Objective To evaluate the clinical value of dual-energy CT in the detection of monosodium urate crystals in patients with gout.Methods One hundred and eight patients who experienced unilateral arthrocele and (or) joint pain in the past two weeks were enrolled into our study.DECT were performed for the upper or lower extremity.Ninety-five patients were enrolled into the gout study group based on the American rheumatism association (ACR) classification standard;The 0.3 linear blended images group were regarded as conventional CT group,DE (80 kV and 140 kV) datasets were reconstructed via gout-recognition software,the pseudo-color images group as the postprocessed group.Imagings were reviewed independently by two senior radiologists.Chi-square test were used for statistical analysis with the SPSS 13.0software.Results In the conventional CT group,DECT scans revealed a total of 298 areas of urate deposition in 51 patients;The sensitivity,specificity,and accuracy were 53.7％,84.6％,and 57.4％.In the postprocessed group,401 areas of green urate deposition were detected in 69 patients,the sensitivity,specificity,and accuracy were 72.6％,100.0％,75.9％ respectively,the differences had statistical significance (x2 =7.329 and 8.333,P ＜ 0.05).Conclusions DECT gout recognition technology can detect smaller amount of monosodium urate in the other parts of the body,with a great potential in early diagnosis and treatment monitoring of patients with gout.

Objective To evaluate the dose reduction technology using in CT-guided percutaneous lung biopsy of pulmonary lesions using automated core needle biopsies (ACNB).Methods 412 ACNB cases included 146 consecutive conventional patients (group A,120 kV/100 mA) and 266 consecutive patients (group B,120 kV/20 mA,low-dose scanning,reduce scanning width and scanning frequency).The quality of images was compared by grain homogeneity,fine structure,clearness of tissue interface and artifacts.The total diagnostic accuracy rate,the examination time and radiation dose between group A and group B were compared.Results The fine structure of group B was significantly lower (X~2 ＝7.0508,P ＜ 0.05).The total diagnostic accuracy rate was 95.9% vs 95.1% (X~2 ＝0.1296,P ＜ 0.05).The examination time for biopsy procedure was (16 ±2.2)min vs (15.9 ±2.0)min (t ＝ 1.3579,P ＜ 0.05) ,and the mean effective dose (E) was (1.74 ± 0.7) mSv vs (0.59 ± 0.14) mSv (t ＝ 19.3415 ,P ＜ 0.05) .The E of group B decreased by 66%.Conclusions ACNB is a feasible and accurate method for diagnosing pulmonary lesions,and the E can significantly reduce the dose received in low-dose scanning.

Objective To find out the epidemic characteristics and the prevalent tendency of transmission of HIV infection in Zhaotong City from 1997 to 2007. Methods Statistical analysis was applied to the data of 1997-2007 Zhaotong City local monitoring detection of HIV-infected persons and AIDS epidemic Tables Network reported. Results From 1997 to 2007, the cumulative report of the city's HIV-infected persons was 914 cases. Before 2002 the report was 144 cases as intravenous drug users. From 2003 to 2007 cumulative reports of 770 cases were infected with HIV, of which 524 were of local detection, accounting for the 68% of reports; field reports were 246 cases, accounting for 31.95%. 260 cases were intravenous drug users, accounting for 33.8%; 155 cases of heterosexual contact, accounting for 20.1%; 20 cases were of mother to child transmission, accounting for 2.6%; 335 were unknown cases, accounting for 43.5%. Report of infection from 0.19/100 000 in 1997 rose to 3.51/100 000 in 2007. The infection rate for migrant workers was 23.43/100 000. Conclusions From 1997 to 2007, transmission of HIV infection in Zhaotong City had a great change, and the rate of infection rose continually. The proliferation from high-risk population groups such as drug user to the general population increased rapidly, and it was the same case with floating population.

Background: Diabetic peripheral neuropathy (DPN) is one of the most serious complications of type 2 diabetes mellitus (T2DM). DPN increases the risk of ulcers, foot infections, and noninvasive amputations, ultimately leading to long-term disability. Methods: Seven hundred patients with T2DM were investigated from 2013 to 2017 in the Sanlin community by obtaining basic data from the electronic medical record system (EMRS). From September 2018 to July 2019, 681 patients (19 missing) were investigated using a questionnaire, physical examination, biochemical index test, and follow-up Toronto clinical scoring system (TCSS) test. Patients with a TCSS score ≥6 points were diagnosed with DPN. After removing missing values, 612 patients were divided into groups in a 3:1 ratio for external validation. Using different Lasso analyses (misclassification error, mean squared error, –2log-likelihood, and area under curve) and a logistic regression analysis of the training set, models A, B, C, and D were established. The receiver operating characteristic (ROC) curve, calibration plot, dynamic component analysis (DCA) measurements, net classification improvement (NRI) and integrated discrimination improvement (IDI) were used to validate discrimination and clinical practicality of the model. Results: Through data analysis, model A (containing four factors), model B (containing five factors), model C (containing seven factors), and model D (containing seven factors) were built. After calibration, ROC curve, DCA, NRI and IDI, models C and D exhibited better accuracy and greater predictive power. Conclusion Four prediction models were established to assist with the early screening of DPN in patients with T2DM. The influencing factors in model C and D are more important factors for patients with T2DM diagnosed with DPN.

