Clinical applications of point‐of‐care ultrasound in brain injury: a narrative review
Bibliographic record
Abstract
The use of point-of-care ultrasound has increased considerably over the last two decades. It has become a readily available, non-invasive bed-side modality for the rapid diagnosis and management of patients in various settings. Point-of-care ultrasound for assessing the heart, lung, abdomen, airway and vascular systems is now well established. Transcranial Doppler ultrasound for assessing cerebral blood flow has been in use for many years. In recent years, brain ultrasonography has been shown to be a powerful tool in the rapid bed-side assessment of cerebral haemodynamics and structural pathology. Brain ultrasound has been shown to be useful in both the emergency department and neurocritical care setting for the non-invasive assessment of raised intracranial pressure, cerebral autoregulation and diagnosis of intracranial haematoma and other space-occupying lesions. Point-of-care ultrasound is an important alternative technique to routine imaging and invasive monitoring techniques, and results are comparable. Competence is easily attainable without formal radiology training. With technological advancement, applications for the use of brain ultrasound continue to grow. This review discusses the clinical use of point-of-care ultrasound in the diagnosis and management of brain injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".