Point-of-Care Ultrasound in Neurology – Report of the EAN SPN/ESNCH/ERcNsono Neuro-POCUS Working Group
Bibliographic record
Abstract
In the last decade, ultrasound examination in neurology has been undergoing a significant expansion of its modalities. In parallel, there is an increasing demand for rapid and high-quality diagnostics in various acute diseases in the prehospital setting, the emergency room, intensive care unit, and during surgical or interventional procedures. Due to the growing need for rapid answers to clinical questions, there is particular demand for diagnostic ultrasound imaging. The Neuro-POCUS working group, a joint project by the European Academy of Neurology Scientific Panel Neurosonology, the European Society of Neurosonology and Cerebral Hemodynamics, and the European Reference Centers in Neurosonology (EAN SPN/ESNCH/ERcNsono Neuro-POCUS working group), was given the task of creating a concept for point-of-care ultrasound in neurology called "Neuro-POCUS". We introduce here a new ultrasound examination concept called point-of-care ultrasound in neurology (Neuro-POCUS) designed to streamline conclusive imaging outside of the ultrasound center, directly at the bedside. The aim of this study is to encourage neurologists to add quick and disease-oriented Neuro-POCUS to accompany the patient in the critical phase as an adjunct not a substitution for computed tomography, magnetic resonance imaging, or standard comprehensive neurosonology examination. Another goal is to avoid unwanted complications during imaging-free periods, ultimately resulting in advantages for the patient.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".