Abstract

To establish a Cox regression model predicting risk factors for mortality in patients with severe fever with thrombocytopenia syndrome (SFTS), a total of 109 SFTS patients treated at The Second Hospital of Nanjing between June 2016 and October 2020 were included in this study. The patients were categorized into survival (n = 82) and death (n = 27) groups, and the clinical manifestations on admission and laboratory examination were collected. The factors associated with the mortality risk of SFTS patients were explored by univariate and binary logistic regression analyses. The receiver operating characteristic curve was used to evaluate the predictive value of independent influencing factors and the STFS scoring system. Univariate screening showed that the putative influencing factors were age, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, invasive mechanical ventilation, continuous renal replacement therapy, application of vasoactive medications, absolute count of lymphocytes, count of platelets, and levels of albumin and D-dimer (P < 0.05). Binary logistic regression showed that age (P = 0.042), APACHE II score (P = 0.030), and vasoactive medications (P = 0.035) were independent risk factors in SFTS patients. The combined prediction equation for the mortality risk of SFTS patients was "Combined predictor = age + 3.162 × APACHE II score + 22.306 × vasoactive medications," and the predictive value of combined predictor was greater than that of age (P = 0.004) or APACHE II score (P < 0.001). The combination of age, APACHE II score, and vasoactive medications had the highest ability to predict the risk of death. The STFS scoring system could make the clinical application of independent risk factors feasible.

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