nach oben

BMC Infectious Diseases

Erschienen in:

Open Access 01.12.2020 | COVID-19 | Research article

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

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

Erschienen in: BMC Infectious Diseases | Ausgabe 1/2020

Abstract

Background

Since 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.

Methods

Sixty-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.

Results

Among 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.

Conclusions

WBC 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.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

COVID-19

Coronavirus disease 2019

Computed tomography

GGOs

Ground-glass opacities

HRCT

High-resolution computed tomography

MDT

Multidisciplinary collaborative diagnosis and treatment

Not applicable

RT-PCR

Reverse transcriptase polymerase chain reaction

SARS-CoV

Coronaviruses

SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2

WBC

White blood cell

WHO

World Health Organization

Background

Since December 2019, the epidemic of pneumonia caused by novel coronavirus in China, has continued to progress [1], having now infected more than 12,322,000 people and killed over 556,000 people worldwide [2]. On February 11, 2020, The International Committee on Taxonomy of Viruses officially named this severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the World Health Organization (WHO) named the disease coronavirus disease 2019 (COVID-19) [3]. Phylogenetic analysis revealed that SARS-CoV-2 falls into the genus betacoronavirus, which includes coronaviruses (SARS-CoV, bat SARS-like CoV, and others) discovered in humans, bats, and other wild animals [4]. On March 11, 2020, the WHO also designated COVID-19 a pandemic [2]. According to epidemiological investigations, the general population is susceptible to SARS-CoV-2, which has the possible route of transmission via droplets, fecal matter, and contact [5]. Because symptoms overlap significantly with other respiratory infections like influenza, diagnosis remains difficult.

Wenzhou had hundreds of confirmed imported cases of COVID-19 and even more suspected cases. Measures to more rapidly and accurately diagnose suspected cases of COVID-19 are challenges that urgently need to be addressed by clinicians. We therefore conducted this study to investigate the clinical characteristics of suspected cases of COVID-19 and to improve the differential diagnosis for COVID-19, thus reduce misdiagnosis.

Methods

Patients and data collection

We retrospectively collected the clinical data, including demographics, clinical manifestations, laboratory and radiological findings and contact history of suspected COVID-19 cases in isolation ward (single rooms) of Wenzhou Central Hospital from January 19, 2020 to February 20, 2020. The diagnostic criteria [6] of suspected cases were: individuals matching any one of the criteria for epidemiological history and any 2 of the clinical manifestations, or individuals matching any 3 of the clinical manifestations when there was no definitive epidemiological history. Epidemiological history included (1) history of travel or residence in Wuhan within 14 days before the disease onset; (2) history of contact with patients confirmed with COVID-19 within 14 days before the disease onset; (3) history of contact with individuals with respiratory symptoms who came from Wuhan or communities with reported COVID-19 cases within 14 days before the disease onset; and (4) clustered disease, meaning ≥2 cases with fever and/or respiratory symptoms. Clinical manifestations included (1) fever, (2) chest imaging showing multiple small patchy shadows and interstitial changes, particularly in the lung periphery, during the early stages, which progressed to multiple ground-glass opacities (GGOs), infiltrates, and consolidation; and (3) normal or reduced total white blood cell (WBC) count or reduced lymphocyte count in the early stages. Criteria to confirm or rule out the diagnosis of COVID-19 was as follows [6]: Confirmed COVID-19 cases: positive real-time reverse transcriptase polymerase chain reaction (RT-PCR) SARS-CoV-2 nucleic acid testing or viral gene sequencing showing high sequence homology to known gene sequences of SARS-CoV-2; COVID-19-negative cases: suspected cases with 2 consecutive negative results of respiratory pathogen nucleic acid testing (sampling time interval at least 1 day). In the same period, these samples were analyzed by multiplex PCR named GeXP assay (multiplex PCR combined with automated capillary electrophoresis) for 13 common respiratory pathogens including Influenza A (Flu A), Influenza B (Flu B), Influenza A H1N1 pdm09 (09H1), influenza H3N2 (H3), human para-influenza virus (HPIV), respiratory syncytial virus (RSV), rhinovirus (HRV), adenovirus (ADV), human metapneumovirus (HMPV), human bocavirus (HBoV), human coronavirus (HCoV), Chlamydia (Ch) and Mycoplasma pneumoniae (Mp) [7].

