Evidence map›Paper›PMID 32948121›Full record

ArticleBMC infectious diseases2020

Differential diagnosis for suspected cases of coronavirus disease 2019: a retrospective study.

Qiong Chi, Xinjian Dai, Xiangao Jiang, Lefei Zhu, Junyan Du, Yuxi Chen, Jiyang Zheng, Jianping Huang

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2020. 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
0.3field-weighted citation impact, top 30% 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, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. A simplified alternative diagnostic algorithm for SARS-CoV-2 suspected symptomatic patients and confirmed close contacts (asymptomatic): A consensus of Latin American experts.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
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  5. Review
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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

8 authors at 1 institution in 1 country.

Qiong ChiDepartment of Respiratory and Critical Care Medicine, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.
Xinjian DaiDepartment of Respiratory and Critical Care Medicine, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.
Xiangao JiangDepartment of Infectious Diseases, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.
Lefei ZhuDepartment of Endocrinology, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.
Junyan DuDepartment of Gastroenterology, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.
Yuxi ChenDepartment of Emergency, Wenzhou Central Hospital, Wenzhou, Zhejiang, China.
Jiyang ZhengDepartment of Respiratory and Critical Care Medicine, Wenzhou Central Hospital, Wenzhou, Zhejiang, China. drzheng6562@163.com.
Jianping HuangDepartment of Neurology, Wenzhou Central Hospital, Wenzhou, Zhejiang, China. 164670892@qq.com.
Wenzhou Central Hospital · CN

Funding

Wenzhou Science and Technology Key Problem Program ZY202004
6 · The paper itself

Abstract

backgroundSince December 2019, the coronavirus disease 2019 (COVID-19) has infected more than 12,322,000 people and killed over 556,000 people worldwide. However, Differential diagnosis remains difficult for suspected cases of COVID-19 and need to be improved to reduce misdiagnosis.

methodsSixty-eight cases of suspected COVID-19 treated in Wenzhou Central Hospital from January 21 to February 20, 2020 were divided into confirmed and COVID-19-negative groups based on the results of real-time reverse transcriptase polymerase chain reaction (RT-PCR) nucleic acid testing of the novel coronavirus in throat swab specimens to compare the clinical symptoms and laboratory and imaging results between the groups.

resultsAmong suspected patients, 17 were confirmed to COVID-19-positive group and 51 were distinguished to COVID-19-negative group. Patients with reduced white blood cell (WBC) count were more common in the COVID-19-positive group than in the COVID-19-negative group (29.4% vs 3.9%, P = 0.003). Subsequently, correlation analysis indicated that there was a significant inverse correlation existed between WBC count and temperature in the COVID-19-positive patients (r = - 0.587, P = 0.003), instead of the COVID-19-negative group. But reduced lymphocyte count was no different between the two groups (47.1% vs 25.5%, P = 0.096). More common chest imaging characteristics of the confirmed COVID-19 cases by high-resolution computed tomography (HRCT) included ground-glass opacities (GGOs), multiple patchy shadows, and consolidation with bilateral involvement than COVID-19-negative group (82.4% vs 31.4%, P = 0.0002; 41.2% vs 17.6% vs P = 0.048; 76.5% vs 43.1%, P = 0.017; respectively). The rate of clustered infection was higher in COVID-19-positive group than COVID-19-negative group (64.7% vs 7.8%, P = 0.001). Through multiplex PCR nucleic acid testing, 2 cases of influenza A, 3 cases of influenza B, 2 cases of adenovirus, 2 cases of Chlamydia pneumonia, and 7 cases of Mycoplasma pneumoniae were diagnosed in the COVID-19-negative group.

conclusionsWBC count inversely correlated with the severity of fever, GGOs, multiple patchy shadows, and consolidation in chest HRCT and clustered infection are common but not specific features in the confirmed COVID-19 group. Multiplex PCR nucleic acid testing helped differential diagnosis for suspected COVID-19 cases.

Indexed as

AdultBetacoronavirusChinaCoronavirus InfectionsCOVID-19Diagnosis, DifferentialFemaleFeverHumansInfluenza, HumanLeukocyte CountMaleMiddle AgedMultiplex Polymerase Chain ReactionPandemicsPneumonia, ViralConfirmed casesCOVID-19Differential diagnosisSuspected cases

Identifiers

PMID32948121
PMCPMC7498741
OpenAlexW3087081077

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.