Literature DB >> 33031835

Serial semiquantitative detection of SARS-CoV-2 in saliva samples.

Ming-Hui Mao1, Jing-Jing Guo2, Li-Zheng Qin3, Zheng-Xue Han1, Ya-Jie Wang4, Di Yang5.   

Abstract

Entities:  

Keywords:  COVID-19; Efficiency; Oropharyngeal; Sputum

Mesh:

Year:  2020        PMID: 33031835      PMCID: PMC7536546          DOI: 10.1016/j.jinf.2020.10.002

Source DB:  PubMed          Journal:  J Infect        ISSN: 0163-4453            Impact factor:   6.072


× No keyword cloud information.
Dear Editor, We read with interest the paper by Azzi and colleagues who report on the reliability of saliva testing for SARS-CoV2 infection. We have carried out a study to analyze the efficiency of saliva testing in monitoring the viral load of confirmed patients and get a similar conclusion. Saliva testing has been widely used in diagnosing and screening suspected COVID-19 patients due to it being easy to collect and noninvasiveness and having a high positive rate. , For inpatients, the current standard for discharge is a negative RT-qPCR result from two sets of nasopharyngeal and throat swab specimens. Multiple throat swab specimens from each patient are needed to monitor the viral load, which will not only inevitably increase the risk of cross-infection but also increase the discomfort of the patient and cause possible complications such as bleeding. There is no doubt that saliva testing can greatly improve patient comfort and reduce the risk of medical staff contracting the virus. In this study, inpatients with a diagnosis of COVID-19 provided by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) on oropharyngeal swabs in Beijing Ditan Hospital, Capital Medical University from July 10, 2020, to July 20, 2020, were included. Saliva was collected and one-step rRT-PCR was performed using the Da'an Gene 2019-nCoV Detection Kit (fluorescent PCR method, batch number: 2020032). Ct values of the ORF1a gene and N gene were also tested simultaneously. The results were considered ‘positive’ when the cycle threshold (Ct) values of FAM and VIC channels were less than 40, and there were obvious amplification curves. SPSS 24.0 and Prism 8.0 were used for statistical analyses, the difference between groups was analyzed by ANOVA and Student's t-test, P < 0.05 was considered to be statistically significant. A total of 34 patients were included (Table 1 ), and 709 nucleic acid tests, consisting of 150 saliva tests (average of 4.41±1.89 times per patient), 326 oropharyngeal swab tests (average of 9.59±2.63 times per patient), and 232 sputum tests (average of 6.82±2.61 times per patient) were performed. The Ct value of 91 saliva tests was recorded; the median Ct value of the ORF1a gene was 36.64 (range 24.10–39.90), and the median Ct value of the N gene was 33.99 (range 23.03–39.67). According to the number of weeks after hospitalization, the median Ct value of the two genes gradually increased, and the amplitude gradually decreased (Fig. 1 A, B) (see Appendix Table A1). The Ct value of most patients increased with time. However, in some patients, the Ct value first decreased with increasing time and finally increased and became negative (Fig. 1C, D). Univariate analysis found that the reduction in red blood cells significantly affected the peak value of the ORF1a gene (p = 0.027), while for the N gene, there was no significant difference (p = 0.059). In multivariate analysis, no related factors that significantly affected the Ct peak were found (see Appendix Table A2).
Table 1

Patient characteristics by severity of disease.

Asymptomatic disease (n = 6)Mild disease (n = 6)Moderate disease (n = 22)p value
Age, years37 (28–48)38.7 (21–57)44.4 (21–64)0.354
Sex
Female2 (33.3%)012 (54.5%)0.764
Male4 (66.7%)6 (100%)10 (45.5%)0.821
Presenting symptoms
Fever05 (83.3%)21 (95.5%)0.683
Chills01 (16.7%)3 (13.6%)0.898
Dyspnea004 (18.2%)0.853
Cough04 (66.7%)11 (50%)0.638
Runny nose001 (4.5%)0.792
Blocked nose02 (33.3%)3 (13.6%)0.483
Sore throat01 (16.7%)5 (22.7%)0.606
Chest discomfort000
Nausea000
Diarrhea01 (16.7%)1 (4.5%)0.64
Myalgia002 (9.1%)0.898
Malaise002 (9.1%)0.443
Loss of taste01 (16.7%)4 (18.2%)0.81
Loss of smell02 (33.3%)4 (18.2%)0.316
Antibody
IgM02 (33.3%)10 (45.5%)0.947
IgG01 (16.7%)9 (40.9%)0.537
Blood tests on admission
Total white blood cell count, × 10⁹ per L4.26 (3.39–5.33)5.85 (3.16–8.91)4.91 (2.83–10.98)0.21
Total white blood cells <4×10⁹ per L2 (33.3%)1 (16.7%)5 (22.7%)0.777
Lymphocyte count, × 10⁹ per L1.69 (1.26–2.27)1.87 (1.23–3.21)1.65 (0.58–3.38)0.091
Lymphocytes <1•0×10⁹ per L004 (18.2)0.762
red blood cell count, × 10⁹ per L4.45 (3.95–5.07)4.54 (2.54–5.28)4.89 (3.90–5.87)0.184
red blood cell count, 4×10⁹ per L1 (16. 7%)1 (16.7%)1 (4.5%)0.251
Platelet count, × 10⁹ per L202.67 (162–282)221.67 (147–364)190.74 (118–296)0.536
Platelets <100×10⁹ per L000

Data are n (%) or median (range), unless otherwise stated. For statistical analyses, ANOVA was performed for continuous variables, and chi-squared test was performed for categorical variables.

