Predicted 10-year risk of cardiovascular disease among Canadian adults using modified Framingham Risk Score in association with dietary intake
Bibliographic record
Abstract
Initial risk assessment to estimate 10-year risk of cardiovascular disease (CVD) is completed by Framingham Risk Score (FRS). In 2012 2 modifications were added to FRS by the Canadian Cardiovascular Society: FRS is doubled in subjects aged 30-59 years who have CVD present in a first-degree relative before 55 years of age for men and 65 years of age for women; and cardiovascular age is calculated for each individual. Our aim was to implement these modifications and evaluate differences compared with traditional FRS. Further, we evaluated the association between dietary intake and 10-year risk. The Canadian Health Measures Survey data cycle 1 was used among participants aged 30-74 years (n = 2730). Descriptive and logistic regression analyses were conducted using STATA SE 11. Using modified FRS for predicting 10-year risk of CVD significantly increased the estimated risk compared with the traditional approach, 8.66% ± 0.35% versus 6.06% ± 0.18%, respectively. Greater impact was observed with the "cardiovascular age" modification in men versus women. The distribution of Canadians in low- (<10%) and high-risk (≥20%) categories of CVD show a significant difference between modified and traditional FRS: 67.4% versus 79.6% (low risk) and 13.7% versus 4.5% (high risk), respectively. The odds of having risk ≥10% was significantly greater in low-educated, abdominally obese individuals or those with lower consumption of breakfast cereal and fruit and vegetable and greater potato and potato products consumption. In conclusion, the traditional FRS method significantly underestimates CVD risk in Canadians; thus, applying modified FRS is beneficial for screening. Additionally, fibre consumption from fruit and vegetable or breakfast cereals might be beneficial in reducing CVD risks.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".