Central Blood Pressure Calibration Method and Cardiovascular Risk Prediction According to Sex
Bibliographic record
Abstract
Background: The accuracy of central BP is improved when calibrated on the mean BP and diastolic BP (C2SBP) compared to calibration on the systolic BP and diastolic BP (C1SBP). Furthermore, preliminary data suggest C2SBP may have the best accuracy in females. We aim to assess whether this enhanced accuracy translates into improved cardiovascular (CV) risk prediction when compared to brachial SBP (bSBP) and C1SBP in the general population and stratified by sex. Methods: 12,927 participants exempt of known CV disease, with prospective follow-up from administrative databases and central BP measurements were included. The SphygmoCor Px device was used to estimate C1SBP. C2SBP was derived from unprocessed radial pressure waveforms extracted from SphygmoCor output data, which was recalibrated with diastolic BP and 40% form factor derived mean BP. Participants with heart rate <60 were excluded due to incomplete waveforms. Major adverse CV events (MACE) comprised myocardial infarction, stroke, heart failure with hospitalization and CV death. Multivariable Cox regressions, differences in area under the curve, net reclassification index and integrated discrimination index were calculated comparing C2SBP to C1SBP and to bSBP. Results: Over a median follow-up of 10.1 years (IQR 9.9-10.3), there were 2125 MACE (723/7013 females and 860/5934 males). All BP parameters were significantly associated with MACE, regardless of sex. In the overall cohort, risk prediction metrics marginally favored C2SBP compared to bSBP, but were similar to C1SBP. No significant improvement of CV risk prediction was found in sex-stratified analyses (see Table). Conclusions: C2SBP marginally improved CV risk prediction when compared to bSBP but not C1SBP in the overall cohort only. All three BP parameters were similarly predictive in both sex, although this analysis possibly lacked power. This may be related to the FF-derived MAP (rather than oscillometric MAP), which is highly dependent on the brachial SBP.Table 1.: Central blood pressure calibration method and cardiovascular risk prediction
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".