Predictive risk score model for severe fever with thrombocytopenia syndrome mortality based on qSOFA and SIRS scoring system.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is a severe systemic virus infectious disease usually having multi-organ dysfunction which resembles sepsis. METHODS: Data of 321 patients with laboratory-confirmed SFTS from May 2013 to July 2017 were retrospectively analyzed. Demographic and clinical characteristics, calculated quick sequential organ failure assessment (qSOFA) score and systemic inflammatory response syndrome (SIRS) criteria for survivors and nonsurvivors were compared. Independent risk factors associated with in-hospital mortality were obtained using multivariable logistic regression analysis. Risk score models containing different risk factors for mortality in stratified patients were established whose predictive values were evaluated using the area under ROC curve (AUC). RESULTS: Of 321 patients, 87 died (27.1%). Age (p < 0.001) and percentage numbers of patients with qSOFA≥2 and SIRS≥2 (p < 0.0001) were profoundly greater in nonsurvivors than in survivors. Age, qSOFA score, SIRS score and aspartate aminotransferase (AST) were independent risk factors for mortality for all patients. qSOFA score was the only common risk factor in all patients, those age ≥ 60 years and those enrolled in the intensive care unit (ICU). A risk score model containing all these risk factors (Model1) has high predictive value for in-hospital mortality in these three groups with AUCs (95% CI): 0.919 (0.883-0.946), 0.929 (0.862-0.944) and 0.815 (0.710-0.894), respectively. A model only including age and qSOFA also has high predictive value for mortality in these groups with AUCs (95% CI): 0.872 (0.830-0.906), 0.885(0.801-0.900) and 0.865 (0.767-0.932), respectively. CONCLUSIONS: Risk models containing qSOFA have high predictive validity for SFTS mortality.

Score risk model for predicting severe fever with thrombocytopenia syndrome mortality.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging epidemic infectious disease with high mortality in East Aisa, especially in China. To predict the prognosis of SFTS precisely is important in clinical practice. METHODS: From May 2013 to November 2015, 233 suspected SFTS patients were tested for SFTS virus using RT-PCR. Cox regression model was utilized to comfirm independent risk factors for mortality. A risk score model for mortality was constructed based on regression coefficient of risk factors. Log-rank test was used to evaluate the significance of this model. RESULTS: One hundred seventy-four patients were confirmed with SFTS, of which 40 patients died (23%). Baseline age, serum aspartate aminotransferase (AST) and serum creatinine (sCr) level were independent risk factors of mortality. The area under ROC curve (AUCs) of these parameters for predicting death were 0.771, 0.797 and 0.764, respectively. And hazard ratio (HR) were 1.128, 1.002 and 1.013, respectively. The cutoff value of the risk model was 10. AUC of the model for predicting mortality was 0.892, with sensitivity and specificity of 82.5 and 86.6%, respectively. Log-rank test indicated strong statistical significance (×2 = 88.35, p < 0.001). CONCLUSIONS: This risk score model may be helpful to predicting the prognosis of SFTS patients.