Prediction of Abdominal Visceral Obesity From Body Mass Index,Waist Circumference and Waist-hip Ratio in Chinese Adults:Receiver Operating Characteristic Curves Analysis

Objective To evaluate the sensitivity and specificity of body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) measurements in diagnosing abdominal visceral obesity. Methods BMI, WC, and WHR were assessed in 690 Chinese adults (305 men and 385 women) and compared with magnetic resonance imaging (MRI) measurements of abdominal visceral adipose tissue (VA). Receiver operating characteristic (ROC) curves were generated and used to determine the threshold point for each anthropometric parameter. Results 1) MRI showed that 61.7% of overweight/obese individuals (BMI≥25 kg/m2) and 14.2% of normal weight (BMI<25 kg/m2) individuals had abdominal visceral obesity (VA≥100 cm2). 2) VA was positively correlated with each anthropometric variable, of which WC showed the highest correlation (r=0.73-0.77, P<0.001). 3) The best cut-off points for assessing abdominal visceral obesity were as followed: BMI of 26 kg/m2, WC of 90 cm, and WHR of 0.93, with WC being the most sensitive and specific factor. 4) Among subjects with BMI≥28 kg/m2 or WC≥95 cm, 95% of men and 90% of women appeared to have abdominal visceral obesity. Conclusion Measurements of BMI, WC, and WHR can be used in the prediction of abdominal visceral obesity, of which WC was the one with better accuracy.

Using receiver operating characteristic curves to evaluate the diagnostic value of the combination of multislice spiral CT and alpha-fetoprotein levels for small hepatocellular carcinoma in cirrhotic patients

BACKGROUND： The various combination of multiphase enhancement multislice spiral CT （MSCT） makes the diagno- sis of a small hepatocellular carcinoma （sHCC） on the back- ground of liver cirrhosis possible. This study was to explore whether the combination of MSCT enhancement scan and alpha-fetoprotein （AFP） level ficiency for sHCC. could increase the diagnostic ef- METHODS： This study included 35 sHCC patients and 52 cir- rhotic patients without image evidence of HCC as a control group. The diagnoses were made by three radiologists em- ploying a 5-point rating scale, with postoperative pathologic results as the gold standard. Receiver operating characteristic （ROC） curve analysis was performed to evaluate the diag- nostic value of the three MSCT combination modes （arterial phase＋portal-venous phase, arterial phase＋delayed phase, arterial phase＋portal-venous phase＋delayed phase） and AFP levels for sHCC on the background of liver cirrhosis. RESULTS： The area under ROC curve （AUC）, sensitivity, and specificity of the combination of arterial phase＋portal- venous phase＋delayed phase were 0.93, 93%, and 82%, respectively. The average AUC of the arterial phase＋portal- venous phase＋delayed phase combination was significantly greater than that of the arterial phase＋portal-venous phase （AUC=0.84, P=0.01） and arterial phase＋delayed phase （AUC=0.85, P=0.03）. Arterial phase＋portal-venous phase had a smaller AUC （0.84） than arterial phase＋delayed phase （0.85）, but the difference was insignificant （P=0.15）. After combining MSCT enhancement scan with AFP, the AUC, sensitivity, and specificity were 0.95, 94%, and 83%, respectively, indicating a greatly increased diagnostic efficiency for sHCC. CONCLUSIONS： The combination of AFP and 3 phases MSCT enhancement scan could increase the diagnostic efficiency for sHCC on the background of liver cirrhosis. The application of ROC curve analysis has provided a new method and reference in HCC diagnosis.

Determination of the diagnostic value of the resazurin reduction assay for evaluating boar semen by receiver operating characteristic analysis

Aim： To assess that metabolic status of spermatozoa could provide a useful tool for evaluation of semen quality. Methods： The accuracy of the spectrophotometric application of the resazurin reduction assay was assessed using receiver operating characteristic （ROC） analysis. Results： Areas under ROC curves （AUC） for motile sperm concentration and sperm index （SI） （sperm concentration multiplied by the square root of percentage sperm motility multiplied by the percentage normal sperm morphology） were 0.922. The best discrimination between poor and good semen samples according to the SI was achieved at a cut-off point of A610 = 0.209, where high sensitivity （94.1%） and specificity （91.7%） were calculated. The assay was less accurate when motile sperm concentration was used as the criterion value, yielding sensitivity of 88.2% and specificity of 87.5%, respectively. Likelihood ratios （LR） indicate that absorbances lower than 0.209 were at least 11.3 times as likely to be found in good semen samples than those in poor according to the SI, whereas in the case of motile sperm concentration, the LR was calculated to be 7.06. Conclusion： These results show that the resazurin reduction assay combined with spectrophotometry is an accurate method of assessing the quality of boar semen.

