Prospective Longitudinal Evaluation of <scp>Point‐of‐Care</scp> Lung Ultrasound in Critically Ill Patients With Severe <scp>COVID</scp>‐19 Pneumonia
Bibliographic record
Abstract
OBJECTIVES: To perform a prospective longitudinal analysis of lung ultrasound findings in critically ill patients with coronavirus disease 2019 (COVID-19). METHODS: Eighty-nine intensive care unit (ICU) patients with confirmed COVID-19 were prospectively enrolled and tracked. Point-of-care ultrasound (POCUS) examinations were performed with phased array, convex, and linear transducers using portable machines. The thorax was scanned in 12 lung areas: anterior, lateral, and posterior (superior/inferior) bilaterally. Lower limbs were scanned for deep venous thrombosis and chest computed tomographic angiography was performed to exclude suspected pulmonary embolism (PE). Follow-up POCUS was performed weekly and before hospital discharge. RESULTS: Patients were predominantly male (84.2%), with a median age of 43 years. The median duration of mechanical ventilation was 17 (interquartile range, 10-22) days; the ICU length of stay was 22 (interquartile range, 20.2-25.2) days; and the 28-day mortality rate was 28.1%. On ICU admission, POCUS detected bilateral irregular pleural lines (78.6%) with accompanying confluent and separate B-lines (100%), variable consolidations (61.7%), and pleural and cardiac effusions (22.4% and 13.4%, respectively). These findings appeared to signify a late stage of COVID-19 pneumonia. Deep venous thrombosis was identified in 16.8% of patients, whereas chest computed tomographic angiography confirmed PE in 24.7% of patients. Five to six weeks after ICU admission, follow-up POCUS examinations detected significantly lower rates (P < .05) of lung abnormalities in survivors. CONCLUSIONS: Point-of-care ultrasound depicted B-lines, pleural line irregularities, and variable consolidations. Lung ultrasound findings were significantly decreased by ICU discharge, suggesting persistent but slow resolution of at least some COVID-19 lung lesions. Although POCUS identified deep venous thrombosis in less than 20% of patients at the bedside, nearly one-fourth of all patients were found to have computed tomography-proven PE.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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, 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".