A wearable carotid Doppler tracks changes in the descending aorta and stroke volume induced by <scp>end‐inspiratory</scp> and <scp>end‐expiratory</scp> occlusion: A pilot study
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Bibliographic record
Abstract
Abstract Background and Aims To test the feasibility of a novel, wearable carotid Doppler ultrasound to track changes in cardiac output induced by end‐inspiratory and end‐expiratory occlusion tests. Methods We observed the pattern of Doppler change of the common carotid artery during a simulated end‐inspiratory and expiratory occlusion test (sEIOT/sEEOT) in 10, nonventilated, healthy subjects. Simultaneously, we measured the Doppler signal of the descending aorta using duplex ultrasound (Xario, Toshiba Medical Systems) and stroke volume (SV) using noninvasive pulse contour analysis (Clearsight, Edwards Lifesciences, Irvine, California). Results During sEIOT, SV, maximum velocity time integral (VTI) of the descending aorta, and common carotid fell by 25.7% ( P = .0131), 26.1% ( P < .0001), and 18.5% ( P < .0001), respectively. During sEEOT, SV, maximum VTI of the descending aorta, and common carotid rose by: 41.3% ( P = .0051), 28.3% ( P < .0001), and 41.6% ( P < .0001), respectively. There was good correlation between change in aortic VTI and carotid VTI ( r 2 = 0.79); SV and aortic VTI ( r 2 = 0.82), and SV and carotid VTI ( r 2 = 0.95).The coefficient of variation of the VTI measured by the Doppler patch was roughly 60% less than that of the duplex system. Conclusions The pattern of SV change induced by a sEIOT/sEEOT in nonmechanically ventilated volunteers is reflected in the common carotid artery and descending aorta. The VTI variability of the Doppler patch was less than that of the traditional, duplex Doppler.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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