Study on Diagnosis Criteria of Fire-Heat Syndrome Based on Receiver Operating Characteristic Curve and Principal Component Analysis

Objective： To establish the diagnostic quantitative criteria for fire-heat syndrome （FHS） of Chinese medicine （CM） based on the receiver operating characteristic （ROC） curve and principal component analysis （PCA）. Methods： The symptoms and signs of FHS cases and healthy subjects from Guangzhou, Henan and Hunan of China were collected through questionnaire, and the diagnostic quantitative score tables were established for the three regions, respectively, with the method of maximum likelihood analysis. The homogeneity test was then performed on the diagnostic score tables for the three regions with ROC curve, and the diagnostic efficiency of diagnostic score tables for the three regions was compared with the prospective test and retrospective test. The method of PCA was adopted to obtain the analysis matrix for classifying the tapes of FHS. Results： Twenty-seven elements of FHS were confirmed through Chi-square test, and the diagnostic score tables for the three regions were established with the method of maximum likelihood analysis on the basis of the collected case data. According to the ROC curve test, the areas under ROC curve of Guangzhou diagnostic score table assessment with candidates in Guangzhou, Henan and Hunan were 0.998, 0.961 and 0.956, respectively. It showed that the diagnostic efficiency of Guangzhou diagnostic score tables was the highest one. With the prospective test, the area under ROC of Guangzhou diagnostic score table was 0.949, and more than any other diagnostic score table. By PCA, FHS was classified into excess fire and deficiency fire, and then classified into syndrome of flaring up of Heart （Xin） fire, syndrome of Lung （Fei）-Stomach （Wei） excess fire, syndrome of deficiency of Liver （Gan）-yin and Kidney （Shen）-yin, and syndrome of deficiency of Lung-yin from the view of viscera. In the retrospective test, the consistency with clinicians＇ diagnosis was 69.4%, and in the prospective test, it was 70.1%. Conclusions： The Guangzhou diagnostic score table could be used as the recommended criteria for the diagnosis of FHS. The classification of FHS was basically in conformity with the clinical situation.

Receiver operating characteristic curve analysis for image quality in the detection of solitary pulmonary nodules on high resolution paper prints versus dry laser film

Along with the development of digital X-ray imaging technology, a new, economical and practicalpaper-based output system gradually emerged. To reduce cost, more and more radiologic institutions began to change from film copies to lower-priced paper prints for documenting radiologic findings.Therefore, laser paper printers are frequently used as an alternative to duplicating film though the use of printed images is not yet widespread. The aim of this study was to compare the practical value of high-resolution paper printer with dry film copies for detecting small solitary pulmonary nodules （SPNs）.

Nomogram for predicting lymph node metastasis rate of submucosal gastric cancer by analyzing clinicopathological characteristics associated with lymph node metastasis

Background： To combine dinicopathological characteristics associated with lymph node metastasis for submucosal gastric cancer into a nomogram. Methods： We retrospectively analyzed 262 patients with submucosal gastric cancer who underwent D2 gastrectomy between 1996 and 2012. The relationship between lymph node metastasis and clinicopathological features was statistically analyzed. With multivariate logistic regression analysis, we made a nomogram to predict the possibility of lymph node metastasis. Receiver operating characteristic （ROC） analysis was also performed to assess the predictive value of the model. Discrimination and calibration were performed using internal validation. Results： A total number of 48 （18.3%） patients with submucosal gastric cancer have pathologically lymph node metastasis. For submucosal gastric carcinoma, lymph node metastasis was associated with age, tumor location, macroscopic type, size, differentiation, histology, the existence of ulcer and lymphovascular invasion in univariate analysis （all P〈0.05）. The multivariate logistic old, macroscopic type III or mixed, undifferentiated type, regression analysis identified that age _〈50 years and presence of lymphovascular invasion were independent risk factors of lymph node metastasis in submucosal gastric cancer （all P〈0.05）. We constructed a predicting nomogram with all these factors for lymph node metastasis in submucosal gastric cancer with good discrimination [area under the curve （AUC） =0.844]. Internal validation demonstrated a good discrimination power that the actual probability corresponds closely with the predicted probability. Conclusions： We developed a nomogram to predict the rate of lymph node metastasis for submucosal gastric cancer. With good discrimination and internal validation, the nomogram improved individualized predictions for assisting clinicians to make appropriated treatment decision for submucosal gastric cancer patients.

