Patient-reported symptoms are a more reliable predictor of the societal burden compared to established physician-reported activity indices in inflammatory bowel disease: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: The societal burden of inflammatory bowel diseases (IBD) is not well documented, and further studies are needed to quantify the costs of the disease state. Thus, the aim was to estimate the societal burden and identify its predictors. METHODS: A cross-sectional questionnaire-based study complemented by objective data from patient medical records was performed for patients with Crohn's disease (CD) and ulcerative colitis (UC). RESULTS: We analyzed data from 161 patients (CD: 102, UC: 59). The overall work impairment reached 15.4%, 11.2% vs. 28.8% without/with self-reported symptoms (p = 0.006). Daily activity impairment was 19.3%, 14.1% vs. 35.6% (p < 0.001). The disability pension rate was 28%, 23% vs. 44% (p = 0.012). The total productivity loss due to absenteeism, presenteeism, and disability amounted to 7,673 €/patient/year, 6,018 vs. 12,354 €/patient/year (p = 0.000). Out-of-pocket costs amounted to 562 €/patient/year, 472 vs. 844 €/patient/year (p = 0.001). Self-reported symptoms were the strongest predictor of costs (p < 0.001). CONCLUSION: We found a high societal burden for IBD and a significant association between patient-reported disease symptoms and work disability, daily activity impairment, disability pensions, and out-of-pocket costs. Physician-reported disease activity is not a reliable predictor of costs except for out-of-pocket expenses.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".