Objective To investigate the short and long term therapeutic effects of prostaglandin E1 (PGEl) on diabetic nephropathy (DN). Methods Patients with DN in stage Ⅲ to Ⅴ according to Mogensen criteria were randomly assigned to four groups of PGE1, angiotensin-converting enzyme inhibitor (ACEI), PGE1 + ACEI and control drug. The levels of proteinuria and albuminuria were measured before and 15 days, 6 months and 18 months after treatment. Patients with DN in stage Ⅳ were subdivided into three groups according to proteinuria: early stage IV (protienuria was less than 1.5 g/d), middle stage Ⅳ (protienuria was between 1.5 g/d and 2.5 g/d) and late stage Ⅳ (protienuria was larger than 2.5 g/d). Results Fifteen days after treatment, the levels of proteinuria and albuminuria were significantly decreased compared with pre-treatment in PGE1 and PGE1 + ACEI groups (P<0. 01), and the therapeutic effect was better in PGE1 + ACE1 group than in ACEI group (P<0. 01). Six months after treatment, there were still significant differences in above parameters in patients with DN in stage Ⅲ and Ⅳ between PGE1 + ACEI and PGE1 groups. And for the patients in stage Ⅴ, statistic significance between pre-and post-treatment existed only in PGE1 + ACEI group (P<0. 05). but not in PGE1 and ACEI groups (both P>0. 05). Eighteen months atter treatment, the levels of proteinuria and albuminuria were significantly decreased in patients in stage HI and early stage IV in all treatment groups (P<0. 01). For patients in middle stage IV and late stage Ⅳ , the significant differences still occurred between pre-and post-treatment in PGE1 + ACEI group (P<0. 01 or P<0. 05), and were significantly better than in ACEI group (P<0. 01 or P<0. 05). However, the proteinuria of patients in late stage IV elevated in PGE1 group in post-treatment versus pre-treatment (P<0. 05). Conclusions The short term therapeutic effect of PGE1 is quick and good in patients with DN. The therapeutic effect is much better in patients in stage Ⅲ compared with stage Ⅴ. The combination of PGE1 and ACEI will get better best therapeutic effect than PGE1 or ACEI alone in long term.

Various questionnaires for screening diabetes in Chinese population were evaluated. Two questionnaires (Finnish Diabetes Risk Score and Danish Diabetes Risk Score) were applied. Sensitivity, specificity and the area under the receiver operating characteristic (ROC) curve (AUC) for both questionnaires were calculated. The AUCs were 0. 760 (95% CI: 0.713-0.806) for the Finnish questionnaire (P<0.01) and 0.706 (95% CI: 0.647-0.764) for the Danish one (P<0.01). The sensitivities, specificities and predictive values of both questionnaires were not so good in the present survey as in the published reports. It suggests that these screening questionnaires must be modified to suitable for Chinese population.

Objective To investigate the image quality and radiation dose of automatic spectral imaging mode selection and adaptive statistical iterative reconstruction (ASIR) at abdominal CT with low contrast agent dose. Methods One hundred cases with the arterial-phase (AP) and portal venous phase (PVP) contrast-enhanced abdominal CT scanning were analyzed prospectively. Patients were randomly assigned to the study group and control group (n=50 each). In the study group, automatic spectral imaging mode selection and contrast agent dose of 300 mg/kg were used and spectral monochromatic images(40 to 60 keV) were reconstructed using either filtered back-projection (FBP) (group A) or ASIR (group B). In the control group, the fixed tube potential of 120 kVp and contrast agent dose of 450 mg/kg were used with images reconstructed using FBP (group C). Quantitative parameters (image noise and contrast-to-noise ratio of the liver, pancreas, aorta and portal vein) and qualitative visual parameters (overall image quality as graded on a 5-point scale) were compared among the groups by using One-way ANOVA or Kruskal-Wallis H test. Two sample t tests were used compare the radiation dose difference. Results There had no significant difference in CTDIvol[both (12±5) mGy] and DLP[(364±142) mGy·cm versus (377±131) mGy·cm] between the study group and control group(t=-0.408 and-0.428,P>0.05). During the AP and PVP, at the energy level of 40 keV, group B showed higher CNRs than group A and group C, lower image noise[ (29±6) HU in AP, (24±6) HU in PVP] than group A[(43±11) HU, (44±10) HU] but higher image noise than group C[ (18± 4) HU, (18±4) HU], lower overall image quality scores[(3.0±0.2) point, (2.9±0.3) point] than group C[(3.6± 0.4) point , (3.6±0.5) point] but similar scores to group A[(2.9±0.4) point,(2.8±0.4)point]. At the energy level of 50 keV, group B showed higher CNRs than group A but higher than or similar CNRs to group C, lower image noise[ (20±5) HU, (20±4) HU] than group A[(31±8) HU, (31±7) HU] but similar image noise to group C, higher overall image quality scores[(3.6±0.4) point, (3.5±0.4) point]than group A[(3.3±0.3) point,(3.3±0.3) point] but similar scores to group C. At the energy level of 60 keV, group B showed lower image noise[(14±4) HU, (14±3) HU], higher CNRs and overall image quality scores[(3.9±0.4) point,(3.9±0.3) point] than group A[(19 ± 5) and (20 ± 5)HU in image noise, (3.7 ± 0.4) and (3.7 ± 0.3) point in overall image quality scores ]and group C. Except for monochromatic images at 40 keV, the overall image quality scores in group B were all greater than 3 point and met the clinical diagnostic level. Conclusions The radiation dose of CT spectral imaging and conventional 120 kVp CT scan is equivalent with the use of automatic spectral imaging mode selection. By combining ASIR technique, monochromatic images at 50 and 60 keV can improve CNR and reduce contrast agent dose while maintain or improve overall image quality.

