Health care and outcomes in persons with obesity in Canada; an analysis of Canadian Institute for Health Information data 2018-2022
Bibliographic record
Abstract
Overweight and obesity are associated with physical, functional, and mental health risks across the continuum of care. The purpose of this thesis was to quantify the ICD-10 code use for overweight and obesity (E66) in healthcare settings across Canada, and explore patient care of persons with obesity within emergency departments in Ontario. This study utilized data from the Canadian Institute for Health Information Discharge Abstract Database and National Ambulatory Care Reporting System from April 1, 2018 to March 31, 2022. Regional variations in E66 use were observed, where the highest rates of coding were seen in Manitoba, and the lowest rates in British Columbia (2018-2019) and PEI (2020-2021). Ontario was the only province to show an increase in E66 coding over time. Compared to controls matched for age, sex, and main diagnosis, patients with an E66 code had higher average length of stay, longer wait time for physician initial assessment, and higher triage scores.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.020 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".