One-Year Costs Associated with Hospitalizations Due to Aortic Stenosis in Canada
Bibliographic record
Abstract
BACKGROUND: There is a lack of data on the burden of patients hospitalized with aortic stenosis (AS) in Canada. The primary study objective was to document the index and 1-year costs of hospitalized patients with AS in Canada. Secondary objectives were to explore results by treatment modality and Canadian provinces. METHODS: Hospitalized patients with a most responsible diagnosis (MRD) of AS during fiscal year 2014/2015 were identified using Canadian administrative databases. Costs were calculated for the index admission and for up to 1 year. For our secondary analyses, patients were classified according to the intervention received: surgical aortic valve replacement (SAVR), SAVR with coronary artery bypass graft, or transfemoral or transapical transcatheter aortic valve implantation. Hospitalized AS patients who did not undergo SAVR or transcatheter aortic valve implantation were classified as the untreated group. The data were also analyzed by Canadian provinces. RESULTS: During fiscal year 2014/15, a total of 7217 Canadians were hospitalized with an MRD of AS. The mean (standard deviation) age of our population was 74.2 (11.5) years, and 39% were female. The 1-year hospital costs associated with an MRD of AS in Canada were calculated at $393 million. Our secondary analyses suggest that patient demographics (mean age ranging from 69 to 82 years) and outcomes (median length of stay ranging from 6 to 12 days) differ among treatment modalities and Canadian provinces. CONCLUSIONS: AS hospitalizations result in a significant cost burden in Canada. Future research is needed to better understand variation among treatment modalities and Canadian provinces.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 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".