Prediction of Flash Flood Susceptibility of Hilly Terrain Using Deep Neural Network:A Case Study of Vietnam

Flash floods are one of the most dangerous natural disasters,especially in hilly terrain,causing loss of life,property,and infrastructures and sudden disruption of traffic.These types of floods are mostly associated with landslides and erosion of roads within a short time.Most of Vietnamis hilly and mountainous;thus,the problem due to flash flood is severe and requires systematic studies to correctly identify flood susceptible areas for proper landuse planning and traffic management.In this study,three Machine Learning(ML)methods namely Deep Learning Neural Network(DL),Correlation-based FeatureWeighted Naive Bayes(CFWNB),and Adaboost(AB-CFWNB)were used for the development of flash flood susceptibility maps for hilly road section(115 km length)of National Highway(NH)-6 inHoa Binh province,Vietnam.In the proposedmodels,88 past flash flood events were used together with 14 flash floods affecting topographical and geo-environmental factors.The performance of themodels was evaluated using standard statisticalmeasures including Receiver Operating Characteristic(ROC)Curve,Area Under Curve(AUC)and Root Mean Square Error(RMSE).The results revealed that all the models performed well(AUC>0.80)in predicting flash flood susceptibility zones,but the performance of the DL model is the best(AUC:0.972,RMSE:0.352).Therefore,the DL model can be applied to develop an accurate flash flood susceptibility map of hilly terrain which can be used for proper planning and designing of the highways and other infrastructure facilities besides landuse management of the area.

Serum N-glycan markers for diagnosing liver fibrosis induced by hepatitis B virus

BACKGROUND Hepatitis B virus (HBV) infection is the primary cause of hepatitis with chronic HBV infection,which may develop into liver fibrosis,cirrhosis and hepatocellular carcinoma.Detection of early-stage fibrosis related to HBV infection is of great clinical significance to block the progression of liver lesion.Direct liver biopsy is regarded as the gold standard to detect and assess fibrosis;however,this method is invasive and prone to clinical sampling error.In order to address these issues,we attempted to find more convenient and effective serum markers for detecting HBV-induced early-stage liver fibrosis.AIM To investigate serum N-glycan profiling related to HBV-induced liver fibrosis and verify multiparameter diagnostic models related to serum N-glycan changes.METHODS N-glycan profiles from the sera of 432 HBV-infected patients with liver fibrosis were analyzed.Significant changed N-glycan levels (peaks)(P <0.05) in differentfibrosis stages were selected in the modeling group,and multiparameter diagnostic models were established based on changed N-glycan levels by logistic regression analysis.The receiver operating characteristic (ROC) curve analysis was performed to evaluate diagnostic efficacy of N-glycans models.These models were then compared with the aspartate aminotransferase to platelet ratio index (APRI),fibrosis index based on the four factors (FIB-4),glutamyltranspeptidase platelet albumin index (S index),GlycoCirrho-test,and GlycoFibro-test.Furthermore,we combined multiparameter diagnostic models with alanine aminotransferase (ALT) and platelet (PLT) tests and compared their diagnostic power.In addition,the diagnostic accuracy of N-glycan models was also verified in the validation group of patients.RESULTS Multiparameter diagnostic models constructed based on N-glycan peak 1,3,4and 8 could distinguish between different stages of liver fibrosis.The area under ROC curves (AUROCs) of Model A and Model B were 0.890 and 0.752,respectively differentiating fibrosis F0-F1 from F2-F4,and F0-F2 from F3-F4,and surpassing other serum panels.However,AUROC (0.747) in Model C used for the diagnosis of F4 from F0-F3 was lower than AUROC (0.795) in FIB-4.In combination with ALT and PLT,the multiparameter models showed better diagnostic power (AUROC=0.912,0.829,0.885,respectively) when compared with other models.In the validation group,the AUROCs of the three combined models (0.929,0.858,and 0.867,respectively) were still satisfactory.We also applied the combined models to distinguish adjacent fibrosis stages of 432patients (F0-F1/F2/F3/F4),and the AUROCs were 0.917,0.720 and 0.785.CONCLUSION Multiparameter models based on serum N-glycans are effective supplementary markers to distinguish between adjacent fibrosis stages of patients caused by HBV,especially in combination with ALT and PLT.

