Continuous Venous-Arterial Doppler Ultrasound During a Preload Challenge
Bibliographic record
Abstract
A preload challenge (PC) is a clinical maneuver that, first, increases the cardiac filling (i.e., preload) and, second, calculates the change in cardiac output. Fundamentally, a PC is a bedside approach for testing the Frank-Starling-Sarnoff (i.e., "cardiac function") curve. Normally, this curve has a steep slope such that a small change in the cardiac preload generates a large change in the stroke volume (SV) or cardiac output. However, in various disease states, the slope of this relationship flattens such that increasing the volume into the heart leads to little rise in the SV. In this pathological scenario, additional cardiac preload (e.g., intravenous fluid) is unlikely to be physiologically effective and could lead to harm if organ congestion evolves. Therefore, inferring both the cardiac preload and output is clinically useful as it may guide intravenous (IV) fluid resuscitation. Accordingly, the goal of this protocol is to describe a method for contemporaneously tracking the surrogates of cardiac preload and output using a novel, wireless, wearable ultrasound during a well-validated preload challenge.
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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 | 0.000 |
| 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".