Spatial variation in the management and outcomes of acute coronary syndrome
Bibliographic record
Abstract
Regional disparities in medical care and outcomes with patients suffering from an acute coronary syndrome (ACS) have been reported and raise the need to a better understanding of links between treatment, care and outcomes. Little is known about the relationship and its spatial variability between invasive cardiac procedure (ICP), hospital death (HD), length of stay (LoS) and early hospital readmission (EHR). The objectives were to describe and compare the regional rates of ICP, HD, EHR, and the average LoS after an ACS in 2000 in the province of Quebec. We also assessed whether there was a relationship between ICP and HD, LoS, and EHR, and if the relationships varied spatially. Using secondary data from a provincial hospital register, a population-based retrospective cohort of 24,544 patients hospitalized in Quebec (Canada) for an ACS in 2000 was built. ACS was defined as myocardial infarction (ICD-9: 410) or unstable angina (ICD-9: 411). ICP was defined as the presence of angiography, angioplasty or aortocoronary bypass (CCA: 480–483, 489), HD as all death cause at index hospitalization, LoS as the number of days between admission and discharge from the index hospitalization, and EHR as hospital readmission for a coronary heart disease ≤30 days after discharge from hospital. The EHR was evaluated on survivors at discharge. ICP rate was 43.7% varying from 29.4% to 51.6% according to regions. HD rate was 6.9% (range: 3.3–8.2%), average LoS was 11.5 days (range: 7.5–14.4; median LoS: 8 days) and EHR rate was 8.3% (range: 4.7–14.2%). ICP was positively associated with LoS and negatively with HD and EHR; the relationship between ICP and LoS varied spatially. An increased distance to a specialized cardiology center was associated with a decreased likelihood of ICP, a decrease in LoS, but an increased likelihood of EHR. The main results of this study are the regional variability of the outcomes even after accounting for age, gender, ICP and distance to a cardiology center; the significant relationships between ICP and HD, LoS and EHR, and the spatial variability in the relationships between ICP and LoS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".