Comparability of oscillometric to simultaneous auscultatory blood pressure measurement in children
Bibliographic record
Abstract
OBJECTIVE: Uncertainty exists regarding the accuracy of automated blood pressure (BP) measurement in children. We recorded oscillometric waveforms in children, derived oscillometric BPs using two standard algorithms, and compared the results to simultaneous auscultation. PATIENTS AND METHODS: Twenty children aged 2-12 years were recruited from a tertiary-care Pediatric Nephrology Clinic. Sex, height, weight, arm circumference, history of hypertension, and clinic BP were recorded. Two, simultaneously measured, oscillometric and auscultatory BP readings were obtained 30-60 s apart. The first reading was discarded and, the second, used for analyses. Fixed-ratio and slope-based algorithms were used for BP derivation. RESULTS: Mean age was 7.95±2.82 years, 40% were female, mean arm circumference was 21.86±4.06 cm, and 50% had hypertension or a history of hypertension. Mean auscultatory BP for all participants (systolic±SD/diastolic±SD) was 93.40±11.80/50.50±9.04 mmHg, oscillometric fixed-ratio BP was 99.20±11.90/57.35±7.15 mmHg and oscillometric slope-based algorithm was 91.60±13.94/60.65±7.71 mmHg. Compared to auscultation, the fixed-ratio method differed by 5.80±12.72/6.85±7.51 mmHg (P=0.06 and <0.01) and the slope-based method differed by -1.80±13.59/10.15±8.07 mmHg (P=0.56 and <0.01). Differences from auscultation were statistically significant for diastolic BP with both fixed-ratio and slope-based methods for all age categories but of greatest magnitude in the youngest children. CONCLUSION: Oscillometric BP derived using two commonly used algorithms differed by more than 5 mmHg in either systolic BP or diastolic BP from simultaneous auscultatory BP in children aged 2-11. These findings emphasize the need for greater understanding of the functionality and accuracy of oscillometry in children.
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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 | 0.007 | 0.037 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".