Back

Clinical diagnosis of 8274 samples with 2019-novel coronavirus in Wuhan

Wang, M.; Wu, Q.; Xu, W.; Qiao, B.; Wang, J.; Zheng, H.; Jiang, S.; Mei, J.; Wu, Z.; Deng, Y.; Zhou, F.; Wu, W.; Zhang, Y.; Lv, Z.; Huang, J.; Guo, X.; Feng, L.; Xia, Z.; Li, D.; Xu, Z.; Liu, T.; Zhang, P.; Tong, Y.; Li, Y.

2020-02-13 infectious diseases
10.1101/2020.02.12.20022327 medRxiv
Show abstract

Background2019-Novel coronavirus (2019-nCoV) outbreaks create challenges for hospital laboratories because thousands of samples must be evaluated each day. Sample types, interpretation methods, and corresponding laboratory standards must be established. The possibility of other infections should be assessed to provide a basis for clinical classification, isolation, and treatment. Accordingly, in the present study, we evaluated the testing methods for 2019-nCoV and co-infections. MethodsWe used a fluorescence-based quantitative PCR kit urgently distributed by the Chinese CDC to detect 8274 close contacts in the Wuhan region against two loci on the 2019-nCoV genome. We also analyzed 613 patients with fever who underwent multiple tests for 13 respiratory pathogens; 316 subjects were also tested for 2019-nCoV. FindingsAmong the 8274 subjects, 2745 (33.2%) had 2019-nCoV infection; 5277 (63.8%) subjects showed negative results in the 2019-nCoV nucleic acid test (non-2019-nCoV); and 252 cases (3.0%) because only one target was positive, the diagnosis was not definitive. Eleven patients who originally had only one positive target were re-examined a few days later; 9 patients (81.8%) were finally defined as 2019-nCoV-positive, and 2 (18.2%) were finally defined as negative. The positive rates of nCoV-NP and nCovORF1ab were 34.7% and 34.7%, respectively. nCoV-NP-positive only and nCovORF1ab-positive cases accounted for 1.5% and 1.5%, respectively. In the 316 patients with multiple respiratory pathogens, 104 were positive for 2019-nCov and 6/104 had co-infection with coronavirus (3/104), influenza A virus (2/104), rhinovirus (2/104), and influenza A H3N2 (1/104); the remaining 212 patients had influenza A virus (11/202), influenza A H3N2 (11/202), rhinovirus (10/202), respiratory syncytial virus (7/202), influenza B virus (6/202), metapneumovirus (4/202), and coronavirus (2/202). InterpretationClinical testing methods for 2019-nCoV require improvement. Importantly, 5.8% of 2019-nCoV infected and 18.4% of non-2019-nCoV-infected patients had other pathogen infections. It is important to treat combined infections and perform rapid screening to avoid cross-contamination of patients. A test that quickly and simultaneously screens as many pathogens as possible is needed. FundingNo founding was received Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for articles published up to January 31, 2020 using the keywords "2019 novel coronavirus" or "2019-nCoV". No published study on the characteristics of 2019-nCoV tests or 2019-nCoV co-infections was found. We only noted recent laboratory findings for other tests of patients infected with 2019-nCoV. Added value of this studyPositive detection of nCoV-NP or nCovORF1ab is presented, and individuals with/without 2019-nCoV infections or with inconclusive results were identified. Patients with inconclusive results may be diagnosed with 2019-nCoV infection or found to be negative for the infection after resampling and retesting in the next few days. Approximately 5.8% of the subjects diagnosed with 2019-nCoV had co-infection. Implications of all the available evidenceManagement of the population showing inconclusive results should be given attention; additionally, such results can be minimized by improving the sampling, sample pretreatment, and testing methodologies. When diagnosing 2019-nCoV subjects, the possibility of co-infection should be considered. Finally, better clinical detection methods are needed to simultaneously screen as many pathogens as possible.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Journal of Clinical Virology
62 papers in training set
Top 0.1%
23.2%
2
Journal of Clinical Microbiology
120 papers in training set
Top 0.1%
23.2%
3
Clinical Infectious Diseases
231 papers in training set
Top 1%
4.4%
50% of probability mass above
4
Journal of Medical Virology
137 papers in training set
Top 1%
3.2%
5
PLOS ONE
4510 papers in training set
Top 43%
3.0%
6
Journal of Infection
71 papers in training set
Top 0.6%
2.8%
7
European Journal of Clinical Microbiology & Infectious Diseases
15 papers in training set
Top 0.1%
2.1%
8
The Journal of Infectious Diseases
182 papers in training set
Top 2%
2.1%
9
BMJ Open
554 papers in training set
Top 8%
2.1%
10
Diagnostic Microbiology and Infectious Disease
21 papers in training set
Top 0.1%
1.9%
11
Clinical Chemistry
22 papers in training set
Top 0.4%
1.7%
12
Open Forum Infectious Diseases
134 papers in training set
Top 1%
1.7%
13
Microbiology Spectrum
435 papers in training set
Top 2%
1.7%
14
BMJ
49 papers in training set
Top 0.7%
1.4%
15
Journal of Medical Microbiology
20 papers in training set
Top 0.3%
1.4%
16
Clinical Microbiology and Infection
60 papers in training set
Top 0.8%
1.3%
17
Diagnostics
48 papers in training set
Top 1%
1.3%
18
Emerging Infectious Diseases
103 papers in training set
Top 2%
1.1%
19
BMC Infectious Diseases
118 papers in training set
Top 4%
1.1%
20
International Journal of Infectious Diseases
126 papers in training set
Top 3%
1.0%
21
Eurosurveillance
80 papers in training set
Top 1%
0.8%
22
Frontiers in Medicine
113 papers in training set
Top 6%
0.8%
23
EClinicalMedicine
21 papers in training set
Top 1%
0.7%
24
Heliyon
146 papers in training set
Top 8%
0.7%
25
The Lancet Microbe
43 papers in training set
Top 1%
0.7%
26
The FASEB Journal
175 papers in training set
Top 4%
0.7%
27
BMC Microbiology
35 papers in training set
Top 2%
0.7%
28
Annals of Internal Medicine
27 papers in training set
Top 1%
0.5%