The Weaning Index combining EtCO2 and respiratory rate early identifies Spontaneous Breathing Trial failure
Bibliographic record
Abstract
BACKGROUND: We aimed to evaluate the predictive value of the end-tidal CO2 (EtCO2) alone or combined with ventilation related parameters on Spontaneous Breathing Trial (SBT) outcome on mechanically ventilated patients. METHODS: Prospective observational study in a medical Intensive Care Unit. Mechanically ventilated adult patients who met predefined criteria for weaning were included. Patients underwent a T-piece SBT for 30 minutes and the hemodynamic and respiratory clinical parameters including EtCO2 were recorded every five minutes. RESULTS: The study included 280 patients, who were studied (age: 64±17 years, SAPS II: 44 [34-56]) during a first SBT and 76 patients during a second SBT. The Weaning Index, defined as the product of the respiratory rate and EtCO2, was a strong early predictive factor of SBT outcome; at 10 minutes, the area under the curve (AUC) was 86% ([80-90], P<0.0001) during the first SBT and 88% ([80-96], P<0.0001) during the second SBT. After 10 minutes of SBT, a Weaning Index >1100 identified patients that will not successfully complete the SBT at 30 minutes with a specificity of 98%. CONCLUSIONS: In unselected mechanically ventilated patients, the Weaning Index is helpful to early identify patients who will fail the SBT during a first and a second trial.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".