Statistical analysis

Characteristics of patients were summarized using descriptive statistics. The continuous variables were presented as mean ± standard deviation (Mean ± SD), and the comparison between groups was analyzed by independent sample t-test. Categorical variables were expressed as the counts and percentages of patients in each category, and the group comparisons were performed using Chi-square test or Fisher’s Exact test or Chi-square. P < 0.05 was considered statistically significant. The SPSS 22.0 software (IBM SPSS Inc., Chicago, IL) was used for statistical analysis in this study.

Results

Sixty-eight suspected COVID-19 cases were recruited retrospectively to our study from January 21 to February 20, 2020. Among them, 17 were confirmed to be COVID-19 positive and 51 were COVID-19 negative. The clinical symptoms were no difference between two groups (Table 1).

Table 1

Demographics and clinical manifestations of suspected cases of COVID-19

	Confirmed COVID-19 group n = 17	COVID-19-negative group n = 51	P value
Male, n (%)	9 (52.9%)	34 (66.7%)	0.309
Age, mean (SD),year	53.5 (13.4)	41.3 (17.9)	0.012
Medical history, n (%)
Hypertension	2 (11.8%)	5 (9.8%)	0.818
Diabetes	1 (5.9%)	2 (3.9%)	NA
Coronary heart disease	1 (5.9%)	2 (3.9%)	NA
Chronic pulmonary diseases	0	2 (3.9%)	NA
Malignant tumors	0	1 (2.0%)	NA
Epidemiological history	11 (64.7%)	6 (11.8%)	0
Clustered infection, n (%)	11 (64.7%)	4 (7.8%)	< 0.001
Familial clustering	6 (35.3%)	2 (3.9%)	0.001
shopping center Clustering	5 (29.4%)	2 (3.9%)	0.003
Clinical manifestations, n (%)
Fever	14 (82.4%)	38 (74.5%)	0.509
37–38 °C	6 (35.3%)	19 (37.3%)	0.885
38–39 °C	5 (29.4%)	14 (27.5%)	0.876
≥ 39 °C	3 (17.6%)	5 (9.8%)	0.385
Cough	12 (70.6%)	27 (52.9%)	0.203
Fatigue	7 (41.2%)	12 (23.5%)	0.160
Expectoration	5 (29.4%)	13 (25.5%)	0.751
Others
Sore through	3 (17.6%)	5 (9.8%)	0.385
Intolerance of cold	3 (17.6%)	9 (17.6%)	1.0
Chest tightness	2 (11.8%)	5 (9.8%)	0.818
Dyspnea	2 (11.8%)	3 (5.9%)	0.421
Palpitations	1 (5.9%)	3 (5.9%)	1.0
Diarrhea	1 (5.9%)	2 (3.9%)	NA
Nausea and vomiting	1 (5.9%)	2 (3.9%)	NA
Hemoptysis	0	2 (3.9%)	NA

COVID-19 coronavirus disease 2019, NA not applicable

Laboratory tests, chest imaging, and nucleic acid testing are shown in Table 2. Patients with reduced WBC count were more common in the confirmed COVID-19 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 (Fig. 1). But reduced lymphocyte count was not found to be significantly 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 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). Bronchial wall thickening (9.8%) and reversed halo signs (2.0%) only saw in Chest HRCT of the COVID-19-negative group. 13 (76.5%) SARS-CoV-2 nucleic positive were identified in the first test of RT-PCR. 17.6% patients appeared negative results in the first round of test but turned to positive in the second round of test. Among the COVID-19-negative cases, 1 patient (2.0%) had a weakly positive result in the first viral nucleic acid test, but had negative results in the two following re-tests. Among the patients in the COVID-19-negative group, multiplex PCR testing showed 2 (3.9%) cases of influenza A with characteristic scattered and patchy shadows and nodular shadows in both lungs (Fig. 2a), 3 (5.9%) cases of influenza B with characteristic subpleural patchy shadows in chest CT (Fig. 2b), 2(3.9%) cases of adenovirus with characteristic consolidation near the pleura in chest CT (Fig. 2c), 2(3.9%) cases of Chlamydia pneumoniae with characteristic multiple GGOs and consolidations in both lungs (Fig. 2d), and 7(13.7%) cases of Mycoplasma pneumoniae infections with characteristic bronchial wall thickening, centrilobular nodules, GGOs and consolidation in Chest HRCT (Fig. 3h & i). No co-infections was observed in the COVID-19-positive or COVID-19-negative patients.