Prognostic relevance of β-catenin expression in T2-3N0M0 esophageal squamous cell carcinoma

AIM: To study the expression of β-catenin in esophageal squamous cell carcinoma (ESCC) at stage T2-3N0M0 and its relation with the prognosis of ESCC patients. METHODS: Expression of β-catenin in 227 ESCC speci-mens was detected by immunohistochemistry (IHC). A reproducible semi-quantitative method which takes both staining percentage and intensity into account was applied in IHC scoring, and receiver operating char-acteristic curve analysis was used to select the cut-off score for high or low IHC reactivity. Then, correlation of β-catenin expression with clinicopathological features and prognosis of ESCC patients was determined. RESULTS: No significant correlation was observed between β-catenin expression and clinicopathological parameters in terms of gender, age, tumor size, tumor grade, tumor location, depth of invasion and pathologi-cal stage. The Kaplan-Meier survival curve showed that the up-regulated expression of β-catenin indicated a poorer post-operative survival rate of ESCC patients at stage T2-3N0M0 (P = 0.004), especially of those with T3 lesions (P = 0.014) or with stage ⅡB diseases (P = 0.007). Multivariate analysis also confirmed that β-catenin was an independent prognostic factor for the overall survival rate of ESCC patients at stage T2-3N0M0 (relative risk = 1.642, 95% CI: 1.159-2.327, P = 0.005). CONCLUSION: Elevated β-catenin expression level may be an adverse indicator for the prognosis of ESCC patients at stage T2-3N0M0, especially for those with T3 lesions or stage ⅡB diseases.

Serum gastrin-17 concentration for prediction of upper gastrointestinal tract bleeding risk among peptic ulcer patients

BACKGROUND Serum gastrin-17(G-17),pepsinogen I(PGI),and pepsinogen II(PGII)concentrations regulate gastric acid secretion,and hypersecretion of gastric acid increases the risks of peptic ulcer and upper gastrointestinal bleeding.These associations suggest that serum G-17,PGI,and(or)PGII may predict gastrointestinal bleeding risk among peptic ulcer patients.AIM To evaluate the efficacies of serum G-17,PGI,PGII,and PGI/PGII ratio(PGR)for predicting upper gastrointestinal bleeding among peptic ulcer patients.METHODS A total of 199 patients diagnosed with peptic ulcer confirmed by gastroscopy and positivity for Helicobacter pylori by the 14C-urea breath test were recruited,including 107 patients with simple peptic ulcer and 92 cases complicated by upper gastrointestinal bleeding.Serum PGI,PGII,G-17,and PGR were measured by immune methods and compared between bleeding and non-bleeding groups by univariate analysis.The specificity and sensitivity of PGs and G-17 for evaluating upper gastrointestinal bleeding risk were then assessed by constructing receiver operating characteristic(ROC)curves.RESULTS Serum G-17 was significantly higher among peptic ulcer patients with upper gastrointestinal bleeding compared to simple peptic ulcer patients(25.34±14.29 vs 8.84±8.03 pmol/L,t=9.822,P<0.01),whereas serum PGI,PGII,and PGR did not differ significantly between bleeding and non-bleeding groups(all P>0.05).The risk of bleeding was significantly higher among peptic ulcer patients with elevated serum G-17(>15 pmol/L)compared to patients with normal or low serum G-17(73.2%vs 27.4%,χ2=40.72,P<0.01).The area under the ROC curve for serum G-17 was 0.866±0.024,and a cut-off of 9.86 pmol/L yielded 90.2%sensitivity and 68.2%specificity for distinguishing peptic ulcer with and without upper gastrointestinal bleeding.CONCLUSION Serum G-17 is significantly upregulated in peptic ulcer patients and higher levels are predictive of upper gastrointestinal bleeding.Conversely,serum PGI,PGII,and PGR have no predictive value.Further prospective studies are warranted to examine if high G-17 can be used to assess risk of bleeding prior to onset.

