Ventilatory equivalent for oxygen as an extubation outcome predictor: A pilot study
Bibliographic record
Abstract
Introduction: Weaning predictors can help liberate patients in a timely manner from mechanical ventilation.Ventilatory equivalent for oxygen (VEqO 2 ), a surrogate for work of breathing and a measure of the efficiency of breathing, may be an important noninvasive alternative to other weaning predictors.Our study's purpose was to observe any differences in VEqO 2 between extubation outcome groups.Methods: Employing a metabolic cart, oxygen consumption (V ̇O2 ), minute volume (VE), tidal volume (VT), and breathing frequency were recorded during a spontaneous breathing trial (SBT) to calculate VEqO 2 and the rapid shallow breathing index (RSBI) in 34 adult participants in the intensive care unit.Five-breath means of VEqO 2 and the RSBI collected throughout the SBT were examined between SBT pass and fail groups and extubation pass and fail groups using the Mann-Whitney U test with p < 0.05.Results: Data from 31 participants were analyzed between SBT outcome groups.Data from 20 participants were examined for extubation outcome after a successful SBT.Median (interquartile range) VEqO 2 was not different between extubation groups.Participants who passed the SBT had a higher median VEqO 2 than those who did not at the midpoint (25.Discussion: VEqO 2 may show differences in SBT outcomes, but not differences between extubation outcomes.VEqO 2 may be able to detect differences in work during an SBT, but may not be able to predict change in workload in the respiratory system after extubation.The small sample size may also have prevented any differences in extubation outcomes to be shown.Conclusion: VEqO 2 was higher in patients that passed their SBT.VEqO 2 was not useful in identifying extubation success or failure in adult mechanically ventilated patients.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".