Prediction of cardiovascular risk: validation of a non-laboratory and a laboratory-based score in a Brazilian community-based cohort of the PURE study
Bibliographic record
Abstract
Background: Risk scores are essential tools for implementing cardiovascular disease (CVD) prevention. Validating risk scores considering regional diversities and disparities is critical for reducing the burden of CVD on global morbidity and mortality. We aimed to validate two cardiovascular risk scores (laboratory and non-laboratory-based) to predict major adverse cardiovascular events in the Brazilian cohort of the PURE study. Methods: We validated two risk scores derived from the INTERHEART study, the non-laboratory INTERHEART risk score (NL-IHRS) and the laboratory fasting cholesterol INTERHEART risk score (FC-IHRS) using data from 4623 (urban areas) and 1415 (rural areas) participants without CVD in the Brazilian cohort of the PURE study enrolled in 2004 and 2005 and followed up to September 2021. The endpoint was major cardiovascular events (MACE), defined as the composite of myocardial infarction, stroke, heart failure, or death from cardiovascular causes. We evaluated the model performance of IHRS through c-statistic and calibration methods. Findings: After a mean follow-up of 8.8 years (range, 0.28-15.1 years), there were 312 cardiovascular events, corresponding to an incidence rate of 0.58% per year (0.56% per year in urban versus 0.64% per year in rural areas). For the NL-IHRS, the c-statistic was 0.69 (95% confidence interval, CI, 0.66-0.72) in the overall cohort, 0.68 (95% CI, 0.64-0.72) in the urban cohort, and 0.72 (95% CI, 0.66-0.78) in the rural cohort. C-statistic values for the recalibrated FC-IHRS were 0.71 (95% CI, 0.67-0.74), 0.71 (95% CI, 0.67-0.75), and 0.70 (95% CI, 0.64-0.76) in the overall, urban, and rural cohorts, respectively. Interpretation: In this Brazilian community-based prospective cohort, both NL-IHRS and FC-IHRS-based models performed with reasonable discriminative accuracy on the risk estimation of long-term risk of major CVD. A non-laboratory-based CVD risk score may be instrumental in Brazilian communities with limited access to medical resources. Funding: Population Health Research Institute, Novartis Biociências S.A.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".