Blood pressure measures and their predictive ability of cardiovascular mortality
Bibliographic record
Abstract
OBJECTIVE(S): Our aim was to calculate the predictability of different blood pressure measures for cardiovascular mortality in a cohort of both men and women. We also aimed to determine whether clinically applicable cut-off levels for cardiovascular mortality risk of these measures work well. MATERIALS AND METHODS: A healthcare need investigation from the 1970s was used. Participants aged 46-65 were included, n=788 (390 men and 398 women). The following blood pressure measures were studied: systolic, diastolic, mean, mid, and pulse pressure. The participants were followed for 26 years with respect to cardiovascular mortality through the Swedish Cause-of-Death Register. Isolated diastolic hypertension failed to show significant associations with cardiovascular mortality. RESULTS: Combined systolic and diastolic hypertension showed twice as high cardiovascular mortality in men and women compared with those with normal blood pressure. Mid arterial blood pressure showed increased significant hazard ratios for all three grades of hypertension in men and for grades 2 and 3 in women with good predictability (area under the curve=0.72 and 0.80, respectively). CONCLUSIONS: Mid arterial blood pressure is strongly associated with cardiovascular mortality. Additional studies in larger populations and with a wider age range comparing mid arterial blood pressure with clinically useful cut-offs of other blood pressure measures are required to corroborate our findings.
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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 | 0.002 | 0.009 |
| 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) | 0.001 | 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".