Use of Ultrasound for Pre-hospital Care in Saudi Arabia: A National Survey
Bibliographic record
Abstract
BACKGROUND The use of pre-hospital ultrasound (U/S) in Saudi Arabia requires further elucidation. AIM We aim to assess the use of pre-hospital ultrasound, as well as its barriers and enablers, among emergency medical services (EMS) providers in Saudi Arabia. METHOD This is a cross-sectional observational study, based on a self-administered questionnaire distributed to emergency services personnel in Saudi Arabia between May and August 2022. RESULT 420 EMS providers responded to this survey. 55.5% (n=233) of them had a positive attitude towards using ultrasound in their practice, although about 81% (n=341) had no ultrasound training. Barriers to the implementation of ultrasound included the need for training, difficulty using ultrasound in an ambulance, case overload, and shortage of personnel, among others. CONCLUSION Our findings indicate that emergency care providers have a positive attitude towards the use of ultrasound in the pre-hospital setting. Saudi Arabian EMS should invest in training, raising awareness, and establishing or strengthening existing regulations in this regard.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".