Table 2

Laboratory tests, chest imaging, and nucleic acid testing of suspected cases of COVID-19

	Confirmed COVID-19 group n = 17	COVID-19-negative group n = 51	P value
White blood cell count, mean (SD), ×10⁹/L	5.27 ± 2.08	6.73 ± 1.94	0.010
< 4, n (%)	5 (29.4%)	2 (3.9%)	0.003
4–10, n (%)	12 (70.6%)	47 (92.2%)	0.023
> 10, n (%)	0	2 (3.9%)	NA
Lymphocyte count, mean (SD), ×10⁹/L	1.35 ± 0.83	1.63 ± 0.81	0.224
< 1.1, n (%)	8 (47.1%)	13 (25.5%)	0.096
≥ 1.1, n (%)	9 (52.9%)	38 (74.5%)	0.096
Hemoglobin concentration, mean (SD), (g//L)	135.18 ± 17.02	138.66 ± 20.33	0.528
< 120, n (%)	3 (17.6%)	7 (13.7%)	0.693
≥ 120, n (%)	14 (82.4%)	44 (86.3%)	0.693
Platelet count, mean (SD), (×10⁹/L)	198.41 ± 92.02	217.52 ± 72.42	0.384
< 100, n (%)	1 (5.9%)	2 (2.9%)	NA
≥ 100, n (%)	16 (94.1%)	49 (96.1%)	NA
C-reactive protein, mean (SD), (mg/L)	29.27 ± 31.30	17.25 ± 23.31	0.097
Chest CT, n (%)
Ground-glass opacities	14 (82.4%)	16 (31.4%)	0.0002
Consolidation	7 (41.2%)	9 (17.6%)	0.048
Patchy shadows	13 (76.5%)	22 (43.1%)	0.017
Grid-like images	3 (17.6%)	2 (3.9%)
Bronchial wall thickening	0	5 (9.8)	NA
Reversed halo sign	0	1 (2.0)	NA
Bilateral pulmonary involvement	14 (82.4%)	8 (15.7%)	< 0.001
SARS-CoV-2 nucleic acid testing, n (%)
Positive in the first test	13 (76.5%)	0
Positive in the second test	3 (17.6%)	0
Weak positive in the first test	1 (5.9%)	0
Suspected positive in the first test	1 (5.9%)	1 (2.0%)
Multiplex PCR, n (%)
Influenza A	0	2 (3.9%)
Influenza B	0	3 (5.9%)
Adenovirus	0	2 (3.9%)
Chlamydia pneumoniae	0	2 (3.9%)
Mycoplasma pneumoniae	0	7 (13.7%)

COVID-19 coronavirus disease 2019, CT computed tomography, NA not applicable, RT-PCR reverse transcriptase polymerase chain reaction, SARS-CoV-2 severe acute respiratory syndrome coronavirus