Background: Diabetic peripheral neuropathy (DPN) is one of the most serious complications of type 2 diabetes mellitus (T2DM). DPN increases the risk of ulcers, foot infections, and noninvasive amputations, ultimately leading to long-term disability. Methods: Seven hundred patients with T2DM were investigated from 2013 to 2017 in the Sanlin community by obtaining basic data from the electronic medical record system (EMRS). From September 2018 to July 2019, 681 patients (19 missing) were investigated using a questionnaire, physical examination, biochemical index test, and follow-up Toronto clinical scoring system (TCSS) test. Patients with a TCSS score ≥6 points were diagnosed with DPN. After removing missing values, 612 patients were divided into groups in a 3:1 ratio for external validation. Using different Lasso analyses (misclassification error, mean squared error, –2log-likelihood, and area under curve) and a logistic regression analysis of the training set, models A, B, C, and D were established. The receiver operating characteristic (ROC) curve, calibration plot, dynamic component analysis (DCA) measurements, net classification improvement (NRI) and integrated discrimination improvement (IDI) were used to validate discrimination and clinical practicality of the model. Results: Through data analysis, model A (containing four factors), model B (containing five factors), model C (containing seven factors), and model D (containing seven factors) were built. After calibration, ROC curve, DCA, NRI and IDI, models C and D exhibited better accuracy and greater predictive power. Conclusion Four prediction models were established to assist with the early screening of DPN in patients with T2DM. The influencing factors in model C and D are more important factors for patients with T2DM diagnosed with DPN.

ObjectiveTo investigate the predictive value of heart rate turbulence(HRT) in patients with diabetes mellitus (DM) after acute myocardial infarction (AMI).MethodsNinety-two AMI patients combined with DM (DM group) and 120 AMI patients without DM (non-DM group) were selected.Turbulence onset (TO) and turbulence slope (TS) were two indexes of HRT.HRT was considered positive when TO was ≥0 and TS was ≤2.5 ms/R-R.The differences in clinical data between HRT-positive and HRT-negative patients were compared.And the related risk factors after AMI were analyzed.ResultsAge,left ventricular ejection fraction (LVEF) level,renal insufficiency,LVEF＜40％,standard deviation of sinus cardiac cycle (R-R interval)(SDNN),heart rate variability (HRV) positiveand HRT indexes (TO,TS) between HRT-positive and HRT-negative patients in DM group had significant differences (P ＜ 0.05 ).Age,LVEF level,SDNN and HRT indexes(TO,TS) between HRT-positive and HRT-negative patients in non-DM group had significant differences(P ＜ 0.05).Multivariate Cox regression analysis showed that renal insufficiency (OR=4.8,95％ CI:1.8 - 10.7,P=0.008) and HRT positive (OR=3.7,95％ CI:1.5 - 8.6,P=0.070) in DM group had statistical significance.And HRT positive in non-DM group had statisticalsignificance(OR=23.0,95％ CI:5.2 ～ 86.0,P ＜ 0.01 ).ConclusionsHRT,an index of dynamic electrocardiogram,can predict the risk in patients with DM or without DM after AMI.

Objective:To evaluate the effects of orthogonal magnetic fields on the dose distribution of 6 MeV X-ray in a uniform water and heterogeneous phantoms.Methods:The Monte Carlo simulation software Gate v8.2 was used to investigate the dose distribution of X-ray beams of different field sizes in a uniform water phantom, water-air/bone-water layer phantom and" custom lung model" in the magnetic field strength of 0.0, 0.5, 1.0, 1.5, 3.0 T, respectively. The relationship between the intensity of magnetic field and the dose distribution of X-rays in the phantoms was analyzed.Results:The existence of a magnetic field would cause the X-ray to shorten the built-up area in the water phantom; when the field was 10 cm×10 cm, the maximum dose on the central axis could change by up to 56.22%(3.0 T). The transverse dose distribution of the radiation field in the direction of the vertical magnetic field shifted to one side by up to 43.64%(-44.55%). The average dose of the air layer in the water-air-water phantom could be reduced by 57.4%(3.0 T). In the water-bone-water phantom, the dose at the proximal end of the bone layer was decreased by 16.5%, whereas the dose at the distal end was increased by 22.6%(1.5 T). The dose change in each layer in the customed lung model was positively correlated with the magnetic field strength.Conclusion:The existence of the orthogonal magnetic field will cause the change of X-ray dose distribution on the built-up area and both sides of the radiation field in the phantoms, which is more obvious adjacent to the interface of heterogeneous phantom.

Objective: To investigate the status of insomnia, Internet addiction, and depressive symptoms among medical students and to analyze the effect of Internet addiction on insomnia and the mediating role of depressive symptoms, in order to provide a basis for the development of targeted interventions and measurements for medical students. Methods: A stratified whole group sampling method was used to select full-time college students from three medical universities in Anhui Province. The Chinese version of Insomnia Severity Index (ISI), Internet Addiction Test (IAT) scale and 9-item Patient Health Questionnaire (PHQ-9) were used to evaluate the symptoms of insomnia, Internet addiction and depressive in students. A multivariate Logistic regression analysis was used to explore the factors influencing insomnia among medical students and to analyze the relationship between insomnia with Internet addiction and depressive symptoms, respectively. Results: The overall rate of Internet addiction was 49.5%, depressive symptoms was 39.5%, insomnia was 18.6%. High academic stress, and the presence of surrounding people diagnosed with COVID-19 were associated with a higher risk of insomnia ( P <0.05). The higher the level of Internet addiction (mild, OR =2.60; moderate/severe, OR =4.21) and depression. (mild, OR =6.35; moderate/severe, OR =19.32), the higher the risk of insomnia. Mediated effect analysis showed that Internet addiction had a direct predictive effect ( β =0.02, P <0.05) on insomnia and also indirectly affected insomnia through depression (indirect effect=0.07，95% CI =0.06-0.08). Conclusion The detected rates of insomnia, Internet addiction and depressive symptoms are high among medical students in Anhui Province, and Internet addiction and depressive symptoms are risk factors for insomnia, which should be given more attention and appropriate interventions when necessary to improve their physical and mental health.