Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Chen CS

PROVIDER: S-EPMC9879147 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

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 CS Jian Ming-Jr MJ Chang Chih-Kai CK Chung Hsing-Yi HY Li Shih-Yi SY Lin Jung-Chung JC Yeh Kuo-Ming KM Yang Ya-Sung YS Chen Chien-Wen CW Hsieh Shan-Shan SS Tang Sheng-Hui SH Perng Cherng-Lih CL Chang Feng-Yee FY Shang Hung-Sheng HS

PeerJ 20230123

<h4>Purpose</h4>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 lin ...[more]

PMID: 36710871

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Project description:BackgroundBetween 2016 and 2017, the national mortality rate involving opioids continued its escalation; opioid deaths rose from 42,249 to 47,600, bringing the public health crisis to a new height. Considering that 69% of adults in the United States use online social media sites, a resource that builds a more complete understanding of prescription drug misuse and abuse could supplement traditional surveillance instruments. The Food and Drug Administration has identified 5 key risks and consequences of opioid drugs-misuse, abuse, addiction, overdose, and death. Identifying posts that discuss these key risks could lead to novel information that is not typically captured by traditional surveillance systems.ObjectiveThe goal of this study was to describe the trends of online posts (frequency over time) involving abuse, misuse, addiction, overdose, and death in the United States and to describe the types of websites that host these discussions. Internet posts that mentioned fentanyl, hydrocodone, oxycodone, or oxymorphone were examined.MethodsPosts that did not refer to personal experiences were removed, after which 3.1 million posts remained. A stratified sample of 61,000 was selected. Unstructured data were classified into 5 key risks by manually coding for key outcomes of misuse, abuse, addiction, overdose, and death. Sampling probabilities of the coded posts were used to estimate the total post volume for each key risk.ResultsAddiction and misuse were the two most commonly discussed key risks for hydrocodone, oxycodone, and oxymorphone. For fentanyl, overdose and death were the most discussed key risks. Fentanyl had the highest estimated number of misuse-, overdose-, and death-related mentions (41,808, 42,659, and 94,169, respectively). Oxycodone had the highest estimated number of abuse- and addiction-related mentions (3548 and 12,679, respectively). The estimated volume of online posts for fentanyl increased by more than 10-fold in late 2017 and 2018. The odds of discussing fentanyl overdose (odds ratios [OR] 4.32, 95% CI 2.43-7.66) and death (OR 5.05, 95% CI 3.10-8.21) were higher for social media, while the odds of discussing fentanyl abuse (OR 0.10, 95% CI 0.04-0.22) and addiction (OR 0.24, 95% CI 0.15-0.38) were higher for blogs and forums.ConclusionsOf the 5 FDA-defined key risks, fentanyl overdose and death has dominated discussion in recent years, while discussion of oxycodone, hydrocodone, and oxymorphone has decreased. As drug-related deaths continue to increase, an understanding of the motivations, circumstances, and consequences of drug abuse would assist in developing policy responses. Furthermore, content was notably different based on media origin, and studies that exclusively use either social media sites (such as Twitter) or blogs and forums could miss important content. This study sets out sustainable, ongoing methodology for surveilling internet postings regarding these drugs.

Dataset Information

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

Purpose

Patients and methods

Results

Conclusion

Publications

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

Similar Datasets

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