Ulcerative Colitis Patients With Clostridium difficile are at Increased Risk of Death, Colectomy, and Postoperative Complications: A Population-Based Inception Cohort Study
Bibliographic record
Abstract
OBJECTIVES: Clostridium difficile (C. difficile) may worsen the prognosis of ulcerative colitis (UC). The objectives of this study were to: (i) validate the International Classification of Diseases-10 (ICD-10) code for C. difficile; (ii) determine the risk of C. difficile infection after diagnosis of UC; (iii) evaluate the effect of C. difficile infection on the risk of colectomy; and (iv) assess the association between C. difficile and postoperative complications. METHODS: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated by comparing ICD-10 codes for C. difficile with stool toxin tests. A population-based surveillance cohort of newly diagnosed UC patients living in Alberta, Canada were identified from 2003 to 2009 (n=1,754). The effect of a C. difficile infection on colectomy was modeled using competing risk survival regression after adjusting for covariates. The effect of a C. difficile infection on postoperative complications was assessed using a mixed effects logistic regression model. RESULTS: The sensitivity, specificity, PPV, and NPV of the ICD-10 code for C. difficile were 82.1%, 99.4%, 88.4%, and 99.1%, respectively. The risk of C. difficile infection within 5 years of diagnosis with UC was 3.4% (95% confidence interval (CI): 2.5-4.6%). The risk of colectomy was higher among UC patients diagnosed with C. difficile (sub-hazard ratio (sHR)=2.36; 95% CI: 1.47-3.80). C. difficile increased the risk of postoperative complications (odds ratio=4.84; 95% CI: 1.28-18.35). C. difficile was associated with mortality (sHR=2.56 times; 95% CI: 1.28-5.10). CONCLUSIONS: C. difficile diagnosis worsens the prognosis of newly diagnosed patients with UC by increasing the risk of colectomy, postoperative complications, and death.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".