Clinical Usefulness of Respiratory Variations in Arterial Pressure
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is increasing interest in the use of respiratory variations in arterial pulse pressure to predict the Q response to a fluid challenge (1–4). This has likely evolved because of the appreciation that excess fluid infusion is harmful, as well as concerns over invasive monitoring (5). Thus, techniques that provide noninvasive assessment of volume status hold great promise. The major impetus for these tests came from the work of Perel and coworkers (6) who followed-up on a preliminary report by Coyle and coworkers (7). They defined the difference between maximum and minimum arterial systolic pressure during a respiratory cycle as systolic pressure variation (SPV) (6). The inspiratory increase in pressure relative to the value at end-expiration was called dUp, and the fall in pressure relative to the end-expiratory value was called dDown (Figures 1 and E1). The larger the dDown and SPV, the larger the predicted increase in Q with volume loading.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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