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). The first familial cluster of COVID-19 involved transmission from a wife (who visited a physician due to 10 days of fever; she was confirmed to be SARS-CoV-2 positive in the second round of nucleic acid testing) to her husband (fatigue for a week and a day of fever; positive result on first SARS-CoV-2 nucleic acid test). Chest HRCTs showed a grid images in the inferior lobes of both lungs, especially obvious in the lung periphery (Fig. 3a & b). In the second cluster, the wife had a positive result in the first SARS-CoV-2 nucleic acid testing after 15 days of fever and her chest computed tomography (CT) showed multiple GGOs near the bilateral pleura. Her husband had a negative result in the first SARS-CoV-2 nucleic acid testing but a positive result upon the re-test on the first day of his fever and his chest CT showed a single GGO in the left lower lung near the pleura (Fig. 3c & d). The third familial cluster involved transmission from husband (fever and cough for 13 days; positive result in the first SARS-CoV-2 nucleic acid testing) to his wife who remained asymptomatic (weak positive result in the first SARS-CoV-2 nucleic acid testing, and a positive result upon re-testing). The husband’s chest CT showed multiple GGOs and consolidation near the pleura of the right lung, while the wife’s chest CT showed patchy shadows near the pleura in the right lung (Fig. 3e & f). However, their son had no symptoms and normal WBC and lymphocyte counts with multiple GGOs and patchy shadows in his left lung (Fig. 3g). After three negative viral nucleic testing of throat swabs or sputum, he was diagnosed COVID-19-negative. One familial cluster occurred in the COVID-19-negative group (father and son). Both were diagnosed with Mycoplasma pneumonia after multiplex PCR nucleic acid testing with hyperpyrexia and cough.

There were two noninfectious cases in COVID-19-negative group. One is 28-year-old previously healthy male patient who was diagnosed suspected case of COVID-19 due to cough, fever, increasing chest tightness gradually and GGOs and consolidation images in anterior basal segment of right lower lung of chest CT. Finally, Deep venous ultrasound showed right femoral vein thrombosis and computed tomography pulmonary angiogram (CTPA) showed multiple pulmonary embolisms in both lungs (Fig. 4a & b). His medical history showed often long-term sedentary position in last 3 months for a test, and intermittent pain in his right lower extremity. The other suspected case had cough, fever, dyspnea and rashes symptoms with interstitial abnormalities in his both lungs (Fig. 4c & d). This patient was eventually diagnosed as dermatomyositis with pulmonary involvement through testing of the spectrum of idiopathic inflammatory myopathies as.

Discussion

As cases of COVID-19 increase in number worldwide, clinicians are struggling to diagnose new cases quickly enough to implement appropriate isolation measures. This is particularly difficult given how closely symptoms of COVID-19 match other common viral respiratory infections, including influenza. The aim of this study was to summarize the diagnostic features of suspected cases of COVID-19 in our hospital to help improve differential diagnosis, reduce misdiagnosis in future. Results of our study suggest that pneumonia in COVID-19 patients and pneumonia caused by other pathogens (eg, influenza viruses, adenovirus, and Mycoplasma) are difficult to distinguish based on their clinical manifestations, which included fever, cough, and fatigue in our study. Rarer clinical manifestations, such as expectoration, sore throat, intolerance of cold, shivering, chest tightness, dyspnea, palpitation, and diarrhea, were also common to both COVID-19 and other respiratory pathogens, which was similar to the results from previous studies [8, 9].

Routine blood tests of COVID-19-positive patients showed that the WBC count was reduced, inversely correlating with the severity of fever, instead of COVID-19-negative patients. This may contribute to the differential diagnosis of suspected cases. Approximately half (47.1%) of COVID-19-positive patients had reduced lymphocyte count; therefore, a reduced lymphocyte count in suspected cases of COVID-19 suggests the possibility of COVID-19. C-reactive protein of the COVID-19-positive patients was elevated, but was not significant for differential diagnosis. Most COVID-19-positive cases had bilateral pulmonary involvement with GGOs, multiple patchy shadows, and consolidation in their chest upon HRCT imaging, which may be helpful for differential diagnosis. However, these Chest HRCT imaging including patchy shadows, nodular shadows and grid-like also seen in the pneumonia caused by Influenza A virus, influenza B virus and adenovirus, consistent with the previous reports [10, 11].

Clustered occurrence is one of the epidemiological criteria for the diagnosis of COVID-19 [12, 13]. Our study also shows 6 out of 17 cases were clustered, but clustering is not unique to COVID-19. Mycoplasma pneumonia can also occur in cluster with GGOs in chest CT. In this study, the 7 patients diagnosed with Mycoplasma pneumonia had a mean age of 29.5 years. Three of the patients were younger than 20 years old. Bronchial wall thickening, characteristic change of Mycoplasma pneumonia, in the chest HRCT of young adults may help distinguish Mycoplasma pneumonia from COVID-19.

