The Prognostic Significance of C-Reactive Protein to Albumin Ratio in Patients With Severe Fever With Thrombocytopenia Syndrome - Yang, Xiaozhou; Yin, Huimin; Xiao, Congshu; Li, Rongkuan; Liu, Yu (Frontiers in Medicine, 2022)
Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with the high case-fatality rate, lacking effective therapies and vaccines. Inflammation-based indexes have been widely used to predict the prognosis of patients with cancers and some inflammatory diseases. In our study, we aim to explore the predictive value of the inflammation-based indexes in SFTS patients. Methods: We retrospectively analyzed 82 patients diagnosed with SFTS. The inflammation-based indexes, including neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), aggregate index of systemic inflammation (AISI) and C-reactive protein to albumin ratio (CAR), were compared between the survival and death patients. Receiver operating characteristic (ROC) curves were used to compare the predictive ability of MLR, AISI and CAR. The survival analysis was based on the Kaplan–Meier (KM) method. Multivariate logistic regression analysis was used to analyze the independent risk factors of poor prognosis in patients with SFTS. Results: The CAR is higher in the death group while MLR and AISI were higher in the survival group. The ROC curve analysis indicated CAR exhibited more predictive value than the other indexes and the optimal cut-off value of CAR was equal to or greater than 0.14. KM survival curve showed that higher CAR was significantly correlated to the lower overall survival in SFTS patients. Multivariate logistic regression analysis indicated that CAR was an independent risk factor for poor prognosis in patients with SFTS. Conclusions: The CAR is an independent risk factor for death in patients with SFTS and could predict the poor prognosis of SFTS patients. It could be used as a biomarker to help physicians to monitor and treat patients more aggressively to improve clinical prognosis.