Accuracy of oscillometric blood pressure algorithms in healthy adults and in adults with cardiovascular risk factors
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Bibliographic record
Abstract
BACKGROUND: Fixed-ratio and slope-based algorithms are used to derive oscillometric blood pressure (BP). However, a paucity of published data exists assessing the accuracy of these methods. Our objective was to determine the accuracy of fixed-ratio and slope-based algorithms in healthy adults and in adults with cardiovascular risk factors. PATIENTS AND METHODS: Overall, 85 healthy adults (age≥18 years) and 85 adults with cardiovascular risk factors were studied. Three oscillometric and four two-observer mercury-based auscultation measurements were performed in each, according to International Standards Organization 2013 methodology. Two fixed-ratio algorithms and one slope-based algorithm were applied to process oscillometric waveform envelopes and derive oscillometric BP. Paired and unpaired t-tests were used to compare mean oscillometric BP within and between each group, respectively. RESULTS: For healthy adults, mean age was 50.3±17.8 years, mean arm circumference was 30.4±3.8 cm, and 62% were female. In the cardiovascular risk group, mean age was 63.8±12.4 years, mean arm circumference was 31.9±4.2 cm, and 62% were female. For systolic BP, the fixed-ratio algorithms produced the lowest mean error and narrowest SD. For diastolic BP, mean errors were similar for all three algorithms, but the fixed-ratio algorithms had higher precision. The comparison of healthy adults and those with cardiovascular risk factor showed high variability for systolic and diastolic BP (SD: 8.113.9 mmHg). CONCLUSION: In both healthy adults and in those with cardiovascular risk factors, the fixed-ratio technique performed better than the slope-based algorithm. High between-group variability indicates that subject-specific algorithms may be needed.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it