Additionally, we recommend performing multiplex PCR nucleic acid testing using throat swabs or sputum. It should be noted that these results may be related to factors such as sampling quality, specimen preservation, and different nasopharyngeal virus concentrations at different stages of the disease [14]. Using multiplex PCR, we distinguish influenza A virus, influenza B virus, Adenovirus, Chlamydia pneumoniae, Mycoplasma pneumoniae and so on from suspected cases easily. In this study, no patient with COVID-19 was found co-infection with other respiratory pathogen(s). Recent report showed that rate of co-infection between SARS-CoV-2 and other respiratory pathogens reached 20.7% in northern California, USA. So, testing of SARS-CoV-2 should been done for patients with non–SARS-CoV-2 respiratory pathogens in high incidence of COVID-19 region [15]. The detection of non–SARS-CoV-2 respiratory pathogens by multiplex PCR may help to assess individual the risk of COVID-19 in areas of low transmission [16]. Because of the highly infectious nature of SARS-CoV2, the suspected COVID-19 cases were all isolated and monitored in a single-person single-room isolation ward. Although communication with healthcare professionals was limited, a detailed medical history should not be neglected. Therefore, it is important to remain open to all causes of lung pathology, including non-infectious causes like pulmonary embolism. For suspected COVID-19 cases, a comprehensive multidisciplinary collaborative diagnosis and treatment (MDT) mechanism should be established. Relevant departments including respiratory medicine, infectious diseases, and radiology should collaborate closely when COVID-19 is suspected to avoid misdiagnosis. Positive result of SARS-CoV-2 nucleic acid testing remains the gold standard for the diagnosis of COVID-19. However, highly suspicious cases with false negative viral nucleic acid testing results should have chest CT and consecutive viral nucleic acid testing in different specimens collected from multiple regions of the body (eg, sputum, throat swabs, blood, urine, and feces) [17]. These patients should also have the tests of serum SARS-CoV-2 specific-IgM and IgG antibodies [18] to improve the diagnosis rate.

This study has some limitations. Because COVID-19 was managed as Class A infectious disease, this study only performed routine blood tests, C-reactive protein, chest HRCT, throat swab SARS-CoV-2 nucleic acid testing, but not blood biochemical tests in the patients. As a result, we cannot comment on co-morbidities in our population. Additionally, the number of cases in this study was limited by the fact that COVID-19 is an emerging disease, and our findings need to be further verified by a large-scale study.

Conclusions

The clinical characteristics of patients with confirmed diagnosis of COVID-19 were similar to those negative cases. However, WBC 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.

Acknowledgements

We would like to thank the medical staffs in the isolation ward of Wenzhou Central Hospital for their providing information about patients. We also thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

This study was approved by the Institutional Review Board (IRB) of Wenzhou Central Hospital (No. L2020–01-054). Written consent was waived by the IRB as described previously. This study has been approved by the ethics committee of Wenzhou Central Hospital. The data used in this study was anonymised before analysis.

Not applicable.

Competing interests

The authors declare that they have no competing interests to disclose.

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506. https://doi.org/10.1016/s0140-6736(20)30183-5.CrossRefPubMedPubMedCentral

WHO. Situation report – 173: Coronavirus disease (COVID-2019). https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200711-covid-19-sitrep-173.pdf?sfvrsn=949920b4_2 (Accessed 12 July 2020).

WHO. Situation report – 22: Novel coronavirus (2019-nCoV). https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200211-sitrep-22-ncov.pdf?sfvrsn=fb6d49b1_2, 2020 (Accessed 11 Feb 2020).

Tan W, Zhao X, Ma X, Wang W, Niu P, Xu W, et al. A novel coronavirus genome identified in a cluster of pneumonia cases — Wuhan, China 2019−2020, China. CDC Weekly. 2020;2(4):61–2 http://weekly.chinacdc.cn/en/article/id/a3907201-f64f-4154-a19e-4253b453d10c.CrossRef

Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020. https://doi.org/10.1056/NEJMoa2002032.

National Health Commission of the People’s Republic of China, Diagnosis and treatment program of the novel coronavirus pneumonia (trial edition 4). 2020 http://www.gov.cn/zhengce/zhengceku/2020-01/28/5472673/files/0f96c10cc09d4d36a6f9a9f0b42d972b. (Accessed 20 Apr 2020).

