Comparison of a Disease Activity Index and Patients’ Self-Reported Symptom Severity in Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND: A self-report instrument to measure disease activity in ulcerative colitis was compared with a full-scale measure of clinical and endoscopic activity, the St. Mark's index. We also tested the effects of symptom reporting style on both instruments. METHODS: Disease activity was measured in 94 patients with ulcerative colitis using the St. Mark's index and an instrument consisting of 7 self-reported symptoms. Reporting style was measured as health anxiety, measured with the Illness Behavior Questionnaire, and repressive coping, defined by scores on the Marlow-Crowne questionnaire and the State Anxiety Index. RESULTS: The St. Mark's index and the self-report index were highly correlated (R = 0.98, P < .001). Compared with the St. Mark's index, the self-report index categorized patients into inactive or active disease with a positive predictive value of 100% and negative predictive value of 100%. Reporting style was associated with differences in disease activity in both disease severity scales. CONCLUSIONS: A self-report measurement of ulcerative colitis disease activity is a valid alternative to complete clinical and endoscopic examination in subjects who do not have severe illness. Determination of disease severity in ulcerative colitis is vulnerable to individual biases in symptom reporting style, not only in self-report instruments, but also in an index that includes endoscopy and physical examination.
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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 | 0.009 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".