The effect of gravity-induced preload change on the venous excess ultrasound (VExUS) score and internal jugular vein Doppler in healthy volunteers
Bibliographic record
Abstract
BACKGROUND: The venous excess ultrasound (VExUS) score is a multi-organ Doppler approach to assess venous congestion. Despite growing use of VExUS in research and clinical practice, other veins can be visualized to assess for venous hypertension, which may overcome acquisition barriers of the VExUS exam. In this pilot, observational study, we used a wearable Doppler ultrasound to assess the relationship between jugular venous Doppler and the VExUS score under different preload conditions. We hypothesized that jugular Doppler morphology would accurately distinguish preload conditions, that it would most closely relate to the hepatic venous Doppler morphology in the fully supine position and that the VExUS score would be influenced by preload condition. RESULTS: We recruited 15 healthy volunteers with no cardiovascular history. Preload change was achieved using a tilt-table with three positions: supine, fully upright, and 30-degree head-down tilt. In each position, a VExUS score was performed; furthermore, inferior vena collapsibility and sphericity index were calculated. At the same time, jugular venous Doppler was captured by a novel, wireless, wearable ultrasound system. A continuous jugular venous Doppler morphology was 96% accurate for detecting the low preload condition. The jugular venous Doppler morphology was highly correlated with the hepatic vein, but only in the supine position. Gravitational position did not significantly affect the sphericity index or the VExUS score. CONCLUSIONS: The jugular vein Doppler morphology was able to accurately distinguish low from high preload conditions in healthy volunteers. Comparisons between VExUS Doppler morphologies and other veins should occur in the supine position when gravitational pressure gradients are minimized; finally, different preload conditions in healthy subjects did not affect the VExUS score.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".