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Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment

PURPOSE: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major healthcare threat worldwide. Since it was first identified in November 2021, the Omicron (B.1.1.529) variant of SARS-CoV-2 has evolved into several lineages, including BA....

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Autores principales: Chen, Chi-Sheng, Jian, Ming-Jr, Chang, Chih-Kai, Chung, Hsing-Yi, Li, Shih-Yi, Lin, Jung-Chung, Yeh, Kuo-Ming, Yang, Ya-Sung, Chen, Chien-Wen, Hsieh, Shan-Shan, Tang, Sheng-Hui, Perng, Cherng-Lih, Chang, Feng-Yee, Shang, Hung-Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879147/
https://www.ncbi.nlm.nih.gov/pubmed/36710871
http://dx.doi.org/10.7717/peerj.14666
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author Chen, Chi-Sheng
Jian, Ming-Jr
Chang, Chih-Kai
Chung, Hsing-Yi
Li, Shih-Yi
Lin, Jung-Chung
Yeh, Kuo-Ming
Yang, Ya-Sung
Chen, Chien-Wen
Hsieh, Shan-Shan
Tang, Sheng-Hui
Perng, Cherng-Lih
Chang, Feng-Yee
Shang, Hung-Sheng
author_facet Chen, Chi-Sheng
Jian, Ming-Jr
Chang, Chih-Kai
Chung, Hsing-Yi
Li, Shih-Yi
Lin, Jung-Chung
Yeh, Kuo-Ming
Yang, Ya-Sung
Chen, Chien-Wen
Hsieh, Shan-Shan
Tang, Sheng-Hui
Perng, Cherng-Lih
Chang, Feng-Yee
Shang, Hung-Sheng
author_sort Chen, Chi-Sheng
collection PubMed
description PURPOSE: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major healthcare threat worldwide. Since it was first identified in November 2021, the Omicron (B.1.1.529) variant of SARS-CoV-2 has evolved into several lineages, including BA.1, BA.2–BA.4, and BA.5. SARS-CoV-2 variants might increase transmissibility, pathogenicity, and resistance to vaccine-induced immunity. Thus, the epidemiological surveillance of circulating lineages using variant phenotyping is essential. The aim of the current study was to characterize the clinical outcome of Omicron BA.2 infections among hospitalized COVID-19 patients and to perform an immunological assessment of such cases against SARS-CoV-2. PATIENTS AND METHODS: We evaluated the analytical and clinical performance of the BioIC SARS-CoV-2 immunoglobulin (Ig)M/IgG detection kit, which was used for detecting antibodies against SARS-CoV-2 in 257 patients infected with the Omicron variant. RESULTS: Poor prognosis was noted in 38 patients, including eight deaths in patients characterized by comorbidities predisposing them to severe COVID-19. The variant-of-concern (VOC) typing and serological analysis identified time-dependent epidemic trends of BA.2 variants emerging in the outbreak of the fourth wave in Taiwan. Of the 257 specimens analyzed, 108 (42%) and 24 (9.3%) were positive for anti-N IgM and IgG respectively. CONCLUSION: The VOC typing of these samples allowed for the identification of epidemic trends by time intervals, including the B.1.1.529 variant replacing the B.1.617.2 variant. Moreover, antibody testing might serve as a complementary method for COVID-19 diagnosis. The combination of serological testing results with the reverse transcription-polymerase chain reaction cycle threshold value has potential value in disease prognosis, thereby aiding in epidemic investigations conducted by clinicians or the healthcare department.
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spelling pubmed-98791472023-01-27 Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment Chen, Chi-Sheng Jian, Ming-Jr Chang, Chih-Kai Chung, Hsing-Yi Li, Shih-Yi Lin, Jung-Chung Yeh, Kuo-Ming Yang, Ya-Sung Chen, Chien-Wen Hsieh, Shan-Shan Tang, Sheng-Hui Perng, Cherng-Lih Chang, Feng-Yee Shang, Hung-Sheng PeerJ Allergy and Clinical Immunology PURPOSE: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major healthcare threat worldwide. Since it was first identified in November 2021, the Omicron (B.1.1.529) variant of SARS-CoV-2 has evolved into several lineages, including BA.1, BA.2–BA.4, and BA.5. SARS-CoV-2 variants might increase transmissibility, pathogenicity, and resistance to vaccine-induced immunity. Thus, the epidemiological surveillance of circulating lineages using variant phenotyping is essential. The aim of the current study was to characterize the clinical outcome of Omicron BA.2 infections among hospitalized COVID-19 patients and to perform an immunological assessment of such cases against SARS-CoV-2. PATIENTS AND METHODS: We evaluated the analytical and clinical performance of the BioIC SARS-CoV-2 immunoglobulin (Ig)M/IgG detection kit, which was used for detecting antibodies against SARS-CoV-2 in 257 patients infected with the Omicron variant. RESULTS: Poor prognosis was noted in 38 patients, including eight deaths in patients characterized by comorbidities predisposing them to severe COVID-19. The variant-of-concern (VOC) typing and serological analysis identified time-dependent epidemic trends of BA.2 variants emerging in the outbreak of the fourth wave in Taiwan. Of the 257 specimens analyzed, 108 (42%) and 24 (9.3%) were positive for anti-N IgM and IgG respectively. CONCLUSION: The VOC typing of these samples allowed for the identification of epidemic trends by time intervals, including the B.1.1.529 variant replacing the B.1.617.2 variant. Moreover, antibody testing might serve as a complementary method for COVID-19 diagnosis. The combination of serological testing results with the reverse transcription-polymerase chain reaction cycle threshold value has potential value in disease prognosis, thereby aiding in epidemic investigations conducted by clinicians or the healthcare department. PeerJ Inc. 2023-01-23 /pmc/articles/PMC9879147/ /pubmed/36710871 http://dx.doi.org/10.7717/peerj.14666 Text en ©2023 Chen et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Allergy and Clinical Immunology
Chen, Chi-Sheng
Jian, Ming-Jr
Chang, Chih-Kai
Chung, Hsing-Yi
Li, Shih-Yi
Lin, Jung-Chung
Yeh, Kuo-Ming
Yang, Ya-Sung
Chen, Chien-Wen
Hsieh, Shan-Shan
Tang, Sheng-Hui
Perng, Cherng-Lih
Chang, Feng-Yee
Shang, Hung-Sheng
Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment
title Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment
title_full Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment
title_fullStr Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment
title_full_unstemmed Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment
title_short Monitoring algorithm of hospitalized patients in a medical center with SARS-CoV-2 (Omicron variant) infection: clinical epidemiological surveillance and immunological assessment
title_sort monitoring algorithm of hospitalized patients in a medical center with sars-cov-2 (omicron variant) infection: clinical epidemiological surveillance and immunological assessment
topic Allergy and Clinical Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879147/
https://www.ncbi.nlm.nih.gov/pubmed/36710871
http://dx.doi.org/10.7717/peerj.14666
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