B-013 Association Between Laboratory Parameters Analysis and Clinical Severity in Patients With Coronavirus Disease (Covid 19) at Hospital Universitario Fundación Santa Fe

Abstract

Abstract Background Clinical management of COVID-19 disease was challenging. Laboratory parameters could be useful to classify patients in risk scores and probability to progress to a severe stage at the emergency room. This study aims to determine the association between laboratory parameters of COVID-19 patients and clinical disease severity to provide applicable information to improved treatment strategies. Thus, we described the laboratory findings that can work as a predictive marker of severity, in a cohort of patients form our institution from Colombia diagnosticated with COVID-19 during a period of one year. Methods This retrospective cohort descriptive study was conducted at one quaternary hospital at Bogota Colombia, where laboratory parameters on peripheric blood samples in 298participants with COVID-19 diagnosis were evaluated. For comparison between two groups’ data, the chi-square and Mann-Whitney U test were used. For correlation between variable a Spearman and a Kruskal Wallis test were performed as data didn’t normal distribution. A P-value lower than 0.05 was considered statistically significant in all analyses. Results Primary outcomes shown significant correlation between more severe disease and interleukin IL-6 elevation, by the Kruskal Wallis test. Lower counts of lymphocytes percent, ferritin, fibrinogen, neutrophils, basophils and coagulation factors were found to be associated with severe disease (P < 0.0001). Creatinine, D dimer, LDH, WBC count, creatinine and erythrosedimentation were significantly higher and were correlated with more severe disease on scores (P < 0.001). Higher levels on PCR parameters were associated with severe disease (P < 0.001). Conclusion Laboratory parameters such as IL-6 can be used as a severity marker in order to help physicians find both adequate treatment and hospitalization location of COVID-19 patients. This information can be used to manage future pandemics, and to evaluate complementary strategies that should be efficient on epidemic management and patient care having an impact on public health, mortality rates and hospitality capacity