Characterization of Inflammatory Bowel Disease in Hospitalized Elderly Patients in a Large Central Canadian Health Region
Bibliographic record
Abstract
OBJECTIVE: To determine differences in phenotype and treatment among hospitalized elderly and young patients with inflammatory bowel disease (IBD), and the utility of International Classification of Diseases, 10th Revision (ICD)-10 codes in hospital discharge abstracts in diagnosing IBD in elderly patients. METHODS: A large Canadian health region hospitalization discharge database was used to identify elderly (>65 years of age) and young (19 to 50 years of age) patients with IBD admitted between April 1, 2007 and March 31, 2012, and a random sample of elderly patients with other colonic conditions. Medical records were reviewed to confirm IBD diagnosis and extract clinical information. The characteristics of elderly versus young hospitalized IBD patients and accuracy of ICD-10 IBD discharge codes in the elderly were assessed. RESULTS: One hundred forty-three elderly and 82 young patients with an IBD discharge diagnosis, and 135 elderly patients with other gastrointestinal discharge diagnoses were included. Elderly IBD patients were less likely to have ileocolonic Crohn disease (21.4% versus 50.9%; P=0.001), more likely to be prescribed 5-aminosalicylates (61% versus 43%; P=0.04), and less likely to be prescribed biologics (6% versus 21%; P=0.016) or immunomodulators (21% versus 42%; P=0.01). The sensitivity, specificity and positive predictive value of a single ICD code for CD were 98%, 96% and 94%, respectively, and for ulcerative colitis (UC) were 98%, 92% and 70%, respectively. CONCLUSIONS: Treatment approaches in elderly patients were different than in younger IBD patients despite having disease sufficiently severe to require hospitalization. While less accurate in UC, a single ICD-10 IBD code was sufficient to identify elderly CD and UC hospitalized patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".