Does the Hitit Index Work in the Differential Diagnosis of CCHF and COVID-19 with Non-Specific Findings?

Abstract

Introduction: During the 2019 novel coronavirus (COVID-19) pandemic period, all cases admitted to the emergency services have been evaluated primarily for COVID-19, and therefore other infectious diseases, especially Crimean Congo Hemorrhagic Fever (CCHF), which are endemic in our region, can be overlooked. In this study, it was aimed to determine the diagnostic power of the Hitit Index, which we developed from a panel consisting of clinical and laboratory findings of the cases with and without CCHF in previous years, to distinguish CCHF cases from COVID-19 cases. Materials and Methods: The study groups consisted of the COVID-19 cases (n= 116) admitted to the emergency service and the CCHF patients (n= 110) who were followed up in the Infectious Diseases and Clinical Microbiology Clinic of the same hospital between 2015-2020. Results: Hitit Index was found to be statistically significantly higher in patients with CCHF. For Hitit Index, sensitivity and specificity were 88% and 99%, while negative predictive value (NPV) and positive predictive value (PPV) were 90% and 99%, respectively. Conclusion: The Hitit Index is an example of artificial intelligence that we can use to distinguish patients with CCHF from patients with COVID-19.