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Objective @#To investigate the epidemiological characteristics of severe fever with thrombocytopenia syndrome (SFTS) in Dongyang City, Zhejiang Province from 2017 to 2022, so as to provide insights into SFTS prevention and control. @*Methods@#Data pertaining to patients with SFTS in Dongyang City from 2017 to 2022 were collected from Notifiable Infectious Disease Reporting System of Chinese Disease Prevention and Control Information System. The epidemiological and clinical characteristics of patients with SFTS were descriptively analyzed, and the trends in incidence of SFTS was evaluated using annual percent change (APC). @*Results@#A total of 32 SFTS cases were reported in Dongyang City from 2017 to 2022, with mean annual incidence of 0.63/105, and 8 cases died, with a fatality rate of 25.00%. The incidence of SFTS appeared a tendency towards a rise from 2017 to 2022 (APC=40.697%, P<0.05). The male to female ratio of SFTS cases was 0.78∶1, and farmer was the predominant occupation (31 cases, 96.88%). SFTS predominantly occurred among individuals at ages of 51 to 69 years (20 cases, 62.50%), and the incidence peaked during the period between March and May and between July and August (28 cases, 87.50%). SFTS cases were reported in 11 out of the 18 townships (streets) in Dongyang City, with the highest number found in Zuocun Township (8 cases, 28.13%), and had the lowest platelet count of (41.46±5.19)×109 platelets/L, with the lowest count of (3.00 to 67.00) ×109 platelets/L. All the SFTS cases had a history of mountain forest and farmland activities 2 weeks prior to onset of the disease, and 5 cases (15.63%) had a history of tick bites.@*Conclusions@#The incidence of SFTS appeared a tendency towards a rise in Dongyang City from 2017 to 2022, and SFTS was highly prevalent in spring and summer, with high incidence among farmers. Intensified health education of SFTS is recommended among residents in high-incidence areas.
ABSTRACT
OBJECTIVES: To construct a nomogram model that combines clinical characteristics and radiomics signatures to preoperatively discriminate pancreatic ductal adenocarcinoma (PDAC) in stage I-II and III-IV and predict overall survival. METHODS: A total of 135 patients with histopathologically confirmed PDAC who underwent contrast-enhanced CT were included. A total of 384 radiomics features were extracted from arterial phase (AP) or portal venous phase (PVP) images. Four steps were used for feature selection, and multivariable logistic regression analysis were used to build radiomics signatures and combined nomogram model. Performance of the proposed model was assessed by using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA). Kaplan-Meier analysis was applied to analyze overall survival in the stage I-II and III-IV PDAC groups. RESULTS: The AP+PVP radiomics signature showed the best performance among the three radiomics signatures [training cohort: area under the curve (AUC) = 0.919; validation cohort: AUC = 0.831]. The combined nomogram model integrating AP+PVP radiomics signature with clinical characteristics (tumor location, carcinoembryonic antigen level, and tumor maximum diameter) demonstrated the best discrimination performance (training cohort: AUC = 0.940; validation cohort: AUC = 0.912). Calibration curves and DCA verified the clinical usefulness of the combined nomogram model. Kaplan-Meier analysis showed that overall survival of patients in the predicted stage I-II PDAC group was longer than patients in stage III-IV PDAC group (p<0.0001). CONCLUSIONS: We propose a combined model with excellent performance for the preoperative, individualized, noninvasive discrimination of stage I-II and III-IV PDAC and prediction of overall survival.
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OBJECTIVE: To evaluate the CT imaging characteristics of incomplete and complete myocardial bridges-mural coronary artery (MB-MCA). METHODS: Fifty subjects with dual source coronary CT angiography (DSCTA) evidenced MB were included. The subjects were divided into incomplete MB-MCA and complete MB-MCA groups. The diameter of MCA in best systole phase and diastole phase, the MCA stenosis rate, the presence of atheromatous change proximal to the MB were evaluated. RESULTS: There were 58 MB, the average length was (2.02 ± 1.02) cm, 23 were incomplete MB and 35 were complete MB. Thirty-two MB were in the middle segments of left anterior descending artery (55.2%); 17 MB were in the distal segment of the left anterior descending artery (29.3%); 1 MB was in the proximal segment of left anterior descending artery; 3 MB in diagonal branch; 4 MB in obtuse marginal branch, 1 MB in distal right coronary artery. It was statistically significant difference between the incomplete MB-MCA and the complete MB-MCA of the diameter change in diastole and systole phase [(1.93 ± 0.49) mm, (1.71 ± 0.45) mm vs. (2.21 ± 0.41) mm, (1.63 ± 0.52) mm, P = 0.008] and stenosis rate (10.38% ± 20.2% vs. 25.12% ± 21.02%, P = 0.01). Atherosclerotic finding was evidenced in 8 incomplete MB (34.78%) and 15 complete MB (42.86%) at the proximal vessel of mural coronary artery (P > 0.05). CONCLUSION: DSCTA can vividly display the incomplete and complete myocardial MB, accurately evaluate the shape change of MB-MCA in diastole and systole phase and detect the atherosclerotic change in the proximal vessel of MB.
