UCLA Scleroderma Clinical Trials Consortium Gastrointestinal Tract (GIT) 2.0 Reflux Scale Correlates With Impaired Esophageal Scintigraphy Findings in Systemic Sclerosis
Bibliographic record
Abstract
Objective The University of California Los Angeles Scleroderma Clinical Trials Consortium Gastrointestinal Tract 2.0 (GIT 2.0) instrument is a self-report tool measuring gastrointestinal (GI) quality of life in patients with systemic sclerosis (SSc). Scarce data are available on the correlation between patient-reported GI symptoms and motility dysfunction as assessed by esophageal transit scintigraphy (ETS). Methods We evaluated the GIT 2.0 reflux scale in patients with SSc admitted to our clinic and undergoing ETS, and correlated their findings. Results Thirty-one patients with SSc undergoing ETS were included. Twenty-seven were female, and 9 had diffuse cutaneous SSc. Twenty-six of 31 (84%) patients had a delayed transit and an abnormal esophageal emptying activity (EA); they also had a higher GIT 2.0 reflux score (P = 0.04). Mean EA percentage was higher in patients with none to mild GIT 2.0 reflux score (81.1 [SD 11.5]) than in those with moderate (55.7 [SD 17.8], P = 0.003) and severe to very severe scores (55.8 [SD 19.7], P = 0.002). The percentage of esophageal EA negatively correlated with the GIT 2.0 reflux score (r = –0.68, P < 0.0001), but it did not correlate with the other GIT 2.0 scales and the total GIT 2.0 score. Conclusion SSc patients with impaired ETS findings have a higher GIT 2.0 reflux score. The GIT 2.0 is a complementary tool for objective measurement of esophageal involvement that can be easily administered in day-to-day clinical assessment.
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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 | 0.003 | 0.011 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".