The construction of a paperless medical record system is a new stage in the development of intelligent medical record management in hospitals.The implementation of paperless medical records has significant practical significance in impro-ving medical record management,enhancing the level of medical services,and reducing healthcare operational costs.To explore the key technological issues of paperless medical record system for inpatient care,this article first provides an overview of the po-sitioning and business process of paperless medical record system in the hospital's information system.Secondly,based on the actual application of paperless medical records in our hospital,the core difficulties and application processes of key technological aspects such as trusted electronic signatures and comprehensive verification of medical record data from all dimensions are dis-cussed.Next,the integrated application effects of paperless medical records are analyzed.Finally,the key research directions and future development models of paperless medical records are discussed.

OBJECTIVETo investigate the application value of spectral CT in the differentiation of stage T3 and T4a gastric carcinoma.

METHODSData of 62 gastric cancer patients of stage T3 and T4a undergoing abdominal spectral CT examination in the First Affiliated Hospital of Zhengzhou University from December 2013 to December 2014 were collected retrospectively. There were 38 male and 24 female patients, with age of 33 to 77(58.6±10.4) years old. Abdominal double-phase enhanced scanning in gemstone spectral imaging mode was used to measure Iodine concentration (IC, 100 μg/ml) and water concentration(WC, 100 μg/ml) of perigastric fat tissue adjacent to the lesion during arterial phase(AP) and venous phase(VP), and normalized iodine concentration (nIC) was calculated respectively(nIC=IC/IC of aorta on the same slice). IC, WC, nIC of arterial phase and venous phase between stage T3 and T4a lesions were compared with double independent sample t test and compared with pathology. The diagnostic efficacy was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTSDuring arterial phase in stage T4a cases, IC (100 μg/ml) was -5.19±0.81 and nIC was -0.05±0.01, which was significantly higher than -3.44±1.54 (P=0.000) and -0.03±0.01 (P=0.000) in stage T3 cases. During venous phase in T4a cases, IC (100 μg/ml) was -3.78±0.94 and nIC was -0.04±0.01, which was significantly higher than -1.62±1.43 (P=0.000) and -0.02±0.02 (P=0.000) in stage T3 cases. As compared to arterial phase, IC and nIC of stage T4a and T3 of venous phase were more significantly different (all P<0.05). WC of stage T4a during arterial and venous phase was 955.72±15.68 and 949.86±17.36 respectively, while WC of stage T3 during arterial and venous phase was 947.77±18.43 and 942.46±18.53 respectively. There were no significant differences in WC between two stage cases during arterial and venous phase (P=0.106, P=0.143). ROC analysis showed that area under the ROC of IC and nIC during arterial phase was 0.829 and 0.867 respectively, and cut-off value of nIC was -0.039 for differentiation of stage T3 and T4a with corresponding 83.3% of sensitivity and 75.0% of specificity; area under the ROC of IC and nIC during venous phase was 0.873 and 0.905 respectively, and cut-off value of nIC was -0.031 for differentiation of stage T3 and T4a with corresponding 81.0% of sensitivity and 85.0% of specificity.

CONCLUSIONSAbdominal spectral CT scan is useful in the differentiation of stage T3 and T4a gastric carcinoma. The IC of perigastric fat tissue is significantly higher in stage T4a gastric carcinoma compared to stage T3 gastric carcinoma. Higher diagnostic efficacy can be obtained when taking -0.031 as the cut-off value of nIC during venous phase.

