Performance of acute coronary syndrome approaches in Brazil: a report from the BRACE (Brazilian Registry in Acute Coronary SyndromEs)
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Bibliographic record
Abstract
AIMS: Diagnostic and therapeutic tools have a significant impact on morbidity and mortality associated with acute coronary syndromes (ACS). Data about ACS performance measures are scarce in Brazil, and improving its collection is an objective of the Brazilian Registry in Acute Coronary syndromEs (BRACE). METHODS AND RESULTS: The BRACE is a cross-sectional, observational epidemiological registry of ACS patients. Stratified 'cluster sampling' methodology was adopted to obtain a representative picture of ACS. A performance score (PS) varying from 0 to 100 was developed to compare studied parameters. Performance measures alone and the PS were compared between institutions, and the relationship between the PS and outcomes was evaluated. A total of 1150 patients, median age 63 years, 64% male, from 72 hospitals were included in the registry. The mean PS for the overall population was 65.9% ± 20.1%. Teaching institutions had a significantly higher PS (71.4% ± 16.9%) compared with non-teaching hospitals (63.4% ± 21%; P < 0.001). Overall in-hospital mortality was 5.2%, and the variables that correlated independently with in-hospital mortality included: PS-per point increase (OR = 0.97, 95% CI 0.95-0.98, P < 0.001), age-per year (OR = 1.06, 95% CI 1.03-1.09, P < 0.001), chronic kidney disease (OR = 3.12, 95% CI 1.08-9.00, P = 0.036), and prior angioplasty (OR = 0.25, 95% CI 0.07-0.84, P = 0.025). CONCLUSIONS: In BRACE, the adoption of evidence-based therapies for ACS, as measured by the performance score, was independently associated with lower in-hospital mortality. The use of diagnostic tools and therapeutic approaches for the management of ACS is less than ideal in Brazil, with high variability especially among different regions of the country.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it