Evidence map›Paper›PMID 39924719›Full record

ArticleUltrasonography (Seoul, Korea)2025

Intelligent handheld ultrasound improving the ability of non-expert general practitioners in carotid examinations for community populations: a prospective and parallel controlled trial.

Pei Sun, Hong Han, Yi-Kang Sun, Xi Wang, Xiao-Chuan Liu, Bo-Yang Zhou, Li-Fan Wang, Ya-Qin Zhang, Zhi-Gang Pan, Bei-Jian Huang and 2 more

Abstract read
In one paragraph

Article in Ultrasonography (Seoul, Korea), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Observational
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

12 authors.

Pei SunDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Hong HanDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Yi-Kang SunDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Xi WangDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Xiao-Chuan LiuGeneral Medicine Department, Zhongshan Hospital, Fudan University, Shanghai, China.
Bo-Yang ZhouDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Li-Fan WangDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Ya-Qin ZhangDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Zhi-Gang PanGeneral Medicine Department, Zhongshan Hospital, Fudan University, Shanghai, China.
Bei-Jian HuangDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Hui-Xiong XuDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
Chong-Ke ZhaoDepartment of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.

Funding

Fundamental Research Funds for the Central Universities ZD-11-202151National Natural Science Foundation of China 12174074National Natural Science Foundation of China 82202174Science and Technology Commission of Shanghai Municipality 18441905500Science and Technology Commission of Shanghai Municipality 19DZ2251100Shanghai Municipal Health Commission 2019LJ21Shanghai Municipal Health Commission SHSLCZDZK03502Shanghai Science and Technology Innovation Action Plan 21Y11911200Zhongshan Hospital of Fudan University 2022ZSQD07
6 · The paper itself

Abstract

purposeThe aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations.

methodsThis prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits.

resultsAmong the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01).

conclusionUsing an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Indexed as

Carotid plaqueCommunity residentsIntelligent handheld ultrasound deviceNon-expert general practitionerPlaque-Reporting and Data System

Identifiers

PMID39924719
PMCPMC11938801

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.