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Epidemiological and clinical characteristics of 99 cases of 2019 novel Coronavirus pneumonia in Wuhan, China: a descriptive study.
Open accessAbstract
Background In December, 2019, a pneumonia associated with the 2019 novel coronavirus (2019-nCoV) emerged in Wuhan, China. We aimed to further clarify the epidemiological and clinical characteristics of 2019-nCoV pneumonia.Methods In this retrospective, single-centre study, we included all confirmed cases of 2019-nCoV in Wuhan Jinyintan Hospital from Jan 1 to Jan 20, 2020. Cases were confirmed by real-time RT-PCR and were analysed for epidemiological, demographic, clinical, and radiological features and laboratory data. Outcomes were followed up until Jan 25, 2020.Findings Of the 99 patients with 2019-nCoV pneumonia, 49 (49%) had a history of exposure to the Huanan seafood market. The average age of the patients was 55·5 years (SD 13·1), including 67 men and 32 women. 2019-nCoV was detected in all patients by real-time RT-PCR. 50 (51%) patients had chronic diseases. Patients had clinical manifestations of fever (82 [83%] patients), cough (81 [82%] patients), shortness of breath (31 [31%] patients), muscle ache (11 [11%] patients), confusion (nine [9%] patients), headache (eight [8%] patients), sore throat (five [5%] patients), rhinorrhoea (four [4%] patients), chest pain (two [2%] patients), diarrhoea (two [2%] patients), and nausea and vomiting (one [1%] patient). According to imaging examination, 74 (75%) patients showed bilateral pneumonia, 14 (14%) patients showed multiple mottling and ground-glass opacity, and one (1%) patient had pneumothorax. 17 (17%) patients developed acute respiratory distress syndrome and, among them, 11 (11%) patients worsened in a short period of time and died of multiple organ failure.Interpretation The 2019-nCoV infection was of clustering onset, is more likely to affect older males with comorbidities, and can result in severe and even fatal respiratory diseases such as acute respiratory distress syndrome. In general, characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia. Further investigation is needed to explore the applicability of the MuLBSTA score in predicting the risk of mortality in 2019-nCoV infection.Funding National Key R&D Program of China.
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“Consistent with the notion that severe COVID-19 is a cytokine storm syndrome (12–17, 336), the severity of COVID-19 is associated with an increased level of inflammatory cytokines, such as IL-6, granulocyte macrophage colony-stimulating factor (GM-CSF) and TNFα (333, 337).”
From IL-6 in inflammation, autoimmunity and cancer (2021) · cites this paper as [337]
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“Given the fact that this group is reportedly more vulnerable during COVID-19 (Chen et al., 2020; Deng et al., 2020; Liu W. et al., 2020; Pan et al., 2020; World Health Organization, 2020), the findings are consistent with other similar studies (Rajkumar, 2020; Özdin and Bayrak Özdin, 2020).”
From Knowledge of COVID-19 and Its Influence on Mindfulness, Cognitive Emotion Regulation and Psychological Flexibility in the Indian Community (2020) · cites this paper as Chen et al., 2020
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“Four fungal pathogens were identified from three studies.10 , 23 , 35 Candida albicans was isolated from the respiratory tract in five patients and urinary tract of a sixth.”
From Co-infections in people with COVID-19: a systematic review and meta-analysis. (2020) · cites this paper as [23]
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“A highly resistant Acinetobacter baumannii was isolated in a further study.23”
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“Other sources identify X-ray as an insensitive test”
From Blockchain and Artificial Intelligence Technology in E-Health (2021) · cites this paper as Chen et al. 2020
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“However, reports on the use of X-ray for COVID-19 diagnosis have been mixed.”
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Metadata
- Authors
- Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., Xia, J., Yu, T., Zhang, X., & Zhang, L.
- Affiliations
- Jinyintan Hospital (CN)
- Shanghai Jiao Tong University (CN)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Zhang, Xinxin
- Zhang, Li
- ORCID
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 395
- Issue
- 10223
- Pages
- 507-513
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- PMC
- PMC7135076
- OpenAlex
- W3002108456
- Cited by
- 21,415
- References
- 27
- Citations by year
- 2026: 157 · 2025: 439 · 2024: 1098 · 2023: 1866 · 2022: 3251 · 2021: 5867 · 2020: 8678
- FWCI
- 645.52
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Lancet (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Key R&D Program of China (2017YFC1309700)
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Clinical Neurology › Long-Term Effects of COVID-19
- Keywords
- SARS-CoV-2, COVID-19 pneumonia, epidemiological characteristics, clinical features, acute respiratory distress syndrome, multiple organ failure, bilateral pneumonia, comorbidities, Wuhan outbreak, mortality, chest imaging findings, viral shedding duration, contact tracing
- MeSH terms
- COVID-19, Adult, Aged, Aged, 80 and over, China, Cough, Disease Outbreaks, Dyspnea, Female, Fever, Humans, Male, Middle Aged, Pneumonia, Viral, Prognosis, Retrospective Studies, Radiography, Thoracic, Tomography, X-Ray Computed, Comorbidity, Coronavirus Infections, Severe Acute Respiratory Syndrome, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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