Handheld Point-of-Care Ultrasound: Safety Considerations for Creating Guidelines
Bibliographic record
Abstract
BACKGROUND: Compared to traditional ultrasound machines, emerging handheld point-of-care-ultrasound (HPOCUS) systems exhibit superior portability and affordability. Thus, they have been increasingly embraced in the intensive care setting. However, there is scarce data on patient safety and current regulatory body guidelines are lacking. Here, we critically appraise the literature with a focus on the merits, concerns, and framework of existing POCUS guidelines. Subsequently, we provide recommendations for future regulatory guidelines. METHODS: A comprehensive literature review was conducted using the PubMed database employing the key words "point-of-care/handheld/portable ultrasound" and "guidelines" alone, in combination, and using thesaurus terms. Eligible articles were scrutinized for description of potential benefits and concerns of HPOCUS, especially from a patient safety perspective, as well as currently existing POCUS practice guidelines. Data was extracted, reported thematically using a narrative synthesis approach, then subsequently used to guide our proposed guidelines. RESULTS: The most widely reported benefits of HPOCUS include superior portability, affordability, imaging, facilitation of expedited diagnosis and management, and integration with medical workplace flow. However, major barriers to adoption include device security/patient confidentiality and patient safety. Furthermore, except for a policy published by the American College of Emergency Physicians (ACEP) in 2018, there are few other national regulatory guidelines pertaining to handheld POCUS. In light of this, we propose a framework for HPOCUS guideline development to address these and other concerns. Such guidelines include training and credentialing, bioengineering approval, and strategic integration with electronic medical record systems. CONCLUSION: HPOCUS can be a powerful tool for expedited diagnosis and management guidance. However, there is limited data regarding patient safety and current regulatory body guidelines are lacking. Our assessment illuminates that there remain many unsolved problems about HPOCUS, and in turn, we propose guidelines to address safe regulation and implementation.
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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 | 0.142 | 0.336 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.013 | 0.023 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".