The 2023 Impact of Inflammatory Bowel Disease in Canada: Special Populations—IBD in Seniors
Bibliographic record
Abstract
Approximately one out of every 88 seniors has inflammatory bowel disease (IBD), and this is expected to increase in the future. They are more likely to have left-sided disease in ulcerative colitis, and isolated colonic disease in Crohn's disease; perianal disease is less common. Other common diagnoses in the elderly must also be considered when they initially present to a healthcare provider. Treatment of the elderly is similar to younger persons with IBD, though considerations of the increased risk of infections and malignancy must be considered when using immune modulating drugs. Whether anti-TNF therapies increase the risk of infections is not definitive, though newer biologics, including vedolizumab and ustekinumab, are thought to be safer with lower risk of adverse events. Polypharmacy and frailty are other considerations in the elderly when choosing a treatment, as frailty is associated with worse outcomes. Costs for IBD-related hospitalizations are higher in the elderly compared with younger persons. When elderly persons with IBD are cared for by a gastroenterologist, their outcomes tend to be better. However, as elderly persons with IBD continue to age, they may not have access to the same care as younger people with IBD due to deficiencies in their ability to use or access technology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".