Carotid Doppler Measurement Variability in Functional Hemodynamic Monitoring: An Analysis of 17,822 Cardiac Cycles
Bibliographic record
Abstract
Carotid Doppler ultrasound is used as a measure of fluid responsiveness, however, assessing change with statistical confidence requires an adequate beat sample size. The coefficient of variation helps quantify the number of cardiac cycles needed to adequately detect change during functional hemodynamic monitoring. DESIGN: Prospective, observational, human model of hemorrhage and resuscitation. SETTING: Human physiology laboratory at Mayo Clinic. SUBJECTS: Healthy volunteers. INTERVENTIONS: Lower body negative pressure. MEASUREMENTS AND MAIN RESULTS: We measured the coefficient of variation of the carotid artery velocity time integral and corrected flow time during significant cardiac preload changes. Seventeen-thousand eight-hundred twenty-two cardiac cycles were analyzed. The median coefficient of variation of the carotid velocity time integral was 8.7% at baseline and 11.9% during lowest-tolerated lower body negative pressure stage. These values were 3.6% and 4.6%, respectively, for the corrected flow time. CONCLUSIONS: The median coefficient of variation values measured in this large dataset indicates that at least 6 cardiac cycles should be averaged before and after an intervention when using the carotid artery as a functional hemodynamic measure.
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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 | 0.004 | 0.011 |
| 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 | 0.000 |
| 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 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".