Dyspepsia and IBS Symptoms in Patients with NERD, ERD and Barrett’s Esophagus
Bibliographic record
Abstract
INTRODUCTION: Irritable bowel syndrome (IBS) and functional dyspepsia (FD) are highly prevalent in the general population as does gastroesophageal reflux disease (GERD). Therefore, it is expected that these conditions may frequently overlap. OBJECTIVE: We aimed at evaluating the presence ofFD and IBS symptoms in patients with erosive (ERD), non-erosive reflux disease (NERD) and Barrett's esophagus (BE). PATIENTS AND METHODS: 71 patients presenting at the reflux disease outpatient clinic were prospectively included in this study. 33 patients had NERD, 25 ERD and 13 BE according to the Montreal classification. All patients with ERD and NERD had typical reflux symptoms, as assessed by a validated GERD questionnaire (RDQ). The diagnosis of functional dyspepsia and IBS symptoms was assessed according to the Rome III criteria. RESULTS: IBS symptoms (bloating, abdominal pain, constipation and diarrhea) were slightly more prevalent in NERD (54.6, 63.6, 21.20, 24.2%, respectively) than in ERD (48.0, 44.0, 12.0, 20.0%, respectively) and in BE (53.9, 23.10, 15,4, 23.1%, respectively), but none of these differences reached statistical significance. NERD patients had more FD symptoms than patients with ERD or BE, but again this difference did not reach statistical significance. CONCLUSION: Our data show that IBS and FD are common in the entire spectrum of GERD. The presence of these disorders might explain why many patients with GERD are deemed as treatment failures if they have no complete symptom relief with proton pump inhibitors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".