Applying deep learning and benchmark machine learning algorithms for landslide susceptibility modelling in Rorachu river basin of Sikkim Himalaya, India

Landslide is considered as one of the most severe threats to human life and property in the hilly areas of the world.The number of landslides and the level of damage across the globe has been increasing over time.Therefore,landslide management is essential to maintain the natural and socio-economic dynamics of the hilly region.Rorachu river basin is one of the most landslide-prone areas of the Sikkim selected for the present study.The prime goal of the study is to prepare landslide susceptibility maps(LSMs)using computer-based advanced machine learning techniques and compare the performance of the models.To properly understand the existing spatial relation with the landslide,twenty factors,including triggering and causative factors,were selected.A deep learning algorithm viz.convolutional neural network model(CNN)and three popular machine learning techniques,i.e.,random forest model(RF),artificial neural network model(ANN),and bagging model,were employed to prepare the LSMs.Two separate datasets including training and validation were designed by randomly taken landslide and nonlandslide points.A ratio of 70:30 was considered for the selection of both training and validation points.Multicollinearity was assessed by tolerance and variance inflation factor,and the role of individual conditioning factors was estimated using information gain ratio.The result reveals that there is no severe multicollinearity among the landslide conditioning factors,and the triggering factor rainfall appeared as the leading cause of the landslide.Based on the final prediction values of each model,LSM was constructed and successfully portioned into five distinct classes,like very low,low,moderate,high,and very high susceptibility.The susceptibility class-wise distribution of landslides shows that more than 90%of the landslide area falls under higher landslide susceptibility grades.The precision of models was examined using the area under the curve(AUC)of the receiver operating characteristics(ROC)curve and statistical methods like root mean square error(RMSE)and mean absolute error(MAE).In both datasets(training and validation),the CNN model achieved the maximum AUC value of 0.903 and 0.939,respectively.The lowest value of RMSE and MAE also reveals the better performance of the CNN model.So,it can be concluded that all the models have performed well,but the CNN model has outperformed the other models in terms of precision.

Serum hepatitis B core-related antigen as a surrogate marker of hepatitis B e antigen seroconversion in chronic hepatitis B

BACKGROUND Quantitative hepatitis B core-related antigen(qHBcrAg)has a better correlation with intrahepatic hepatitis B virus(HBV)covalently closed circular DNA(cccDNA)than HBV DNA or hepatitis B e antigen(HBeAg),but data are still lacking for its clinical application.AIM The aim was to investigate serum qHBcrAg levels in patients with chronic hepatitis B and assess the correlation of serum qHBcrAg with pregenomic RNA(pgRNA),cccDNA,and HBeAg seroconversion.METHODS This study was a secondary analysis of patients who underwent percutaneous liver biopsy between July 2014 and June 2019 in two multicenter randomized controlled clinical trials of peginterferon vs nucleos(t)ide analog(NUC)-based therapy(NCT03509688 and NCT03546530).Serum qHBcrAg,pgRNA,HBV DNA,hepatitis B core antigen,HBeAg,liver cccDNA,and HBV DNA were measured.The correlations of serum qHBcrAg with other biomarkers were analyzed.RESULTS A total of 139 patients were included.The mean qHBcrAg levels were 5.32±1.18 log10 U/mL at baseline and decreased during treatment(all P<0.0001).Serum qHBcrAg levels were positively correlated with pgRNA(r=0.597,P<0.0001)and cccDNA(r=0.527,P<0.0001)levels.The correlation of serum qHBcrAg level and intrahepatic HBV DNA levels at baseline was weak but significant(r=0.399,P<0.0001).HBcrAg predicted HBeAg seroconversion,with areas under the receiver operating characteristics curve of 0.788 at 24 wk and 0.825 at 48 wk.Log HBcrAg at wk 24 and 48 was independently associated with HBeAg seroconversion[odds ratio(OR)=2.402,95%confidence interval(CI):1.314-4.391,P=0.004;OR=3.587,95%CI:1.315-9.784,P=0.013].CONCLUSION Serum HBcrAg levels were correlated with HBV virological markers and could be used to predict HBeAg seroconversion.

