Analysis of disease severity and sex specific data among hospitalized covid19 patients

ABSTRACT

Rationale It is critical to identify factors that contribute to disease severity among patients diagnosed with COVID-19. A recently published meta-analysis of over 3 million global admissions demonstrated that male patients have higher rates of ICU admission and mortality. This abstract details an investigation of the correlation between biological sex and predisposing conditions as well as COVID-19 disease severity among 1816 patients hospitalized within the St. Luke's Hospital Network in Eastern PA/Western NJ. Methods: Data were extracted from patients' electronic medical records both during their admission and after discharge. Chi-squared test of independence was performed to examine the relation between known COVID-19 risk factors and COVID-19 infected female patients (n=865) compared to male patients (n=951). The sample is comprised of 47.6% female participants and 52.4% male, of whom 23.5% identify as Hispanic or Latino, and 68.9% identified their race as Caucasian. The mean age of the participants is 66.0 years (+/- 17). Results: Risk factors stratified by biological sex showed that female patients with COVID were more likely to have asthma (p < 0.001) and male patients were more likely to have diabetes (p = 0.014). There was a statistically significant higher incidence of intubation (p < 0.001), tocilizumab administration (p < 0.001), and ICU admission (p < 0.001) among male patients. There was no statistically significant difference in disease severity between the sexes with respect to mortality, dialysis, and remdesivir administration.Conclusion: The results of this study show that male patients admitted within this hospital network have increased incidence of disease severity with regards to ICU admission, ventilation, and Tocilizumab administration, without an increase in 90 day all-cause mortality. Limitations of this study include small sample size, and ongoing treatment protocol modifications with provider treatment bias.