Abstract
This retrospective multi-center matched cohort study assessed the risk for severe COVID-19 (combination of severity indicators), intensive care unit (ICU) admission, and in-hospital mortality in hospitalized patients when infected with the Omicron variant compared to when infected with the Delta variant. The study is based on a causal framework using individually-linked data from national COVID-19 registries. The study population consisted of 954 COVID-19 patients (of which, 445 were infected with Omicron) above 18 years old admitted to a Belgian hospital during the autumn and winter season 2021-2022, and with available viral genomic data. Patients were matched based on the hospital, whereas other possible confounders (demographics, comorbidities, vaccination status, socio-economic status, and ICU occupancy) were adjusted for by using a multivariable logistic regression analysis. The estimated standardized risk for severe COVID-19 and ICU admission in hospitalized patients was significantly lower (RR = 0.63; 95% CI (0.30; 0.97) and RR = 0.56; 95% CI (0.14; 0.99), respectively) when infected with the Omicron variant, whereas in-hospital mortality was not significantly different according to the SARS-CoV-2 variant (RR = 0.78, 95% CI (0.28-1.29)). This study demonstrates the added value of integrated genomic and clinical surveillance to recognize the multifactorial nature of COVID-19 pathogenesis.
Keywords: COVID-19; Delta; Omicron; SARS-CoV-2; genomic surveillance.
【저자키워드】 COVID-19, SARS-CoV-2, Genomic surveillance, Delta, omicron, 【초록키워드】 vaccination, intensive care, severe COVID-19, severity, hospital, Genomic surveillance, variant, SARS-CoV-2 variant, Comorbidities, intensive care unit, risk, hospitalized patients, omicron, delta variant, ICU, cohort study, Hospital mortality, COVID-19 pathogenesis, Surveillance, ICU admission, Omicron variant, genomic, Admission, in-hospital mortality, retrospective, Combination, Analysis, COVID-19 patient, demographics, Vaccination Status, 95% CI, study population, multivariable logistic regression, genomic data, Multivariable logistic regression analysis, National, significantly lower, multifactorial, confounder, were infected, adjusted, added, recognize, hospitalized patient, not significantly different, the SARS-CoV-2, 【제목키워드】 clinical, Winter, Belgium, season,