Comparison of diagnostic validity of two autism rating scales for suspected autism in a large Chinese sample

BACKGROUND Autism is the most common clinical developmental disorder in children.The childhood autism rating scale(CARS)and autistic autism behavior checklist(ABC)are the most commonly used assessment scales for diagnosing autism.However,the diagnostic validations and the corresponding cutoffs for CARS and ABC in individuals with suspected autism spectrum disorder(ASD)remain unclear.Furthermore,for suspected ASD in China,it remains unclear whether CARS is a better diagnostic tool than ABC.Also unclear is whether the current cutoff points for ABC and CARS are suitable for the accurate diagnosis of ASD.AIM To investigate the diagnostic validity of CARS and ABC based on a large Chinese sample.METHODS A total of 591 outpatient children from the ASD Unit at Beijing Children’s Hospital between June and November 2019 were identified.First,the Clancy autism behavior scale(CABS)was used to screen out suspected autism from these children.Then,each suspected ASD was evaluated by CARS and ABC.Receiver operating characteristic(ROC)curve analysis was used to compare diagnostic validations.We also calculated the area under the curve(AUC)for both CARS and ABC.RESULTS We found that the Cronbach alpha coefficients of CARS and ABC were 0.772 and 0.426,respectively.Therefore,the reliability of the CARS was higher than that of the ABC.In addition,we found that the correlation between CARS and CABS was 0.732.Next,we performed ROC curve analysis for CARS and ABC,which yielded AUC values of 0.846 and 0.768,respectively.The cutoff value,which is associated with the maximum Youden index,is usually applied as a decision threshold.We found that the cutoff values of CARS and ABC were 34 and 67,respectively.CONCLUSION This result indicated that CARS is superior to ABC in the Chinese population with suspected ASD.

Serum neuron-specific enolase:A promising biomarker of silicosis

BACKGROUND Silicosis is a type of chronic pulmonary fibrosis caused by long-term inhalation of silica dust particles.There has been no ideal biomarker for the diagnosis and differential diagnosis of silicosis until now.Studies have found that elevated neuron-specific enolase(NSE)concentration in the serum of silicosis patients is helpful for diagnosis and severity assessment of the disease.However,the number of cases in these studies was not enough to arouse attention.AIM To investigate the clinical significance of serum NSE in the diagnosis and staging of silicosis.METHODS From January 2017 to June 2019,326 cases of silicosis confirmed in Quanzhou First Hospital Affiliated to Fujian Medical University were included in the silicosis group.A total of 328 healthy individuals or medical patients without silicosis were included in the control group.Serum NSE concentrations of all subjects were determined by electrochemical luminescence.RESULTS There were no significant differences in sex,age,smoking index and complications between the silicosis and control groups.The mean serum NSE concentration was 26.57±20.95 ng/mL in the silicosis group and 12.42±2.68 ng/mL in the control group.The difference between the two groups was significant(U=15187,P=0.000).Among the 326 patients with silicosis,103 had stage I silicosis,and the mean serum NSE concentration was 15.55±6.23 ng/mL.The mean serum NSE concentration was 21.85±12.05 ng/mL in 70 patients with stage II silicosis.The mean serum NSE concentration was 36.14±25.72 ng/mL in 153 patients with stage III silicosis.Kruskal-Wallis H test suggested that the difference in serum NSE concentration in silicosis patients in the three groups was significant(H=130.196,P=0.000).Receiver operating characteristic curve analysis indicated that the area under the curve was 0.858(95%confidence interval:0.828-0.888;P=0.000).When the NSE concentration was 15.82 ng/mL,the Jorden index was the largest,the sensitivity was 72%,and the specificity was 90%.CONCLUSION Serum NSE concentration may be a promising biomarker for the diagnosis and assessment of severity of silicosis.

High-resolution computed tomography findings independently predict epidermal growth factor receptor mutation status in groundglass nodular lung adenocarcinoma

BACKGROUND For lung adenocarcinoma with epidermal growth factor receptor(EGFR)gene mutation,small molecule tyrosine kinase inhibitors are more effective.Some patients could not obtain enough histological specimens for EGFR gene mutation detection.Specific imaging features can predict EGFR mutation status to a certain extent.AIM To assess the associations of EGFR mutations with high-resolution computerized tomography(HRCT)features in ground-glass nodular lung adenocarcinoma.METHODS This study retrospectively assessed patients with ground-glass nodular lung adenocarcinoma diagnosed between January 2011 and March 2017.EGFR gene mutations in exons 18-21 were detected.The patients were classified into mutant EGFR and wild-type groups,and general data and HRCT image characteristics were assessed.RESULTS Among 98 patients,31(31.6%)and 67(68.4%)had mutated and wild-type EGFR in exons 18-21,respectively.Gender,age,smoking history,location of lesions,morphology,edges,borders,pleural indentations,and associations of nodules with bronchus and blood vessels were comparable in both groups(all P>0.05).Patients with mutant EGFR had larger nodules than those with the wild-type(17.19±6.79 and 14.37±6.30 mm,respectively;P=0.047).Meanwhile,the vacuole/honeycomb sign was more frequent in the mutant EGFR group(P=0.011).The logistic regression prediction model included the combination of nodule size and vacuole/honeycomb sign(OR=1.120,95%CI:1.023-1.227,P=0.014)revealed a sensitivity of 83.9%,a specificity of 52.2%and an AUC of 0.698(95%CI:0.589-0.806;P=0.002).CONCLUSION Nodule size and vacuole/honeycomb features could independently predict EGFR mutation status in ground-glass nodular lung adenocarcinoma.

