Emerging Applications of Extracardiac Ultrasound in Critically Ill Cardiac Patients
Bibliographic record
Abstract
Point-of-care ultrasound has evolved as an invaluable diagnostic modality and procedural guidance tool in the care of critically ill cardiac patients. Beyond focused cardiac ultrasound, additional extracardiac ultrasound modalities may provide important information at the bedside. In addition to new uses of existing modalities, such as pulsed-wave Doppler ultrasound, the development of new applications is fostered by the implementation of additional features in mid-range ultrasound machines commonly acquired for intensive care units, such as tissue elastography, speckle tracking, and contrast-enhanced ultrasound quantification software. This review explores several areas in which ultrasound imaging technology may transform care in the future. First, we review how lung ultrasound in mechanically ventilated patients can enable the personalization of ventilator parameters and help to liberate them from mechanical ventilation. Second, we review the role of venous Doppler in the assessment of organ congestion and how tissue elastography may complement this application. Finally, we explore how contrast-enhanced ultrasound could be used to assess changes in organ perfusion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".