernia (60% vs 33.9% vs 16.7%, P = 0.001), and males (73.3% vs 73.2% vs 32.4%, P = 0.001) in the obese cases. The severity and frequency of heartburn, not acid regurgitation, was positively correlated with BMI, with a significant association in men, but not in women. Obese patients were prone to have low quality of life scores, with obese women having the lowest scores for mental health. CONCLUSION: In patients with GERD, obese men had the most severe endoscopic and clinical presentation. Obese women had the poorest mental health.
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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 | 0.001 |
| 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 | 0.000 |
| 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".