Evidence map›Paper›PMID 36684897›Full record

ArticleFrontiers in public health2022

Medical implementation practice and its medical performance evaluation of a giant makeshift hospital during the COVID-19 pandemic: An innovative model response to a public health emergency in Shanghai, China.

Minjie Chen, Yiling Fan, Qingrong Xu, Hua Huang, Xinyi Zheng, Dongdong Xiao, Weilin Fang, Jun Qin, Junhua Zheng, Enhong Dong

Abstract 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. 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

10 authors.

Minjie ChenDepartment of Outpatient and Emergency Management, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
Yiling FanDepartment of Neurosurgery, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
Qingrong XuDepartment of Orthopaedics, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
Hua HuangDepartment of Administration, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
Xinyi ZhengDepartment of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.
Dongdong XiaoDepartment of Urology, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
Weilin FangDepartment of Urology, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
Jun QinDepartment of Gastroenterology, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
Junhua ZhengDepartment of Urology, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
Enhong DongSchool of Nursing and Health Management, Shanghai University of Medicine and Health Sciences, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In confronting the sudden COVID-19 epidemic, China and other countries have been under great pressure to block virus transmission and reduce fatalities. Converting large-scale public venues into makeshift hospitals is a popular response. This addresses the outbreak and can maintain smooth operation of a country or region's healthcare system during a pandemic. However, large makeshift hospitals, such as the Shanghai New International Expo Center (SNIEC) makeshift hospital, which was one of the largest makeshift hospitals in the world, face two major problems: Effective and precise transfer of patients and heterogeneity of the medical care teams. Methods: To solve these problems, this study presents the medical practices of the SNIEC makeshift hospital in Shanghai, China. The experiences include constructing two groups, developing a medical management protocol, implementing a multi-dimensional management mode to screen patients, transferring them effectively, and achieving homogeneous quality of medical care. To evaluate the medical practice performance of the SNIEC makeshift hospital, 41,941 infected patients were retrospectively reviewed from March 31 to May 23, 2022. Multivariate logistic regression method and a tree-augmented naive (TAN) Bayesian network mode were used. Results: We identified that the three most important variables were chronic disease, age, and type of cabin, with importance values of 0.63, 0.15, and 0.11, respectively. The constructed TAN Bayesian network model had good predictive values; the overall correct rates of the model-training dataset partition and test dataset partition were 99.19 and 99.05%, respectively, and the respective values for the area under the receiver operating characteristic curve were 0.939 and 0.957. Conclusion: The medical practice in the SNIEC makeshift hospital was implemented well, had good medical care performance, and could be copied worldwide as a practical intervention to fight the epidemic in China and other developing countries.

Indexed as

COVID-19Bayes TheoremChinaHospitalsHumansPandemicsPublic HealthRetrospective StudiesChinaCOVID-19 pandemicgiant makeshift hospitalperformanceTAN Bayesian network

Identifiers

PMID36684897
PMCPMC9853970

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.