Anxiety But Not Depression Predicts Poor Outcomes in Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Patients with inflammatory bowel disease (IBD) have high rates of psychiatric comorbidities, but it is not clear whether those with comorbidities are at higher risk of poor outcomes. We aimed to determine whether patients with IBD who have co-existing anxiety and/or depression are more likely to have poor IBD-related outcomes compared with IBD patients without anxiety and/or depression. METHODS: This was a prospective longitudinal follow-up study in Ontario, Canada, from 2008 to 2016. Patients were asked to complete questionnaires at the time of initial assessment, including the Hospital Anxiety and Depression Scale (HADS). We selected a number of clinical variables at the time of presentation and tested their ability to predict subsequent poor IBD-related outcomes, such as IBD-related hospitalization, emergency room visits, and recurrent courses of corticosteroids over the duration of follow-up. Logistic regression was used for multivariate analysis. RESULTS: Four hundred fourteen IBD patients completed the baseline questionnaire. Among them, 125 had anxiety and/or depression at baseline. Factors that predicted poor IBD-related outcomes during longitudinal follow-up included increased severity of disease at initial presentation, prior IBD-related surgery, longer duration of follow-up, and elevated C-reactive protein at time of initial presentation. After adjustment for potential covariates, IBD patients with abnormal anxiety subscores had poor IBD-related outcomes compared with those without elevated anxiety subscores (odds ratio [OR] 3.36, 95% CI, 1.51-7.48). No difference in IBD-related outcomes were observed in those with abnormal depression subscores compared with those without elevated depression scores (OR 0.43, 95% CI, 0.14-1.32). CONCLUSIONS: Severe disease, anxiety, and previous IBD-related surgery predict poor IBD-related outcomes in patients in the future. Closer monitoring with regular follow-up may be appropriate for patients with these risk factors.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".