Evidence map›Paper›PMID 32862396›Full record

ArticleFrontiers of medicine2020

Taizhou's COVID-19 prevention and control experience with telemedicine features.

Cenyi Shao, Shijian Li, Feng Zhu, Dahai Zhao, Hui Shao, Haixiao Chen, Zhiruo Zhang

Abstract read
In one paragraph

Article in Frontiers of medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
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

7 authors.

Cenyi ShaoSchool of Public Health, Shanghai Jiao Tong University, Shanghai, 200025, China.
Shijian LiDepartment of Public Health, SUNY College at Old Westbury, Old Westbury, NY, 11568, USA.
Feng ZhuTaizhou Enze Medical Center (Group), Taizhou Hospital of Wenzhou Medical University, Taizhou, 317000, China.
Dahai ZhaoSchool of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, 200025, China.
Hui ShaoTaizhou Enze Medical Center (Group), Taizhou Hospital of Wenzhou Medical University, Taizhou, 317000, China.
Haixiao ChenTaizhou Enze Medical Center (Group), Taizhou Hospital of Wenzhou Medical University, Taizhou, 317000, China. chenhx@enzemed.com.
Zhiruo ZhangSchool of Public Health, Shanghai Jiao Tong University, Shanghai, 200025, China. zhangzhiruo@sjtu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outbreak of coronavirus disease 2019 (COVID-19) has spread rapidly around the world. As of May 30, 2020, a total of 84 568 confirmed COVID-19 cases have been recorded in China, with a mortality rate of approximately 5.5%. Taizhou is a prefecture-level city in Zhejiang Province. A total of 146 cases were diagnosed in this epidemic, with a fatality rate of 0%. This condition is due to the establishment of an "Internet +" diagnosis and treatment model based on online medical application (APP), telemedicine, WeChat service, and consultation hotline in Taizhou. Taizhou led in opening the "COVID-19 Prevention and Treatment Special Line" in China, which is conducive to pre-hospital screening, suppressing social panic, and clinical support. Hospitals also carried out related online lectures and popularization of science. We summarize Taizhou's COVID-19 prevention and control experience with telemedicine features, with a view to providing reference for the control of the epidemic at home and abroad.

Indexed as

BetacoronavirusChinaCoronavirus InfectionsCOVID-19HumansInternetPandemicsPneumonia, ViralSARS-CoV-2TelemedicineCOVID-19prevention experiencetelemedicine

Identifiers

PMID32862396
PMCPMC7456200

What OpenQuestion holds

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Registered trials

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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.