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Record W4407398925 · doi:10.1016/j.lana.2025.101009

Prediction of cardiovascular risk: validation of a non-laboratory and a laboratory-based score in a Brazilian community-based cohort of the PURE study

2025· article· en· W4407398925 on OpenAlexafffund
Gustavo Bernardes de Figueiredo Oliveira, Rafael Amorim Belo Nunes, Lucas Bassolli de Oliveira Alves, Precil Diego Miranda de Menezes Neves, Victor Augusto Hamamoto Sato, Ana Heloísa Kamada Triboni, Haliton Alves de Oliveira Júnior, Priscila Raupp da Rosa, Maria Luz Díaz, Fernando Laņas, Philip Joseph, Álvaro Avezum

Bibliographic record

VenueThe Lancet Regional Health - Americas · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersNovartis Animal HealthMcMaster University
KeywordsCohortFramingham Risk ScoreMedicineStatisticsInternal medicineMathematicsDisease

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.328
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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