EFSUMB Clinical Practice Guidelines for Point-of-Care Ultrasound: Part One (Common Heart and Pulmonary Applications) LONG VERSION
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: To evaluate the evidence and produce a summary and recommendations for the most common heart and lung applications of point-of-care ultrasound (PoCUS). METHODS: We reviewed 10 clinical domains/questions related to common heart and lung applications of PoCUS. Following review of the evidence, a summary and recommendation were produced, including assignment of levels of evidence (LoE) and grading of the recommendation, assessment, development, and evaluation (GRADE). 38 international experts, the expert review group (ERG), were invited to review the evidence presented for each question. A level of agreement of over 75 % was required to progress to the next section. The ERG then reviewed and indicated their level of agreement regarding the summary and recommendation for each question (using a 5-point Likert scale), which was approved if a level of agreement of greater than 75 % was reached. A level of agreement was defined as a summary of "strongly agree" and "agree" on the Likert scale responses. FINDINGS AND RECOMMENDATIONS: One question achieved a strong consensus for an assigned LoE of 3 and a weak GRADE recommendation (question 1). The remaining 9 questions achieved broad agreement with one assigned an LoE of 4 and weak GRADE recommendation (question 2), three achieving an LoE of 3 with a weak GRADE recommendation (questions 3-5), three achieved an LoE of 3 with a strong GRADE recommendation (questions 6-8), and the remaining two were assigned an LoE of 2 with a strong GRADE recommendation (questions 9 and 10). CONCLUSION: These consensus-derived recommendations should aid clinical practice and highlight areas of further research for PoCUS in acute settings.
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.
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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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 it