Predicting extubation in patients with traumatic cervical spinal cord injury using the diaphragm electrical activity during a single maximal maneuver
Bibliographic record
Abstract
BACKGROUND: The unsuccessful extubation in patients with traumatic cervical spinal cord injuries (CSCI) may result from impairment diaphragm function and monitoring of diaphragm electrical activity (EAdi) can be informative in guiding extubation. We aimed to evaluate whether the change of EAdi during a single maximal maneuver can predict extubation outcomes in CSCI patients. METHODS: This is a retrospective study of CSCI patients requiring mechanical ventilation in the ICU of a tertiary hospital. A single maximal maneuver was performed by asking each patient to inhale with maximum strength during the first spontaneous breathing trial (SBT). The baseline (during SBT before maximal maneuver), maximum (during the single maximal maneuver), and the increase of EAdi (ΔEAdi, equal to the difference between baseline and maximal) were measured. The primary outcome was extubation success, defined as no reintubation after the first extubation and no tracheostomy before any extubation during the ICU stay. RESULTS: Among 107 patients enrolled, 50 (46.7%) were extubated successfully at the first SBT. Baseline EAdi, maximum EAdi, and ΔEAdi were significantly higher, and the rapid shallow breathing index was lower in patients who were extubated successfully than in those who failed. By multivariable logistic analysis, ΔEAdi was independently associated with successful extubation (OR 2.03, 95% CI 1.52-3.17). ΔEAdi demonstrated high diagnostic accuracy in predicting extubation success with an AUROC 0.978 (95% CI 0.941-0.995), and the cut-off value was 7.0 μV. CONCLUSIONS: The increase of EAdi from baseline SBT during a single maximal maneuver is associated with successful extubation and can help guide extubation in CSCI patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".