Validity of the Leading Causes of Death Classification for Premature Mortality in Inflammatory Bowel Disease: A Population-Based Comparison with ICD-10 Coding in Ontario, Canada
Bibliographic record
Abstract
Introduction: Studying patterns of death, particularly premature deaths (<75 years), provides insights to address health inequities among those living. Multiple coding systems for cause of death (COD) exist. The Leading Causes of Death (LCD) scheme is designed for identifying priority COD for interventions in global populations. The extent to which such classification is effective for identifying priority causes of premature mortality among subpopulations with chronic health conditions, such as inflammatory bowel disease (IBD), is unknown. Objective: To evaluate the usability of the LCD for characterizing premature mortality among those with IBD. Methods: We conducted a population-based matched case control study of persons with IBD who died between 2010 and 2018 using linked health administrative data from Ontario, Canada. Individuals with IBD were matched with five decedents without IBD based on sex and years of birth and death. We compared COD for premature and overall mortality using two classification structures: the LCD scheme and the International Statistical Classification of Diseases and Related Health Problems, tenth revision (ICD-10) chapters. Results: Among 7,919 decedents with IBD (39,414 matched controls), 47% died prematurely. With the LCD framework, COD differences for premature mortality were not detectable as 29% were allocated to the residual category (Standardized differences [SD]: 18%). Most residual deaths were due to neoplasms (34%) or diseases of the gastrointestinal system (32%). Using ICD-10 chapters, premature deaths were more commonly due to diseases of the digestive system than for matched controls (13% vs 5%, SD: 31%). Discussion: The LCD coding scheme provides more granular COD details compared to the ICD-10 chapters. However, a larger proportion of deaths among people with IBD were allocated to the residual category, limiting its utility for enabling healthcare systems to identify priority targets to reduce premature mortality. Further work to develop and validate a framework for premature COD classification in populations with IBD is needed.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| 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".