Diaphragm function and weaning from mechanical ventilation: an ultrasound and phrenic nerve stimulation clinical study
Why this work is in the frame
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Bibliographic record
Abstract
Diaphragm dysfunction is defined by a value of twitch tracheal pressure in response to magnetic phrenic stimulation (twitch pressure) amounting to less than 11 cmH 2 O. This study assessed whether this threshold or a lower one would predict accurately weaning failure from mechanical ventilation. Twitch pressure was compared to ultrasound measurement of diaphragm function. In patients undergoing a first spontaneous breathing trial, diaphragm function was evaluated by twitch pressure and by diaphragm ultrasound (thickening fraction). Receiver operating characteristics curves were computed to determine the best thresholds predicting failure of spontaneous breathing trial. Seventy-six patients were evaluated, 48 (63%) succeeded and 28 (37%) failed the spontaneous breathing trial. The optimal thresholds of twitch pressure and thickening fraction to predict failure of the spontaneous breathing trial were, respectively, 7.2 cmH 2 O and 25.8%, respectively. The receiver operating characteristics curves were 0.80 (95% CI 0.70–0.89) for twitch pressure and 0.82 (95% CI 0.73–0.93) for thickening fraction. Both receiver operating characteristics curves were similar ( p = 0.83). A twitch pressure value lower than 11 cmH 2 O (the traditional cutoff for diaphragm dysfunction) predicted failure of the spontaneous breathing trial with a sensitivity of 89% (95% CI 72–98%) and a specificity of 45% (95% CI 30–60%). Failure of spontaneous breathing trial can be predicted with a lower value of twitch pressure than the value defining diaphragm dysfunction. Twitch pressure and thickening fraction had similar strong performance in the prediction of failure of the spontaneous breathing trial.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it