Inferior Vena Caval Measures Do Not Correlate with Carotid Artery Corrected Flow Time Change Measured Using a Wireless Doppler Patch in Healthy Volunteers
Bibliographic record
Abstract
(1) Background: The inspiratory collapse of the inferior vena cava (IVC), a non-invasive surrogate for right atrial pressure, is often used to predict whether a patient will augment stroke volume (SV) in response to a preload challenge. There is a correlation between changing stroke volume (SV∆) and corrected flow time of the common carotid artery (ccFT∆). (2) Objective: We studied the relationship between IVC collapsibility and ccFT∆ in healthy volunteers during preload challenges. (3) Methods: A prospective, observational, pilot study in euvolemic, healthy volunteers with no cardiovascular history was undertaken in a local physiology lab. Using a tilt-table, we studied two degrees of preload augmentation from (a) supine to 30-degrees head-down and (b) fully-upright to 30-degrees head down. In the supine position, % of IVC collapse with respiration, sphericity index and portal vein pulsatility was calculated. The common carotid artery Doppler pulse was continuously captured using a wireless, wearable ultrasound system. (4) Results: Fourteen subjects were included. IVC % collapse with respiration ranged between 10% and 84% across all subjects. Preload responsiveness was defined as an increase in ccFT∆ of at least 7 milliseconds. A total of 79% (supine baseline) and 100% (head-up baseline) of subjects were preload-responsive. No supine venous measures (including IVC % collapse) were significantly related to ccFT∆. (5) Conclusions: From head-up baseline, 100% of healthy subjects were ‘preload-responsive’ as per the ccFT∆. Based on the 42% and 25% IVC collapse thresholds in the supine position, only 50% and 71% would have been labeled ‘preload-responsive’.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".