Regional outcomes of heart failure in Canada.
Bibliographic record
Abstract
BACKGROUND: Heart failure is a condition associated with significant mortality and morbidity. However, demographic features and outcomes following hospitalization for heart failure, and associated regional comparisons have not been performed in Canada. METHODS: Anonymously rendered records of patients hospitalized for incident heart failure in Canada were selected from the Canadian Institute for Health Information discharge abstract and hospital morbidity databases from fiscal years 1997/1998 to 1999/2000. The demographics, in-hospital mortality rate and heart failure readmission rates were compared among provinces and health regions. RESULTS: A total of 83,406 patients were hospitalized for heart failure across Canada during the study period. The number of cases increased dramatically with each decade after age 50 years, with 85% of hospitalized patients being age 65 years and over. On average, in-hospital mortality per index admission in Canada was 9.5 deaths per 100 hospitalized cases. While the greatest burden of readmissions was among those 65 years of age and over, heart failure readmission rates were similar across age groups. Among all patients surviving the index admission, heart failure readmission rates were 8.7%, 14.1% and 23.6% at 30 days, 90 days and one year, respectively. The highest age- and sex-adjusted in-hospital mortality rates were 11.9% (95% CI 10.6 to 13.2) in Newfoundland/Labrador and 11.6% (95% CI 10.6 to 12.7) in Nova Scotia. The highest readmission rates at one year were 26.9% (95% CI 24.9 to 28.9) in Newfoundland/Labrador, 26.3% (95% CI 25.0 to 27.7) in Saskatchewan and 25.2% (95% CI 24.3 to 26.1) in British Columbia. There were significant regional variations in heart failure readmission rates and mortality. CONCLUSIONS: There is a great burden of heart failure in Canada, increasing significantly with age. The mortality and readmission rates for this condition are high and exhibit variation among health regions and provinces. Factors contributing to regional variations in these outcomes merit further study.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".