Establishment of sex-specific predictive models for critical illness in Chinese people with the Omicron variant - Yang, Rui; Guan, Xin; Niu, Ziguang; Zhang, Rulin; Lv, Siang; Xu, Xiang; Zhao, Yingying; Wu, Jun (Frontiers in Microbiology, 2024)
The Omicron variant has rapidly spread throughout the world instead of the Delta variant and poses a great threat to global health care systems due to its immune evasion and rapid spread. Sex has been identified as a factor significantly associated with COVID-19 mortality, but it remains unclear which clinical indicators could be identified as risk factors in each sex group and which sex-specific risk factors might shape the worse clinical outcome, especially for Omicrons. This study aimed to confirm the relationship between sex and the progression of the Omicron variant, and to explore its sex-biased risk factors. We conducted a retrospective study including 1132 hospitalized patients with COVID-19 Omicron variant from 2022.12.5 to 2023.1.25 at Shanghai General Hospital, and the medical history data and clinical index data of the inpatients for possible sex differences were compared and analysed.Then, sex-specific Lasso regression was performed to select the variables significantly associated with critical illness, including intensive care unit admission, invasive mechanical ventilation, or death. Logistic regression was used to construct a sex-specific predictive model distinctively for the critical illness outcome using selected covariates. From the collected 115 clinical indicators, up to 72 showed significant sex differences, including the difference in merit and the proportion of people with abnormalities. More importantly, males had greater critical illness (28.4% vs. 19.9%), with significantly higher intensive care unit occupancy (20.96% vs. 14.49%) and mortality (13.2% vs. 4.9%), and males over 80 showed worse outcomes than females. Predictive models (AUC: 0.861 for males and 0.898 for females) showed 12 risk factors for males and 10 for females. Through a comprehensive sex-stratified analysis of a large cohort of hospitalized Omicron-infected patients, we identified the specific risk factors for critical illness by developing prediction models.According to our data, sex disparities and the identified risk factors should be considered, especially in the targeted treatment and prevention of the COVID-19 Omicron variant.