The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
A Comparative Study on the Clinical Features of Coronavirus 2019 (COVID-19) Pneumonia With Other Pneumonias
Open accessAbstract
Background: A novel coronavirus (COVID-19) has raised world concern since it emerged in Wuhan, China in December 2019. The infection may result in severe pneumonia with clusters of illness onsets. Its impacts on public health make it paramount to clarify the clinical features with other pneumonias. Methods: Nineteen COVID-19 and 15 other patients with pneumonia (non-COVID-19) in areas outside of Hubei were involved in this study. Both COVID-19 and non-COVID-19 patients were confirmed to be infected using throat swabs and/or sputa with/without COVID-2019 by real-time RT-PCR. We analyzed the demographic, epidemiological, clinical, and radiological features from those patients, and compared the differences between COVID-19 and non-COVID-19. Results: All patients had a history of exposure to confirmed cases of COVID-19 or travel to Hubei before illness. The median (IQR) duration was 8 (6–11) and 5 (4–11) days from exposure to onset in COVID-19 and non-COVID-19 cases, respectively. The clinical symptoms were similar between COVID-19 and non-COVID-19. The most common symptoms were fever and cough. Fifteen (78.95%) COVID-19 but 4 (26.67%) non-COVID-19 patients had bilateral involvement while 17 COVID-19 patients (89.47%) but 1 non-COVID-19 patient (6.67%) had multiple mottling and ground-glass opacity on chest CT images. Compared with non-COVID-19, COVID-19 presents remarkably more abnormal laboratory tests, including AST, ALT, γ-GT, LDH, and α-HBDH. Conclusions: The COVID-19 infection has onsets similar to other pneumonias. CT scan may be a reliable test for screening COVID-19 cases. Liver function damage is more frequent in COVID-19 than non-COVID-19 patients. LDH and α-HBDH may be considerable markers for evaluation of COVID-19.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Identification of a novel coronavirus in patients with severe acute respiratory syndrome
Drosten, C., Günther, S., Preiser, W., van der Werf, S., Brodt, H.-R., Becker, S., Rabenau, H., Panning, M., Kolesnikova, L., Fouchier, R. A. M., et al. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa030747 · Cited by 4,574
Baskin, C. R., Bielefeldt-Ohmann, H., Tumpey, T. M., Sabourin, P. J., Long, J. P., García-Sastre, A., Tolnay, A.-E., Albrecht, R., Pyles, J. A., Olson, P. H., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0813234106 · Cited by 361
Cited by
Co-infections in people with COVID-19: a systematic review and meta-analysis.
Lansbury, L., Lim, B., Baskaran, V., & Lim, W. S. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.05.046 · Cited by 1,619
Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations
Phua, J., Weng, L., Ling, L., Egi, M., Lim, C.-M., Divatia, J. V., Shrestha, B. R., Arabi, Y. M., Ng, J., Gomersall, C. D., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30161-2 · Cited by 1,509
Thomas, P., Baldwin, C., Bissett, B., Boden, I., Gosselink, R., Granger, C. L., Hodgson, C., Jones, A. Y., Kho, M. E., Moses, R., et al. (2020) · Journal of Physiotherapy · doi:10.1016/j.jphys.2020.03.011 · Cited by 718
Musuuza, J. S., Watson, L., Parmasad, V., Putman-Buehler, N., Christensen, L., & Safdar, N. (2021) · PLOS ONE · doi:10.1371/journal.pone.0251170 · Cited by 544
Wu, X., Hui, H., Niu, M., Li, L., Wang, L., He, B., Yang, X., Li, L., Li, H., Tian, J., et al. (2020) · European Journal of Radiology · doi:10.1016/j.ejrad.2020.109041 · Cited by 268
Self-citation
Metadata
- Authors
- Zhao, D., Yao, F., Wang, L., Zheng, L., Gao, Y., Ye, J., Guo, F., Zhao, H., & Gao, R.
- Venue
- Clinical Infectious Diseases
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-03-12
- Volume
- 71
- Issue
- 15
- Pages
- 756-761
- ISSN
- 1058-4838 (ISSN-L)
- 1537-6591
- OpenAlex
- W3010609078
- Cited by
- 488
- References
- 6
- FWCI
- 14.12
- Type
- journal article
- Language
- en
- Open access
- bronze
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Comparative Study on the Clinical Features of Coronavirus 2019 (COVID-19) Pneumonia With Other Pneumonias. https://app.cochat.ai/papers/10.1093/cid/ciaa247
- The paper
- Zhao, D., Yao, F., Wang, L., Zheng, L., Gao, Y., Ye, J., Guo, F., Zhao, H., & Gao, R. (2020). A Comparative Study on the Clinical Features of Coronavirus 2019 (COVID-19) Pneumonia With Other Pneumonias. Clinical Infectious Diseases. https://doi.org/10.1093/cid/ciaa247
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
