Predicting relapse in Crohn’s disease: a biopsychosocial model
Bibliographic record
Abstract
BACKGROUND: Crohn's disease (CD) is a chronic relapsing inflammatory bowel disorder. Both biological and psychosocial factors may modulate the illness experience. AIM: The aim of this study was to identify clinical, biological and psychosocial parameters as predictors of clinical relapse in quiescent CD. METHODS: Patients in medically induced remission were followed prospectively for 1 year, or less if they relapsed. Disease characteristics were determined at baseline. Serum cytokines, anti-Saccharomyces cerevisiae antibodies, C-reactive protein (CRP), erythrocyte sedimentation rate and intestinal permeability were measured every 3 months. Psychological distress, perceived stress, minor life stressors and coping strategies were measured monthly. A time-dependent multivariate Cox regression model determined predictors of time to relapse. RESULTS: 101 patients (60 females, 41 males) were recruited. Fourteen withdrew and 37 relapsed. CRP (HR = 1.5 per 10 mg/l, 95% CI 1.1 to 1.9, p = 0.007), fistulising disease (HR = 3.2, 95% CI, 1.1 to 9.4, p = 0.04), colitis (HR = 3.5 95% CI 1.2 to 9.9, p = 0.02) and the interaction between perceived stress and avoidance coping (HR = 7.0 per 5 unit increase for both scales, 95% CI 2.3 to 21.8, p = 0.003) were predictors of earlier relapse. CONCLUSIONS: In quiescent CD, a higher CRP, fistulising disease behaviour and disease confined to the colon were independent predictors of relapse. Moreover, patients under conditions of low stress and who scored low on avoidance coping (ie, did not engage in social diversion or distraction) were least likely to relapse. This study supports a biopsychosocial model of CD exacerbation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".