The impact of intensifying acid suppression on sleep disturbance related to gastro‐oesophageal reflux disease in primary care
Bibliographic record
Abstract
BACKGROUND: Sleep disturbance is common in patients with GERD but there has been little evaluation of this problem in primary care in patients already taking therapy. AIM: To evaluate the impact of administering a questionnaire (PASS test) to identify patients with sleep problems and evaluate the efficacy of esomeprazole to improve sleep disturbance in patients with GERD. METHODS: This was a primary care based cluster-randomised, open-label study where practices were assigned to intervention or control groups. PASS test failures continued current therapy (control) or were switched to 4 weeks' once-daily esomeprazole 20 or 40 mg (intervention). Patients were evaluated at the end of 4 weeks and the outcomes that were assessed were the sleep questions from the Quality of Life in Reflux and Dyspepsia (QOLRAD) questionnaire and the presence or absence of sleep disturbance from the PASS test questionnaire. RESULTS: A total of 1388 patients with evaluable data at 4 weeks were included in the analysis and 825 reported GERD-related sleep disturbance at baseline. At 4 weeks, 161 of 291 of control patients (55%) reported continued sleep disturbance compared to 120 of 534 (22.5%) of intervention patients [number needed to treat of 3: 95% confidence intervals (CI): 2.5-4]. There was a mean improvement in QOLRAD scores related to sleep in the intervention patients compared to control patients (mean improvement = 4.91; 95% CI: 3.73-6.09). CONCLUSION: A PASS strategy identifies GERD patients with sleep disturbance in primary care that will benefit from a change in acid-suppressive therapy. ClinicalTrials.gov identifier: NCT00392002; study code: D9612L00096.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".