Ultrasound evaluation of diaphragm function in mechanically ventilated patients: comparison to phrenic stimulation and prognostic implications
Bibliographic record
Abstract
Rationale In intensive care unit (ICU) patients, diaphragm dysfunction is associated with adverse clinical outcomes. Ultrasound measurements of diaphragm thickness, excursion (EXdi) and thickening fraction (TFdi) are putative estimators of diaphragm function, but have never been compared with phrenic nerve stimulation. Our aim was to describe the relationship between these variables and diaphragm function evaluated using the change in endotracheal pressure after phrenic nerve stimulation (Ptr,stim), and to compare their prognostic value. Methods Between November 2014 and June 2015, Ptr,stim and ultrasound variables were measured in mechanically ventilated patients <24 hours after intubation (‘initiation of mechanical ventilation (MV)’, under assist-control ventilation, ACV) and at the time of switch to pressure support ventilation (‘switch to PSV’), and compared using Spearman9s correlation and receiver operating characteristic curve analysis. Diaphragm dysfunction was defined as Ptr,stim <11 cm H2O. Results 112 patients were included. At initiation of MV, Ptr,stim was not correlated to diaphragm thickness (p=0.28), EXdi (p=0.66) or TFdi (p=0.80). At switch to PSV, TFdi and EXdi were respectively very strongly and moderately correlated to Ptr,stim, (r=0.87, p<0.001 and 0.45, p=0.001), but diaphragm thickness was not (p=0.45). A TFdi <29% could reliably identify diaphragm dysfunction (sensitivity and specificity of 85% and 88%), but diaphragm thickness and EXdi could not. This value was associated with increased duration of ICU stay and MV, and mortality. Conclusions Under ACV, diaphragm thickness, EXdi and TFdi were uncorrelated to Ptr,stim. Under PSV, TFdi was strongly correlated to diaphragm strength and both were predictors of remaining length of MV and ICU and hospital death.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".