Epidemiological characteristics, routine laboratory diagnosis, clinical signs and risk factors for hand, -foot -and -mouth disease: A systematic review and meta-analysis.

BACKGROUND: For the past few years, only a few monovalent EV71 vaccines have been developed, while other enterovirus vaccines are in short supply. We conducted a quantitative meta-analysis to explore the epidemiological characteristics, routine laboratory diagnosis, clinical signs and risk factors for hand, foot and mouth disease (HFMD). METHODS: PubMed, Embase and the Web of Science were searched for eligible reports published before April 16, 2021, with no publication time or language restrictions. The primary outcome was the odds ratio of the epidemiological characteristics, routine laboratory diagnosis, and clinical signs associated with HFMD severity and death. RESULTS: After screening 10522 records, we included 32 articles comprising 781903 cases of hand, foot and mouth disease. Patients with severe illness developed some clinical signs (hypersomnia (OR = 21.97, 95% CI: 4.13 to 116.74), convulsion (OR = 16.18, 95% CI: 5.30 to 49.39), limb shaking (OR = 47.96, 95% CI: 15.17 to 151.67), and breathlessness (OR = 7.48, 95% CI: 1.90 to 29.40)) and had some changes in laboratory parameters (interleukin-6 levels standardized mean difference (SMD) = 1.57, 95%CI: 0.55 to 2.60), an increased neutrophils ratio (SMD = 0.55, 95%CI: 0.17 to 0.93), cluster of differentiation 4 (CD4+) (SMD = -1.38, 95%CI: -2.33 to -0.43) and a reduced lymphocytes ratio (SMD = -0.48, 95%CI: -0.93 to -0.33)) compared with patients with mild illness. The risk factors for death included cyanosis (OR = 5.82, 95% CI: 2.29 to 14.81), a fast heart rate (OR = 3.22, 95% CI: 1.65 to 6.30), vomiting (OR = 2.70, 95% CI: 1.33 to 5.49) and an increased WBC count (SMD = 0.60, 95% CI: 0.27 to 0.93). CONCLUSIONS: China has the highest incidence of HFMD. Our meta-analyses revealed important risk factors that are associated with the severity and mortality of HFMD.

Application of a decision tree model in the early identification of severe patients with severe fever with thrombocytopenia syndrome.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is a serious infectious disease with a fatality of up to 30%. To identify the severity of SFTS precisely and quickly is important in clinical practice. METHODS: From June to July 2020, 71 patients admitted to the Infectious Department of Joint Logistics Support Force No. 990 Hospital were enrolled in this study. The most frequently observed symptoms and laboratory parameters on admission were collected by investigating patients' electronic records. Decision trees were built to identify the severity of SFTS. Accuracy and Youden's index were calculated to evaluate the identification capacity of the models. RESULTS: Clinical characteristics, including body temperature (p = 0.011), the size of the lymphadenectasis (p = 0.021), and cough (p = 0.017), and neurologic symptoms, including lassitude (p<0.001), limb tremor (p<0.001), hypersomnia (p = 0.009), coma (p = 0.018) and dysphoria (p = 0.008), were significantly different between the mild and severe groups. As for laboratory parameters, PLT (p = 0.006), AST (p<0.001), LDH (p<0.001), and CK (p = 0.003) were significantly different between the mild and severe groups of SFTS patients. A decision tree based on laboratory parameters and one based on demographic and clinical characteristics were built. Comparing with the decision tree based on demographic and clinical characteristics, the decision tree based on laboratory parameters had a stronger prediction capacity because of its higher accuracy and Youden's index. CONCLUSION: Decision trees can be applied to predict the severity of SFTS.