Analysis on severe fever with thrombocytopenia syndrome bunyavirus infection combined with atrial fibrillation under digital model detection

Abstract

Abstract To heighten the diagnostic efficiency, in this study, the algebraic reconstruction technology (ART)-based echocardiography (ECG) was used to analyze severe fever with thrombocytopenia syndrome bunyavirus (SFTSV) complicated by atrial fibrillation. From Jan. 2015 to Dec. 2019, 200 elderly patients with SFTSV infection and hypertrophic cardiomyopathy (HCM) admitted to our hospital were selected as the observation group, and 20 healthy volunteers were in the control group. Then 200 patients were randomly divided into two groups with 100 people in each group. One group received routine clinical observation after surgery, and the other group received artificial intelligence atrial fibrillation monitoring. ECG displayed the left ventricular ejection fraction (LVEF), left ventricular mass index (LVMI), left ventricular end diastolic volume index (EDVI), and end systolic volume index (ESVI) of patients. The accuracy and satisfaction of different methods in observation were recorded. The risk factors of postoperative atrial fibrillation in elderly patients with HCM were evaluated, and changes in their white blood cell levels were detected. The results showed that, there was a significant difference in ECG between normal people and patients after surgery. Also, differences were noted in accuracy and satisfaction of the two methods in observation group (P