Current status of point of care ultrasonography for the perioperative care of trauma patients
Bibliographic record
Abstract
PURPOSE OF REVIEW: The incorporation of point of care ultrasound into the field of anesthesiology and perioperative medicine is growing at rapid pace. The benefits of this modality align with the acuity of patient care and decision-making in anesthetic care of a trauma patient. RECENT FINDINGS: Cardiac ultrasound can be used to diagnose cardiac tamponade or investigate the inferior vena cava to assess volume status in patients who may suffer from hemorrhagic shock. Thoracic ultrasound may be used to rapidly identify pneumothorax or hemothorax in a patient suffering chest wall trauma. In addition, investigators are exploring the utility of ultrasonography in traumatic airway management and elevated intracranial pressure. In addition, the utility of gastric ultrasound on trauma patients is briefly discussed. SUMMARY: Incorporation of point of care ultrasound techniques into the practice of trauma anesthesiology is important for noninvasive, mobile and expeditious assessment of trauma patients. In addition, further large-scale studies are needed to investigate how point of care ultrasound impacts outcomes in trauma patients.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".