Fig. 1

Ct value from serial semiquantitative detection of SARS-CoV-2 for all 34 patients(A-B); Fig. 1A shows the N gene, and Fig. 1B shows the ORF1a gene. Datapoints denote the Ct value, and the curve indicates the median value.

Ct value of each patient after hospitalization(C-D). Fig. 1C shows the N gene, and Fig. 1D shows the ORF1a gene.

Patient characteristics by severity of disease. Data are n (%) or median (range), unless otherwise stated. For statistical analyses, ANOVA was performed for continuous variables, and chi-squared test was performed for categorical variables. Ct value from serial semiquantitative detection of SARS-CoV-2 for all 34 patients(A-B); Fig. 1A shows the N gene, and Fig. 1B shows the ORF1a gene. Datapoints denote the Ct value, and the curve indicates the median value. Ct value of each patient after hospitalization(C-D). Fig. 1C shows the N gene, and Fig. 1D shows the ORF1a gene. The total positive rate of nucleic acid detection from sputum was the highest (67.2%), followed by oropharyngeal swabs (53.1%) and saliva (36%). According to the number of weeks after hospitalization, the positive rate of nucleic acid detection from the three sample types gradually decreased, the positive rate of nucleic acid detection from saliva was 83.33% in the second week, 48% in the third week, and 0% in the seventh week (see Appendix Fig. A1). While the positive rates of nucleic acid detection from saliva, sputum, and oropharyngeal swab samples were significantly different at 3 and 6 weeks (see Appendix Table A3). The average time for nucleic acid detection results to become negative was 27.29±7.73 days for sputum samples, 27.82±12.09 days for oropharyngeal swab samples, and 24.53±13.59 days for saliva samples (see Appendix Table A4). Univariate analysis revealed that the clinical classification had a significant impact on both the time of the positive to negative conversion of sputum, oropharyngeal swab and saliva samples (p = 0.001, p = 0.001, p = 0.012), while only red blood cell reduction had a significant effect on the positive to negative conversion time of saliva samples (p = 0.032). Multivariate analysis found that clinical classification had a significant impact on the time of sputum and oropharyngeal swab samples to become negative (p = 0.007, p = 0.002) (see Appendix Table A5). Taking sputum specimens as an example, the average time for test results to become negative in asymptomatic patients was 14 days, while the average times for patients with mild and moderate disease were 25 days and 32 days, respectively. Using the sputum-oropharyngeal swab test results as a reference, that is, a negative result was when the nucleic acid results of both specimen types were negative, and if one of the samples had a positive test result, it is considered a positive result. The efficiency of saliva single detection method and saliva-sputum combined detection method was tested. The results showed that the total sensitivity, efficiency and specificity of saliva single detection method were 74.10%, 83.90% and 94.40%, respectively. The overall sensitivity, efficiency and specificity of saliva-sputum combined detection method were 93.40%, 94.00% and 95.20%, respectively (see Appendix Table A6). Studies have conducted research on the effectiveness of saliva to diagnosis COVID-19, and the overall efficiency rate differs, ranging from 30.7% to 100%. , 5, 6, 7, 8, 9 total efficiency and specificity of the saliva detection method in this study were higher than those of the sputum and oropharyngeal swab detection methods (83.90% and 94.40%, respectively). The saliva-sputum combined diagnosis is more effective, with a total efficiency and specificity of 94.00% and 95.20%, respectively. In addition, to verify the specificity of saliva testing, the saliva and oropharyngeal swab samples of 50 patients were tested, and the results of all of these patients were negative. However, only 34 patients were included and it was not possible to collect all three sample types from every patient at the same time. We also fails to obtain the true copy of the virus, that is, the viral copies per ml of sample. Nonetheless, our results show that combined sputum-saliva detection is a reliable method for monitoring the viral load of patients recovering from COVID-19.

Funding

None.

Role of the funding source

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

Data directly supporting the study results can be found in Beijing Ditan Hospital in paper form.

Declaration of Competing Interest

None.
  9 in total

1.  Saliva as a diagnostic specimen for testing respiratory virus by a point-of-care molecular assay: a diagnostic validity study.