Evaluation of high-risk factors and the diagnostic value of alpha-fetoprotein in the stratification of primary liver cancer

BACKGROUND Alpha-fetoprotein(AFP)is one of the diagnostic standards for primary liver cancer(PLC);however,AFP exhibits insufficient sensitivity and specificity for diagnosing PLC.AIM To evaluate the effects of high-risk factors and the diagnostic value of AFP in stratified PLC.METHODS In total,289 PLC cases from 2013 to 2019 were selected for analysis.First,the contributions of high-risk factors in stratifying PLC were compared according to the following criteria:Child–Pugh score,clinical stage of liver cirrhosis,tumor size,and Barcelona Clinic Liver Cancer(BCLC)stage.Then,the diagnostic value of AFP was evaluated in different stratifications of PLC by receiver operating characteristic curves.For PLC cases in which AFP played little role,the diagnostic values of carcinoembryonic antigen(CEA),carbohydrate antigen 19-9(CA 19-9),gamma-glutamyl transferase(GGT),and AFP were analyzed.RESULTS The roles of high-risk factors differed in stratified PLC.The incidence of smoking and drinking history was higher in PLC with Child–Pugh scores of C(P<0.0167).The hepatitis B virus(HBV)infection rate in PLC with cirrhosis was more than in PLC without cirrhosis(P<0.0167).Small tumors were more prone to cirrhosis than large tumors(P<0.005).BCLC stage D PLC was more likely to be associated with HBV infection and cirrhosis(P<0.0083).AFP levels were higher in PLC with cirrhosis,diffuse tumors,and BCLC stage D disease.In diagnosing PLC defined as Child–Pugh A,B,and C,massive hepatoma,diffuse hepatoma,BCLC stage B,C,and D,and AFP showed significant diagnostic value[all area under the curve(AUC)>0.700].However,these measures were meaningless(AUC<0.600)in small hepatomas and BCLC A stage PLC,but could be replaced by the combined detection of CEA,CA 19-9,GGT,and AFP(AUC=0.810 and 0.846,respectively).CONCLUSION Stratification of PLC was essential for precise diagnoses and benefited from evaluating AFP levels.

Fraud Identification of Chinese Listed Companies——an Improvement Based on M-Score

To evaluate the applicability of the M-score model in the Chinese capital market,this research observed 190 financial fraud samples punished by the China Securities Regulatory Commission(CSRC)in the years from 2014 to 2018.The test results indicate that two types of errors are high,which means that the applicability of the M-score is unacceptable.Therefore,in this paper,a 9-index model is constructed by Wald's backward stepwise regression method,and the optimal threshold is set by the Beneish expected cost method(ECM).The accuracy of the modified M-score is significantly improved,especially the Type I error rate of is reduced from 70.37%to 19.75%.The receiver operating characteristic(ROC)curve test also proves the superior identification effect of the modified M-score applied in the Chinese market.Finally,variables such as current ratio,fixed asset index,and equity concentration in the modified model could represent the fraud characteristics of Chinese listed companies.

