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Tsuchida T, Nitahara Y, Suzuki S, Komase Y, Candray K, Kido Y, Nakagama Y, Yamasaki Y, Imamura M, Kawahata K, Kunishima H, Fujitani S, Mineshita M, Matsuda T. Back to normal; serological testing for COVID-19 diagnosis unveils missed infections. J Med Virol 2021; 93:4549-4552. [PMID: 33739483 PMCID: PMC8250857 DOI: 10.1002/jmv.26949] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Revised: 03/03/2021] [Accepted: 03/17/2021] [Indexed: 12/16/2022]
Abstract
Background The gold standard for coronavirus disease (COVID‐19) diagnosis has been the detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) RNA by nucleic acid amplification testing (NAAT). On the other hand, serological testing for COVID‐19 may offer advantages in detecting possibly overlooked infections by NAAT. Methods To evaluate seroconversion of NAAT‐negative pneumonia patients, immunoglobulin M (IgM) and IgG targeting the spike protein of SARS‐CoV‐2 were semiquantified by an immunofluorescence assay. Seroconversion was confirmed by another serological method, targeting the nucleocapsid protein. Results Eight suspected but unconfirmed COVID‐19 pneumonia patients (median age, 39 years; range, 21–55) were included. The median period between symptom onset and NAAT sample collection was 6 days (2–27 days). None of them had tested positive for SARS‐CoV‐2 by NAAT. In contrast, all eight patients revealed seropositivity with the two serological methods, indicating actual seroconversion against SARS‐CoV‐2. The median period between onset and blood sampling was 26.5 days (7–51 days). Conclusion Eight patients with COVID‐19 pneumonia, initially tested negative for SARS‐CoV‐2 by NAAT, were finally confirmed of the diagnosis by serological testing. To cover the whole spectrum of this heterogenous infectious disease, serology testing should be implemented to the multitiered diagnostic algorithm for COVID‐19.
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Affiliation(s)
- Tomoya Tsuchida
- Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Yuko Nitahara
- Department of Parasitology and Research Center for Infectious Disease Sciences, Graduate School of Medicine, Osaka City University, Osaka, Japan
| | - Shotaro Suzuki
- Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Yuko Komase
- Department of Respiratory Internal Medicine, St. Marianna University School of Medicine, Yokohama-City Seibu Hospital, Yokohama, Japan
| | - Katherine Candray
- Department of Parasitology and Research Center for Infectious Disease Sciences, Graduate School of Medicine, Osaka City University, Osaka, Japan
| | - Yasutoshi Kido
- Department of Parasitology and Research Center for Infectious Disease Sciences, Graduate School of Medicine, Osaka City University, Osaka, Japan
| | - Yu Nakagama
- Department of Parasitology and Research Center for Infectious Disease Sciences, Graduate School of Medicine, Osaka City University, Osaka, Japan
| | - Yukitaka Yamasaki
- Department of Infectious Diseases, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Mitsuru Imamura
- Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Kimito Kawahata
- Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Hiroyuki Kunishima
- Department of Infectious Diseases, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Shigeki Fujitani
- Department of Emergency and Critical Care Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Masamichi Mineshita
- Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Takahide Matsuda
- Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
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