Ultrasound Assessment of Lung Aeration in Subjects Supported by Venovenous Extracorporeal Membrane Oxygenation
Bibliographic record
Abstract
BACKGROUND: The value of ultrasound in assessing lung aeration of patients with ARDS who require venovenous extracorporeal membrane oxygenation (ECMO) has, to our knowledge, never been studied. The objective of the study was to evaluate by using ultrasound lung aeration at ECMO initiation and withdrawal in subjects with severe ARDS supported by venovenous ECMO. METHODS: Fifty subjects were included in this pilot retrospective study. The lung ultrasound aeration score (LUS) and respiratory variables were collected at ECMO initiation (T0) and ECMO withdrawal (T1). The LUS at T0 between the subjects who survived to ICU discharge and those who died in ICU was compared. The relationship between changes in LUS and changes in P aO 2 /F IO 2 from T0 to T1 was assessed. RESULTS: The ICU mortality was 34%. The LUS at T0 did not differ between survivors and non-survivors (median 22 [interquartile range] {IQR} 19–26 vs median 24 [IQR, 19–28]; P = .60). From T0 to T1, the LUS decreased significantly in survivors (median 22 [IQR, 19–26] vs median 16 [IQR, 13–19]; P < .001), it decreased moderately in non-survivors who were weaned off ECMO (median 26 [24–29]) vs median 22 (IQR, 17–24), P = .031), and remained stable in those who died during ECMO (median 25 [IQR, 19–29] vs median 25 [IQR, 23–31]; P = .22). Changes in P aO 2 /F IO 2 were not related to changes in the LUS between T0 and T1. CONCLUSIONS: At the time of ECMO placement, the subjects who survived ARDS had aeration loss close to that observed in the subjects who did not survive. At the time of ECMO withdrawal, there was a significant improvement in lung aeration in the survivors, whereas a severe loss of lung aeration persisted in the non-survivors, although some were weaned off ECMO. Lung ultrasound provided a valuable tool for bedside assessment of lung aeration in subjects supported by ECMO.
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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 | 0.000 |
| 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) | 0.001 | 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".