Liu XQ, Lu GZ, Yin DL, Kang YY, Zhou YY, Wang YH, Xu J. Analysis of clinical characteristics and risk factors between elderly patients with severe and nonsevere Omicron variant infection.
World J Clin Infect Dis 2023;
13:37-48. [DOI:
10.5495/wjcid.v13.i4.37]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 11/02/2023] [Accepted: 11/13/2023] [Indexed: 11/22/2023] Open
Abstract
BACKGROUND
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to millions of confirmed cases and deaths worldwide. Elderly patients are at high risk of developing and dying from COVID-19 due to advanced age, decreased immune function, intense inflammatory response, and comorbidities. Shanghai has experienced a wave of infection with Omicron, a new variant of SARS-CoV-2, since March 2022. There is a pressing need to identify clinical features and risk factors for disease progression among elderly patients with Omicron infection to provide solid evidence for clinical policy-makers, public health officials, researchers, and the general public.
AIM
To investigate clinical characteristic differences and risk factors between elderly patients with severe and nonsevere Omicron SARS-CoV-2 variant infection.
METHODS
A total of 328 elderly patients with COVID-19 admitted to the Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from April 2022 to June 2022 were enrolled and divided into a severe group (82 patients) and a nonsevere group (246 patients) according to the diagnosis and treatment protocol of COVID-19 (version 7). The clinical data and laboratory results of both groups were collected and compared. A chi-square test, t test, Mann-Whitney U test, hierarchical log-rank test, univariate and multivariate logistic regression, and hierarchical analyses were used to determine significant differences.
RESULTS
The severe group was older (84 vs 74 years, P < 0.001), included more males (57.3% vs 43.9%, P = 0.037), had a lower vaccination rate (P < 0.001), and had a higher proportion of comorbidities, including chronic respiratory disease (P = 0.001), cerebral infarction (P < 0.001), chronic kidney disease (P = 0.002), and neurodegenerative disease (P < 0.001), than the nonsevere group. In addition, severe disease patients had a higher inflammatory index (P < 0.001), greater need for symptomatic treatment (P < 0.001), longer hospital stay (P = 0.011), extended viral shedding time (P = 0.014), and higher mortality than nonsevere disease patients (P < 0.001). No difference was observed in the application of Paxlovid in the severe and nonsevere groups (P = 0.817). Oxygen saturation, cerebral infarction, and D-dimer were predictive factors for developing severe disease in patients with COVID-19, with D-dimer having an excellent role (area under the curve: 90.1%, 95%CI: 86.1-94.0%). In addition, D-dimer was a risk factor for developing severe COVID-19 according to multivariate stratified analysis.
CONCLUSION
The clinical course of severe COVID-19 is complex, with a higher need for symptomatic treatment. D-dimer is a suitable biomarker for identifying patients at risk for developing severe COVID-19.
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