Effectiveness of Systemic Corticosteroids Therapy for Nonsevere Patients With COVID-19: A Multicenter, Retrospective, Longitudinal Cohort Study.

OBJECTIVES: Corticosteroids were clinically used in the treatment of nonsevere patients with COVID-19, but the efficacy of such treatment lacked sufficient clinical evidence, and the impact of dose had never been studied. This study aimed to evaluate the effect of systemic corticosteroid use (SCU) in nonsevere patients with COVID-19. METHODS: We conducted a multicenter retrospective cohort study in Hubei Province. A total of 1726 patients admitted with nonsevere type COVID-19 were included. Mixed-effect Cox model, mixed-effect Cox model with time-varying exposure, multiple linear regression, and propensity score analysis (inverse probability of treatment weight and propensity score matching) were used to explore the association between SCU and progression into severe type, all-cause mortality, and length of stay. RESULTS: During the follow-up of 30 days, 29.8% of nonsevere patients with COVID-19 received treatment with systemic corticosteroids. The use of systemic corticosteroids was associated with higher probability of developing severe type (adjusted hazard ratio 1.81; 95% confidence interval 1.47-2.21), all-cause mortality (adjusted hazard ratio 2.92; 95% confidence interval 1.39-6.15) in time-varying Cox analysis, and prolonged hospitalization (ß 4.14; P < .001) in multiple linear regression. Analysis with 2 propensity score cohorts displayed similar results. Besides, increased corticosteroid dose was significantly associated with elevated probability of developing severe type (P < .001) and prolonged hospitalization (P < .001). CONCLUSIONS: Corticosteroid treatment against nonsevere patients with COVID-19 was significantly associated with worse clinical outcomes. The higher dose was significantly associated with elevated risk of poor disease progression. We recommend that SCU should be avoided unless necessary among nonsevere patients with COVID-19.

Sex-Disaggregated Data on Clinical Characteristics and Outcomes of Hospitalized Patients With COVID-19: A Retrospective Study.

Background: Sex and gender are crucial variables in coronavirus disease 2019 (COVID-19). We sought to provide information on differences in clinical characteristics and outcomes between male and female patients and to explore the effect of estrogen in disease outcomes in patients with COVID-19. Method: In this retrospective, multi-center study, we included all confirmed cases of COVID-19 admitted to four hospitals in Hubei province, China from Dec 31, 2019 to Mar 31, 2020. Cases were confirmed by real-time RT-PCR and were analyzed for demographic, clinical, laboratory and radiographic parameters. Random-effect logistic regression analysis was used to assess the association between sex and disease outcomes. Results: A total of 2501 hospitalized patients with COVID-19 were included in the present study. The clinical manifestations of male and female patients with COVID-19 were similar, while male patients have more comorbidities than female patients. In terms of laboratory findings, compared with female patients, male patients were more likely to have lymphopenia, thrombocytopenia, inflammatory response, hypoproteinemia, and extrapulmonary organ damage. Random-effect logistic regression analysis indicated that male patients were more likely to progress into severe type, and prone to ARDS, secondary bacterial infection, and death than females. However, there was no significant difference in disease outcomes between postmenopausal and premenopausal females after propensity score matching (PSM) by age. Conclusions: Male patients, especially those age-matched with postmenopausal females, are more likely to have poor outcomes. Sex-specific differences in clinical characteristics and outcomes do exist in patients with COVID-19, but estrogen may not be the primary cause. Further studies are needed to explore the causes of the differences in disease outcomes between the sexes.

Association of metformin with mortality or ARDS in patients with COVID-19 and type 2 diabetes: A retrospective cohort study.

AIMS: To determine the association between metformin use and mortality and ARDS incidence in patients with COVID-19 and type 2 diabetes. METHODS: This study was a multi-center retrospective analysis of COVID-19 patients with type 2 diabetes and admitted to four hospitals in Hubei province, China from December 31st, 2019 to March 31st, 2020. Patients were divided into two groups according to their exposure to metformin during hospitalization. The outcomes of interest were 30-day all-cause mortality and incidence of ARDS. We used mixed-effect Cox model and random effect logistic regression to evaluate the associations of metformin use with outcomes, adjusted for baseline characteristics. RESULTS: Of 328 patients with COVID-19 and type 2 diabetes included in the study cohort, 30.5% (100/328) were in the metformin group. In the mixed-effected model, metformin use was associated with the lower incidence of ARDS. There was no significant association between metformin use and 30-day all-cause mortality. Propensity score-matched analysis confirmed the results. In the subgroup analysis, metformin use was associated with the lower incidence of ARDS in females. CONCLUSIONS: Metformin may have potential benefits in reducing the incidence of ARDS in patients with COVID-19 and type 2 diabetes. However, this benefit differs significantly by gender.

Sleep disturbances among Chinese residents during the Coronavirus Disease 2019 outbreak and associated factors.

OBJECTIVES: Sleep status can affect the body's immune status and mental health. This study aims to investigate the sleep status of Chinese residents during the outbreak of Coronavirus Disease 2019 (COVID-19) and to evaluate its related risk factors. METHODS: This research carried out a cross-sectional survey in February 2020 (during the COVID-19 outbreak) to investigate the sleep status of residents nationwide in the form of an online questionnaire. Of the 8151 respondents, 6437 were eventually included in the analysis. Logistic regression is applied to analyze the associated factors affecting residents' sleep quality. RESULTS: During the COVID-19 outbreak, the incidence of sleep disturbances in residents was 17.65%. Increased risk of sleep disturbances was found to be associated with older age, female gender, and poor self-reported health status. Moreover, the odds ratios (ORs) were 1.42 (95% CI: 1.1-2.64), 1.35 (95% CI: 1.16-1.59), 5.59 (95% CI: 4.32-7.23), respectively. Those residents who believed COVID-19 had caused a high number of deaths or who thought COVID-19 was not easy to cure were more likely to experience sleep disorders, and the ORs were 1.73 (95% CI: 1.43-2.09), 1.57 (95% CI: 1.29-1.91), respectively. Regular exercise was a protective factor for sleep disturbances, OR = 0.77 (95% CI: 0.63-0.93). CONCLUSIONS: During the outbreak of COVID-19, nearly one-fifth of participants had sleep disorders. It is necessary to pay more attention to people at high risk for sleep disturbances during the outbreak, adopt effective risk communication methods, enhance residents' rational understanding of COVID-19, and develop practical indoor exercise programs for general public to improve sleep quality.