Evidence map›Paper›PMID 42891441›Full record

ReviewJournal of medical ultrasound

Utility of Point-of-care Ultrasound in Clinical Care: A Narrative Review.

Chi-Hsin Chen, Wan-Ching Lien

Abstract readReview
In one paragraph

Review in Journal of medical ultrasound. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Chi-Hsin ChenDepartment of Emergency Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan.
Wan-Ching LienDepartment of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Point-of-care ultrasound (POCUS) has emerged as an essential bedside diagnostic tool in modern clinical practice. By enabling real-time visualization of anatomical structures and physiological processes, POCUS allows clinicians to rapidly evaluate patients and integrate imaging findings directly into clinical decision-making. This narrative review summarizes current evidence regarding the clinical utility of POCUS across both critical and noncritical care settings. Key applications include the use of structured ultrasound protocols during cardiac arrest, such as the US-CAB framework, and lung ultrasound approaches like the bedside lung ultrasound in emergency protocol for evaluating acute respiratory failure. In addition, growing evidence supports the use of POCUS in common emergency department presentations, including acute flank pain, nontraumatic abdominal pain, and undifferentiated chest pain or dyspnea. Across these clinical scenarios, POCUS has been shown to facilitate rapid diagnosis, reduce reliance on radiation-based imaging, and improve operational efficiency by shortening emergency department length of stay and expediting clinical decision-making. Despite its clinical advantages, the effective implementation of POCUS requires appropriate operator training and standardized protocols to ensure diagnostic reliability. Ongoing advances in portable ultrasound technology and image-analysis tools may further enhance the accessibility and clinical integration of POCUS in diverse healthcare environments. Overall, POCUS represents a valuable extension of bedside clinical assessment and continues to play an expanding role in modern patient-centered care.

Indexed as

Abdominal painacute respiratory failurecardiac arrestclinical utilityemergency medicinelength of staypoint-of-care ultrasound

Identifiers

PMID42891441
PMCPMC13674897

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.