Authors:  K K W To; C C Y Yip; C Y W Lai; C K H Wong; D T Y Ho; P K P Pang; A C K Ng; K-H Leung; R W S Poon; K-H Chan; V C C Cheng; I F N Hung; K-Y Yuen
Journal:  Clin Microbiol Infect       Date:  2018-06-12       Impact factor: 8.067

2.  Additional molecular testing of saliva specimens improves the detection of respiratory viruses.

Authors:  Kelvin Kw To; Lu Lu; Cyril Cy Yip; Rosana Ws Poon; Ami My Fung; Andrew Cheng; Daniel Hk Lui; Deborah Ty Ho; Ivan Fn Hung; Kwok-Hung Chan; Kwok-Yung Yuen
Journal:  Emerg Microbes Infect       Date:  2017-06-07       Impact factor: 7.163

3.  Saliva as a Noninvasive Specimen for Detection of SARS-CoV-2.

Authors:  Eloise Williams; Katherine Bond; Bowen Zhang; Mark Putland; Deborah A Williamson
Journal:  J Clin Microbiol       Date:  2020-07-23       Impact factor: 5.948

4.  Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study.

Authors:  Kelvin Kai-Wang To; Owen Tak-Yin Tsang; Wai-Shing Leung; Anthony Raymond Tam; Tak-Chiu Wu; David Christopher Lung; Cyril Chik-Yan Yip; Jian-Piao Cai; Jacky Man-Chun Chan; Thomas Shiu-Hong Chik; Daphne Pui-Ling Lau; Chris Yau-Chung Choi; Lin-Lei Chen; Wan-Mui Chan; Kwok-Hung Chan; Jonathan Daniel Ip; Anthony Chin-Ki Ng; Rosana Wing-Shan Poon; Cui-Ting Luo; Vincent Chi-Chung Cheng; Jasper Fuk-Woo Chan; Ivan Fan-Ngai Hung; Zhiwei Chen; Honglin Chen; Kwok-Yung Yuen
Journal:  Lancet Infect Dis       Date:  2020-03-23       Impact factor: 25.071

5.  A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster.

Authors:  Jasper Fuk-Woo Chan; Shuofeng Yuan; Kin-Hang Kok; Kelvin Kai-Wang To; Hin Chu; Jin Yang; Fanfan Xing; Jieling Liu; Cyril Chik-Yan Yip; Rosana Wing-Shan Poon; Hoi-Wah Tsoi; Simon Kam-Fai Lo; Kwok-Hung Chan; Vincent Kwok-Man Poon; Wan-Mui Chan; Jonathan Daniel Ip; Jian-Piao Cai; Vincent Chi-Chung Cheng; Honglin Chen; Christopher Kim-Ming Hui; Kwok-Yung Yuen
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

6.  Detection of SARS-CoV-2 in saliva and characterization of oral symptoms in COVID-19 patients.

Authors:  Lili Chen; Jiajia Zhao; Jinfeng Peng; Xiaoshuang Li; Xuliang Deng; Zhi Geng; Zhenyu Shen; Fengyuan Guo; Qianwen Zhang; Yang Jin; Lin Wang; Songlin Wang
Journal:  Cell Prolif       Date:  2020-10-19       Impact factor: 6.831

7.  Consistent Detection of 2019 Novel Coronavirus in Saliva.

Authors:  Kelvin Kai-Wang To; Owen Tak-Yin Tsang; Cyril Chik-Yan Yip; Kwok-Hung Chan; Tak-Chiu Wu; Jacky Man-Chun Chan; Wai-Shing Leung; Thomas Shiu-Hong Chik; Chris Yau-Chung Choi; Darshana H Kandamby; David Christopher Lung; Anthony Raymond Tam; Rosana Wing-Shan Poon; Agnes Yim-Fong Fung; Ivan Fan-Ngai Hung; Vincent Chi-Chung Cheng; Jasper Fuk-Woo Chan; Kwok-Yung Yuen
Journal:  Clin Infect Dis       Date:  2020-07-28       Impact factor: 9.079

8.  Saliva is a reliable tool to detect SARS-CoV-2.

Authors:  Lorenzo Azzi; Giulio Carcano; Francesco Gianfagna; Paolo Grossi; Daniela Dalla Gasperina; Angelo Genoni; Mauro Fasano; Fausto Sessa; Lucia Tettamanti; Francesco Carinci; Vittorio Maurino; Agostino Rossi; Angelo Tagliabue; Andreina Baj
Journal:  J Infect       Date:  2020-04-14       Impact factor: 6.072

9.  Two cases of COVID-19 with positive salivary and negative pharyngeal or respiratory swabs at hospital discharge: A rising concern.

Authors:  Lorenzo Azzi; Giulio Carcano; Daniella Dalla Gasperina; Fausto Sessa; Vittorio Maurino; Andreina Baj
Journal:  Oral Dis       Date:  2020-05-11       Impact factor: 4.068

  9 in total
  1 in total

1.  Salivary SARS-CoV-2 antigen rapid detection: A prospective cohort study.

Authors:  Daniela Basso; Ada Aita; Andrea Padoan; Chiara Cosma; Filippo Navaglia; Stefania Moz; Nicole Contran; Carlo-Federico Zambon; Anna Maria Cattelan; Mario Plebani
Journal:  Clin Chim Acta       Date:  2021-02-21       Impact factor: 3.786

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.