Wang L, Feng Z, Zhao M, Yang S, Yan X, Guo W, et al. A comparison study between GeXP-based multiplex-PCR and serology assay for Mycoplasma pneumoniae detection in children with community acquired pneumonia. BMC Infect Dis. 2017;17(1):518. https://doi.org/10.1186/s12879-017-2614-3.CrossRefPubMedPubMedCentral

Xu XW, Wu XX, Jiang XG, Xu KJ, Ying LJ, Ma CL, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series [published correction appears in BMJ. 2020 Feb 27;368:m792]. BMJ. 2020;368:m606. https://doi.org/10.1136/bmj.m606.CrossRefPubMedPubMedCentral

Zhao X, Xu X, Yin H, et al. Clinical characteristics of patients with 2019 coronavirus disease in a non-Wuhan area of Hubei Province, China: a retrospective study. BMC Infect Dis. 2020;20:311. https://doi.org/10.1186/s12879-020-05010-w.CrossRefPubMedPubMedCentral

10.

Koo HJ, Lim S, Choe J, Choi S-H, Sung H, Do K-H. Radiographic and CT features of viral pneumonia. Radiographics. 2018;38(3):719–39. https://doi.org/10.1148/rg.2018170048.CrossRefPubMed

11.

Koo HJ, Choi SH, Sung H, Choe J, Do KH. RadioGraphics update: radiographic and CT features of viral pneumonia. Radiographics. 2020;40(4):E8–E15. https://doi.org/10.1148/rg.2020200097.CrossRefPubMed

12.

Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382(8):727–33. https://doi.org/10.1056/nejmoa2001017.CrossRefPubMedPubMedCentral

13.

Chan JF-W, Yuan S, Kok K-H, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514–23. https://doi.org/10.1016/S0140-6736(20)30154-931986261.CrossRefPubMedPubMedCentral

14.

Chan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, et al. Thoughts on the name and clinical diagnosis of the respiratory tract infection caused by the novel coronavirus. Chin J Respir Crit Care Med. 2020; http://kns.cnki.net/kcms/detail/51.1631.R.20200210.2248.004.html.

15.

Kim D, Quinn J, Pinsky B, Shah NH, Brown I. Rates of co-infection between SARS-CoV-2 and other respiratory pathogens [published online ahead of print, 2020 Apr 15]. JAMA. 2020;323(20):2085–6. https://doi.org/10.1001/jama.2020.6266.CrossRefPubMedPubMedCentral

16.

Sberna Sberna G, Amendola A, Valli MB, Carletti F, Capobianchi MR, Bordi L, et al. Trend of respiratory pathogens during the COVID-19 epidemic [published online ahead of print, 2020 May 26]. J Clin Virol. 2020;129:104470. https://doi.org/10.1016/j.jcv.2020.104470.CrossRefPubMed

17.

Xu K, Cai H, Shen Y, et al. [Management of corona virus disease-19 (COVID-19): the Zhejiang experience]. Zhejiang Da Xue Xue Bao Yi Xue Ban. 2020; 49(1):0. Chinese.

18.

Xiang F, Wang X, He X, Peng Z, Yang B, Zhang J, et al. Antibody detection and dynamic characteristics in patients with COVID-19 [published online ahead of print, 2020 Apr 19]. Clin Infect Dis. 2020:ciaa461. https://doi.org/10.1093/cid/ciaa461.

Titel: Differential diagnosis for suspected cases of coronavirus disease 2019: a retrospective study
verfasst von: Qiong Chi
Xinjian Dai
Xiangao Jiang
Lefei Zhu
Junyan Du
Yuxi Chen
Jiyang Zheng
Jianping Huang
Publikationsdatum: 01.12.2020
Verlag: BioMed Central
Schlagwort: COVID-19
Erschienen in: BMC Infectious Diseases / Ausgabe 1/2020
Elektronische ISSN: 1471-2334
DOI: https://doi.org/10.1186/s12879-020-05383-y

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Die Highlights vom Kongress des American College of Cardiology 2024

Springer Medizin

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