Measurement of Systolic Blood Pressure Using POCUS With Color Doppler Compared to with an Intraarterial Line
Bibliographic record
Abstract
Background: In some clinical circumstances, it may be difficult to accurately measure systolic blood pressure (SBP) using direct auscultation technique or an automated oscillometric cuff pressure device. As an alternative method, this study compared the measurement of SBP using point of care ultrasound (POCUS) with color Doppler to the measurement of SBP using an intraarterial catheter. Methods: Study subjects were 50 patients in an intensive care unit who had an intraarterial catheter placed for monitoring blood pressure. The intraarterial catheter systolic pressure was recorded and compared to the contemporaneous measurement of SBP using POCUS with color power Doppler (CPD). The operator placed the Doppler sample volume over the brachial artery with ipsilateral inflation of a prepositioned upper arm blood pressure cuff that was inflated sufficiently to ablate blood flow in the target artery. The blood pressure cuff was then deflated until there was return of CPD signal in the brachial artery. At this moment, the corresponding blood pressure was noted on a sphygmomanometer attached to the blood pressure cuff. The values of the two methods were compared using standard statistical technique. Results: The intraarterial systolic pressures and CPD systolic pressures by POCUS were well correlated with a Pearsons correlation coefficient of 0.96. Bland-Altman analysis of bias and limits of agreement indicated that the POCUS with CPD measurement was sufficiently accurate to have clinical utility. Conclusions: The use of POCUS with CPD to measure SBP may have utility in situations where direct auscultation or automated oscillometeric cuff pressure measurements may be unreliable.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".