Adipose Tissue ; Adult ; Aged ; Female ; Humans ; Iodine ; Male ; Middle Aged ; Neoplasm Staging ; ROC Curve ; Retrospective Studies ; Sensitivity and Specificity ; Stomach Neoplasms ; diagnosis ; Tomography, X-Ray Computed

Objective:To investigate the clinical application value of amplitude-integrated electroencephalogram (aEEG) in evaluating the prognosis of brain function in children with disturbance of consciousness.Methods:A total of 100 children with disturbance of consciousness admitted to the pediatric intensive care unit (PICU) in the Third Affiliated Hospital of Zhengzhou University from October 2018 to September 2019 were enrolled.All patients completed aEEG and video electroencephalogram (vEEG) (monitoring hours≥ 6 h), modified Glasgow coma scale (GCS) rating, peripheral blood brain injury marker S100β protein and neuron-specific enolase (NSE) detection within 48 hours of admission.The prognosis was evaluated based on the above results.The actual prognosis of the children was recorded by telephone follow-up based on the pediatric cerebral performance category score (PCPC) until 6 months of onset or clinical death.The receiver operating characteristic curve (ROC) was used to analyze and compare the clinical efficacy of aEEG, vEEG, improved GCS, S100β protein, and NSE in evaluating the prognosis of brain function in children with disturbance of consciousness. Kappa consistency test was made to evaluate the correlation between the estimated prognosis and the actual prognosis. Results:The area under the ROC curve (AUC) of aEEG, vEEG, improved GCS, S100β protein and NSE was 0.847, 0.810, 0.729, 0.685 and 0.784, respectively, indicating the five methods had statistically significant value in evaluating the prognosis of brain function (all P<0.05). Taking the Z value as the gold standard, the clinical efficacy of aEEG in evaluating the prognosis of brain function was significantly different from that of S100β ( Z>1.96, P<0.05), but showed no significant difference with that of other 3 methods.Using the best cut-off value as the gold standard for evaluating the prognosis, aEEG had the highest sensitivity to evaluate a poor prognosis (90.5%). The Kappa consistency test showed that the prognosis predicted by aEEG was consistent with the actual prognosis ( Kappa=0.550, P<0.01). Conclusions:aEEG has a good evaluation value for the brain function prognosis of children with disturbance of consciousness.aEEG has high sensitivity, and the predicated prognosis is consistent with the actual clinical prognosis, so it can be widely used in the diagnosis and treatment of PICU.

Objective We sought to determine whether SF3a3 was capable of inhibiting HCV replication and to investigate the possible mechanisms.Methods Using the infectious HCV clones JFH1, we performed siRNA knockdown in Huh7.5.1 cells.First, we performed small interfering RNA (siRNA) to knock down SF3 gene expression.After 72 h incubation, Huh7.5.1 cells were infected with JFH1 for 24 h and then treated with 30IU/ml PEG-IFNα-2b for 48h.Members of SF3 family, HCV core and the key proteins of the IFN relative pathways were monitored by real time PCR and Western blot.Results SF3a3 mRNA level and protein expression were significantly decreased by SF3a3 specific siRNA compared with non-targeting siRNA, whose silencing effect was the best compared with other members of SF3a3 family;knockdown of SF3a3 protein expression by siRNA rescued HCV core expression, inhibited the role of interferon in anti-HCV infection under the same PEG-IFNα-2b pressure, and downregulated the phosphorylation of PI3K and Akt, as well as their total protein levels.Conclusions Silencing SF3a3 by specific siRNA could downregulate the expression of PI3K-Akt and p-PI3K/p-Akt proteins, which promoted the HCV replication.

Panax notoginseng is a traditional Chinese medicinal herb in China. Due to its widespread pharmacology and significant clinical effect, the demand of Panax notoginseng is increasing surprisingly. Saponins are effective components in Radix Notoginseng. It has the effect of stopping bleeding and dispelling blood stasis. The content of saponins is affected by the factors such as location, variety and origin. This paper mainly introduced the notoginsenoside in different parts, the factors (origin and varieties) affecting the contents of notoginsenoside. A standard and pollution-free cultivation system of Panax notoginseng was established to help to cultivate the high-yield, high-quality and pollution-free P.notoginseng, which can provide the basis for choosing reasonable administration parts and provide the references for the development and utilization of Panax notoginseng.

Objective To evaluate the effect of " elite small class" training mode in capacity building for general practitioners in Yiwu city. Methods The Fourth Affiliated Hospital of Zhejiang University School of Medicine worked with Yiwu Health Bureau, and held the first training class for general practitioners from December 6th in 2018 to April 5th in 2019.The mode of " elite small-class" was adopted. Theoretical assessment was carried out for trainees before and after the training and discussion was conducted after the training. Descriptive analysis of quantitative data and thematic analysis of qualitative data were carried out. Results The trainees′theoretical performance had been significantly improved after 4 months of theoretical learning and clinical rotation.The average score of the theoretical performance was increased from 66.94 to 72.59. Conclusions It was preliminarily found that the " elite small-class" training mode was suitable for the training of general practitioners in rural areas.Government support and trainee selection are key to training outcomes.

