Longitudinal Assessment of Patient-reported Outcome Measures in Systemic Sclerosis Patients with Gastroesophageal Reflux Disease — Scleroderma Clinical Trials Consortium
Bibliographic record
Abstract
OBJECTIVE: Validated gastrointestinal (GI) symptoms scales are used in clinical practice to assess patient-reported GI involvement. We sought to determine whether University of California, Los Angeles (UCLA) GI Tract Questionnaire (GIT) 2.0 Reflux scale, Patient-Reported Outcomes Measurement Information System (PROMIS) Reflux scale, and the Quality of Life in Reflux and Dyspepsia questionnaire (QOLRAD) are sensitive to identifying changes in GI symptoms following therapeutic intervention in participants with systemic sclerosis (SSc) and gastroesophageal reflux disease (GERD). METHODS: Participants with active GERD were recruited during clinical visits at 6 international SSc centers. Patient-reported outcome surveys and the GI self-reported questionnaire were completed at baseline and again at 4 weeks following a single intervention, and patients were classified as "improved" or "not improved." Effect size (ES) was calculated to assess the sensitivity to change. ES was interpreted as 0.50-0.79 as moderate effect and ≥ 0.80 as large effect. RESULTS: There were 116 participants with SSc and active GERD who enrolled. The average age was 53.8 years and mean disease duration was 12.0 years. The UCLA GIT 2.0 Reflux scale and PROMIS Reflux scale had a significant correlation at baseline (0.61, p < 0.0001), and both instruments correlated with the QOLRAD domains (-0.56 to -0.71). In participants who had the UCLA GIT 2.0, PROMIS Reflux scale, and QOLRAD administered over 2 timepoints (n = 57) and were classified as improved, the ES was large for the UCLA GIT 2.0 and PROMIS Reflux scale, and moderate to large across all QOLRAD domains. CONCLUSION: The UCLA GIT 2.0 Reflux scale, PROMIS Reflux scale, and QOLRAD are sensitive to change and can be included in future clinical trials.
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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 | 0.059 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".