Evidence map›Paper›PMID 35923952›Full record

ArticleFrontiers in public health2022

Successful Use of a 5G-Based Robot-Assisted Remote Ultrasound System in a Care Center for Disabled Patients in Rural China.

Hui-Hui Chai, Rui-Zhong Ye, Lin-Fei Xiong, Zi-Ning Xu, Xuan Chen, Li-Juan Xu, Xin Hu, Lian-Feng Jiang, Cheng-Zhong Peng

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 18% of its field
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

7 citing papers in PubMed, 21 citations in OpenAlex.

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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

9 authors at 3 institutions in 1 country.

Hui-Hui ChaiDepartment of Medical Ultrasound, Shanghai Tenth People' Hospital, Tongji University School of Medicine, Shanghai, China.
Rui-Zhong YeEmergency and Critical Care Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China.
Lin-Fei XiongDepartment of Engineering, BGI Life Science Research Institution, Shenzhen, China.
Zi-Ning XuEmergency and Critical Care Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, China.
Xuan ChenDepartment of Engineering, BGI Life Science Research Institution, Shenzhen, China.
Li-Juan XuDepartment of General Practice, Yuanshu Disabled Care Center, Huzhou, China.
Xin HuDepartment of General Practice, Yuanshu Disabled Care Center, Huzhou, China.
Lian-Feng JiangDepartment of General Practice, Yuanshu Disabled Care Center, Huzhou, China.
Cheng-Zhong PengDepartment of Medical Ultrasound, Shanghai Tenth People' Hospital, Tongji University School of Medicine, Shanghai, China.
BGI Group (China) · CNShanghai Tenth People's Hospital · CNZhejiang Provincial People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Disability has become a global population health challenge. Due to difficulties in self-care or independent living, patients with disability mainly live in community-based care centers or institutions for long-term care. Nonetheless, these settings often lack basic medical resources, such as ultrasonography. Thus, remote ultrasonic robot technology for clinical applications across wide regions is imperative. To date, few experiences of remote diagnostic systems in rural care centers have been reported. Objective: To assess the feasibility of a fifth-generation cellular technology (5G)-based robot-assisted remote ultrasound system in a care center for disabled patients in rural China. Methods: Patients underwent remote robot-assisted and bedside ultrasound examinations of the liver, gallbladder, spleen, and kidneys. We compared the diagnostic consistency and differences between the two modalities and evaluated the examination duration, image quality, and safety. Results: Forty-nine patients were included (21 men; mean age: 61.0 ± 19.0 [range: 19-91] years). Thirty-nine and ten had positive and negative results, respectively; 67 lesions were detected. Comparing the methods, 41 and 8 patients had consistent and inconsistent diagnoses, respectively. The McNemar and kappa values were 0.727 and 0.601, respectively. The mean duration of remote and bedside examinations was 12.2 ± 4.5 (range: 5-26) min and 7.5 ± 1.8 (range: 5-13) min ( Conclusions: A 5G-based robot-assisted remote ultrasound system is feasible and has comparable diagnostic efficiency to traditional bedside ultrasound. This system may provide a unique solution for basic ultrasound diagnostic services in primary healthcare settings.

Indexed as

Persons with DisabilitiesRoboticsAdultAgedAged, 80 and overChinaHumansMaleMiddle AgedRural PopulationUltrasonography5G networkcare centerdisabilityrobot-assistedrural healthultrasonography

Identifiers

PMID35923952
PMCPMC9339711
OpenAlexW4285730963

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.