Brachial-Ankle Pulse Wave Velocity and the Risk Prediction of Cardiovascular Disease
Bibliographic record
Abstract
An individual participant data meta-analysis was conducted in the data of 14 673 Japanese participants without a history of cardiovascular disease (CVD) to examine the association of the brachial-ankle pulse wave velocity (baPWV) with the risk of development of CVD. During the average 6.4-year follow-up period, 687 participants died and 735 developed cardiovascular events. A higher baPWV was significantly associated with a higher risk of CVD, even after adjustments for conventional risk factors ( P for trend <0.001). When the baPWV values were classified into quintiles, the multivariable-adjusted hazard ratio for CVD increased significantly as the baPWV quintile increased. The hazard ratio in the subjects with baPWV values in quintile 5 versus that in those with the values in quintile 1 was 3.50 (2.14–5.74; P <0.001). Every 1 SD increase of the baPWV was associated with a 1.19-fold (1.10–1.29; P <0.001) increase in the risk of CVD. Moreover, addition of baPWV to a model incorporating the Framingham risk score significantly increased the C statistics from 0.8026 to 0.8131 ( P <0.001) and also improved the category-free net reclassification (0.247; P <0.001). The present meta-analysis clearly established baPWV as an independent predictor of the risk of development of CVD in Japanese subjects without preexisting CVD. Thus, measurement of the baPWV could enhance the efficacy of prediction of the risk of development of CVD over that of the Framingham risk score, which is based on the traditional cardiovascular risk factors.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.029 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".