Abstract P264: Cardiovascular and Cardiometabolic Post-hospitalization Mortality Rates are Not Associated With Traditional Risk Factors and Socioeconomic Status at the Population Level in Canada
Bibliographic record
Abstract
Background: While existing literature has established individual risk factors for early death post-hospitalization in patients with cardiovascular and cardiometabolic disease (CVD/CMD), few studies to date have examined whether the known effects of these risk factors are maintained at the population level. The aim of this study was to determine whether traditional CVD risk factors and socioeconomic factors at the population level impacted CVD/CMD post-hospitalization mortality rates in Canada over time. Methodology: We conducted an ecological, cross-sectional analysis using merged data from two sources: 1) the Canadian Community Health Survey 2000-2011 and, 2) the Canadian Vital Statistics Death Database linked to the Discharge Abstract Database 2000-2012. The study outcome was 1-year mortality rate after hospital discharge for CVD/CMD, calculated by census division (CD) using ICD-9-CA codes for hospitalizations and deaths. The first stage of the statistical analysis reported age- and sex-standardized 1-year mortality rates after hospital discharge for CVD/CMD, across CDs in Canada. The second stage utilized Poisson regression to model associations between traditional CVD risk factors and socioeconomic factors at the CD level and CVD/CMD post-hospitalization mortality rates in Canada over time. Results: National 1-year mortality rates in patients with CVD/CMD increased from 146.5 per 100,000 in 2000 to 150.4 in 2012, peaking at 202.4 in 2006, with no significant trend observed over time. Maps of average 1-year mortality rates over the time period (2000-2012) show wide variations in rates across census divisions (CDs) in Canada. Nova Scotia and Ontario had the highest proportion of CDs with worsening rates of mortality over time (3% and 7% respectively) that remained below the national average. Traditional CVD risk factors, demographic factors and socioeconomic factors at the census division level were not associated with 1-year mortality rates after hospital discharge for CVD/CMD over time. Potential implication: Reductions in the CVD/CMD post-hospitalization mortality burden at the individual level may benefit from treatment targeted towards traditional risk factors and socioeconomic factors however; reduction in post-hospitalization burden at the population level can benefit from policy focused towards other societal elements such as healthcare and community care resources.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".