Impact of <i>Clostridium difficile</i> colitis on 5‐year health outcomes in patients with ulcerative colitis
Bibliographic record
Abstract
BACKGROUND: Clostridium difficile colitis (CDC) is associated with an increased short-term mortality risk in hospitalised ulcerative colitis (UC) patients. We sought to determine whether CDC also impacts long-term risks of adverse health events in this population. AIM: To determine whether CDC also impacts long-term risks of adverse health events in this population. METHODS: A population-based retrospective cohort study was conducted of UC patients hospitalised in Ontario, Canada between 2002 and 2008. Patients with and without CDC were compared on the rates of adverse health events. The primary outcomes were the 5-year adjusted risks of colectomy and death. RESULTS: Among 181 patients with CDC and 1835 patients without CDC, the 5-year cumulative colectomy rates were 44% and 33% (P = 0.0052) and the 5-year cumulative mortality rates were 27% and 14% (P < 0.0001) respectively. CDC was associated with a higher adjusted 5-year risk of mortality [adjusted hazard ratio (aHR) 2.40, 95% CI 1.37-4.20], but not of colectomy (aHR 1.18, 95% CI 0.90-1.54). CDC impacted mortality risk both during index hospitalisation (adjusted odds ratio 8.90, 95% CI 2.80-28.3) as well as over 5 years following hospital discharge among patients who recovered from their acute illness (aHR 2.41, 95% CI 1.37-4.22). Colectomy risk was not influenced by CDC in this cohort. CONCLUSION: Clostridium difficile colitis is associated with increased short-term and long-term mortality risks among hospitalised ulcerative colitis patients. As colectomy risk is not similarly impacted by Clostridium difficile colitis, factors predictive of death among C. difficile-infected ulcerative colitis patients require elucidation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".