A Novel Prognostic Score for Acute-on-Chronic Hepatitis B Liver Failure

Patients with acute-on-chronic hepatitis B liver failure（HBV-ACLF） show high morbidity and mortality. Independent prognostic predictors of short-term HBV-ACLF mortality include the Child-Turcotte-Pugh（CTP） score, the model for end-stage liver disease（MELD） score, other MELD-based indices and the dynamic changes in these indices. The aims of this study were to evaluate the existing prognostic scores in a large cohort of HBV-ACLF patients and create a new predictive model. We retrospectively reviewed 392 HBV-ACLF patients from December 2008 to November 2011 and evaluated their 3-month survival. The predictive accuracy of CTP, MELD and MELD-based indices and the dynamic changes in the MELD-related scores（Δ scoring systems） upon admission and after two weeks of treatment were compared using the area under the receiver operating characteristic（ROC） curve method. Life-threatening factors and a series of bio-clinical parameters were studied by univariate and multivariate analyses. Among the existing scores, MELD had the best predictive ability. However, our new regression model provided an area under the curve of 0.930±0.0161（95% CI： 0.869 to 0.943）, which was significantly larger than that obtained with the MELD score at admission and after two weeks of treatment as well as with the dynamic changes of the MELD score（0.819, 0.921, and 0.826, respectively）（Z=3.542, P=0.0004）. In a large cohort of patients retrospectively reviewed for this study, our prognostic model was superior to the MELD score and is, therefore, a promising predictor of short-term survival in patients with HBV-ACLF.

A method of line spectrum extraction based on target radiated spectrum feature and its post-processing

To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum that the high intense and stable line spectrum is superimposed on the wide continuous spectrum.This method modifies the traditional beam forming algorithm by calculating and fusing the beam forming results at multi-frequency band and multi-azimuth interval,showing an excellent way to extract the line spectrum when the interference and the target are not in the same azimuth interval simultaneously.Statistical efficiency of the estimated azimuth variance and corresponding power of the line spectrum band depends on the line spectra ratio(LSR)of the line spectrum.The change laws of the output signal to noise ratio(SNR)with the LSR,the input SNR,the integration time and the filtering bandwidth of different algorithms bring the selection principle of the critical LSR.As the basis,the detection gain of wideband energy integration and the narrowband line spectrum algorithm are theoretically analyzed.The simulation detection gain demonstrates a good match with the theoretical model.The application conditions of all methods are verified by the receiver operating characteristic(ROC)curve and experimental data from Qiandao Lake.In fact,combining the two methods for target detection reduces the missed detection rate.The proposed post-processing method in2-dimension with the Kalman filter in the time dimension and the background equalization algorithm in the azimuth dimension makes use of the strong correlation between adjacent frames,could further remove background fluctuation and improve the display effect.

Atherogenic index of plasma combined with waist circumference and body mass index to predict metabolic-associated fatty liver disease

BACKGROUND Early identification of metabolic-associated fatty liver disease(MAFLD)is urgent.Atherogenic index of plasma(AIP)is a reference predictor of obesity-related diseases,but its predictive value for MAFLD remains unclear.No studies have reported whether its combination with waist circumference(WC)and body mass index(BMI)can improve the predictive performance for MAFLD.AIM To systematically explore the relationship between AIP and MAFLD and evaluate its predictive value for MAFLD and to pioneer a novel noninvasive predictive model combining AIP,WC,and BMI while validating its predictive performance for MAFLD.METHODS This cross-sectional study consecutively enrolled 864 participants.Multivariate logistic regression analysis and receiver operating characteristic curve were used to evaluate the relationship between AIP and MAFLD and its predictive power for MAFLD.The novel prediction model A-W-B combining AIP,WC,and BMI to predict MAFLD was established,and internal verification was completed by magnetic resonance imaging diagnosis.RESULTS Subjects with higher AIP exhibited a significantly increased risk of MAFLD,with an odds ratio of 12.420(6.008-25.675)for AIP after adjusting for various confounding factors.The area under receiver operating characteristic curve of the A-W-B model was 0.833(0.807-0.858),which was significantly higher than that of AIP,WC,and BMI(all P<0.05).Subgroup analysis illustrated that the A-W-B model had significantly higher area under receiver operating characteristic curves in female,young and nonobese subgroups(all P<0.05).The best cutoff values for the A-W-B model to predict MAFLD in males and females were 0.5932 and 0.4105,respectively.Additionally,in the validation set,the area under receiver operating characteristic curve of the A-W-B model to predict MAFLD was 0.862(0.791-0.916).The A-W-B level was strongly and positively associated with the liver proton density fat fraction(r=0.630,P<0.001)and significantly increased with the severity of MAFLD(P<0.05).CONCLUSION AIP was strongly and positively associated with the risk of MAFLD and can be a reference predictor for MAFLD.The novel prediction model A-W-B combining AIP,WC,and BMI can significantly improve the predictive ability of MAFLD and provide better services for clinical prediction and screening of MAFLD.