Objective:To investigate the predictive model construction of anastomotic thickening character after radical surgery of esophageal cancer based on computed tomogralphy(CT) radiomics and its application value.Methods:The retrospective cohort study was conducted. The clinicopathological data of 202 patients with esophageal squamous cell carcinoma (ESCC) who were admitted to The First Affiliated Hospital of Zhengzhou University from January 2013 to June 2021 were collected. There were 147 males and 55 females, aged (63±8) years. Based on random number table, 202 patients were assigned into training dataset and validation dataset at a ratio of 7:3, including 141 cases and 61 cases respectively. Patients underwent radical resection of ESCC and enhanced CT examination. Observation indicators: (1) influencing factor analysis of malignant anas-tomotic thickening; (2) construction and evaluation of predictive model; (3) performance comparison of 3 predictive models. The normality of continuous variables was tested by Kolmogorov-Smirnov method. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was analyzed using the t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was analyzed using the Mann-Whintney U test. Count data were represented as absolute numbers, and comparison between groups was analyzed using the chi-square test or Fisher's exact probability. The consistency between subjective CT features by two doctors and measured CT numeric variables was analyzed by Kappa test and intraclass correlation coefficient (ICC), with Kappa >0.6 and ICC >0.6 as good consistency. Univariate analysis was conducted by corresponding statistic methods. Multivariate analysis was conducted by Logistics stepwise regression model. The receiver operating characteristic (ROC) curve was drawn, and area under curve (AUC), Delong test, decision curve were used to evaluate the diagnostic efficiency and clinical applicability of model. Results:(1) Influencing factor analysis of malignant anastomotic thickening. Of the 202 ESCC patients, 97 cases had malignant anastomotic thickening and 105 cases had inflammatory anastomotic thickening. The consistency between subjective CT features by two doctors and measured CT numeric variables showed Kappa and ICC values >0.6. Results of multivariate analysis showed that the maximum thickness of anastomosis and CT enhancement pattern were independent influencing factors for malignant anastomotic thickening[ hazard ratio=1.46, 3.09, 95% confidence interval ( CI) as 1.26-1.71,1.18-8.12, P<0.05]. (2) Construction and evaluation of predictive model. ① Clinical predictive model. The maximum thickness of anasto-mosis and CT enhancement pattern were used to construct a clinical predictive model. ROC curve of the clinical predictive model showed an AUC, accuracy, sensitivity, specificity as 0.86 (95% CI as 0.80-0.92),0.77, 0.77, 0.80 for the training dataset, and 0.78 (95% CI as 0.65-0.89), 0.77, 0.77, 0.80 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=1.22, P>0.05). ② Radiomics predictive model. A total of 854 radiomics features were extracted and 2 radiomics features (wavelet-LL_first order_ Maximum and original_shape_VoxelVolume) were finally screened out to construct a radiomics predictive model. ROC curve of the radiomics predictive model showed an AUC, accuracy, sensitivity, specificity as 0.87 (95% CI as 0.81-0.93), 0.80, 0.75, 0.86 for the training dataset, and 0.73 (95% CI as 0.63-0.83), 0.80, 0.76, 0.94 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=-0.25, P>0.05). ③ Combined predictive model. Results of multivariate analysis and radiomics features were used to construct a combined predictive model. ROC curve of the combined predictive model showed an AUC, accuracy, sensitivity, specificity as 0.93 (95% CI as 0.89-0.97),0.84, 0.90, 0.84 for the training dataset, and 0.79 (95% CI as 0.70-0.88), 0.89, 0.86, 0.91 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=0.22, P>0.05). (3) Performance comparison of 3 predictive models. Results of Hosmer-Lemeshow goodness-of-fit test showed that the clinical predictive model, radiomics predictive model and combined predictive model had a good fitting degree ( χ2=4.88, 7.95, 4.85, P>0.05). Delong test showed a significant difference in AUC between the combined predictive model and clinical predictive model, also between the combined predictive model and radiomics predictive model ( Z=2.88, 2.51, P<0.05 ). There was no significant difference in AUC between the clinical predictive model and radiomics predictive model ( Z=-0.32, P>0.05). The calibration curve showed a good predictive performance in the combined predictive model. The decision curve showed a higher distinguishing performance for anastomotic thickening character in the combined predictive model than in the clinical predictive model or radiomics predictive model. Conclusions:The maximum thickness of anastomosis and CT enhancement pattern are independent influencing factors for malignant anastomotic thickening. Radiomics predictive model can distinguish the benign from malignant thickening of anastomosis. Combined predictive model has the best diagnostic efficacy.