Increasing rate of hospitalization for inflammatory bowel disease is an age-related effect: A Canadian Population Study
Bibliographic record
Abstract
INTRODUCTION: To understand trends in the risk of all-cause hospitalization for individuals with inflammatory bowel disease, we explored age, period, and cohort effects in Canada. METHODS: Repeated cross-sectional survey data from the 2005-2014 Canadian Community Health Survey linked to the Discharge Abstract Database to capture the all-cause hospitalization within 3 years of entry into the study for eligible individuals. Random-effects 2-level models estimated fixed effects for age and random effects for time periods and birth cohorts on the risk of all-cause hospitalization within 3 years entry into the study. RESULTS: An estimated 197,000 individuals were eligible for study inclusion. From this, an estimated 70,140 all-cause hospitalizations occurred within 3 years postentry into the study. The risk of hospitalization within 3 years increased with age and across birth cohorts, with older cohorts experiencing greater risks of hospitalization. A small temporal effect was identified for both inflammatory bowel disease groups. Within birth cohorts, the risk of hospitalization increased across ages for Crohn's disease, but in individuals with ulcerative colitis, the risk decreased across ages, except for the 2 oldest birth cohorts. DISCUSSION: These data support the hypothesis that age effects are primarily responsible for increased risk of hospitalizations. As the prevalence of IBD continues to rise and age distribution of Canadians shifts toward an older-aged population, increasing the allocation of healthcare resources to prevent age-related risks of hospitalizations would be beneficial to reduce hospital burdens.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".