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Analysis of risk factors leading to anxiety and depression in patients with prostate cancer after castration and the construction of a risk prediction model

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World Journal of Psychiatry 2024年第2期14卷 255-265页

作者： Rui-Xiao Li Xue-Lian Li Guo-Jun Wu Yong-Hua Lei Xiao-Shun Li Bo Li Jian-Xin Ni Urology Hospital Xi'an People's Hospital(Xi'an Fourth Hospital)Xi'an 710199Shaanxi ProvinceChina Department of Surgery Xi'an Hospital of Traditional Chinese MedicineXi'an 710199Shaanxi ProvinceChina

BACKGROUND Cancer patients often suffer from severe stress reactions psychologically,such as anxiety and *** cancer(PC)is one of the common cancer types,with most patients diagnosed at advanced stages that cannot be treated by radical surgery and which are accompanied by complications such as bodily pain and bone ***,attention should be given to the mental health status of PC patients as well as physical adverse events in the course of clinical *** To analyze the risk factors leading to anxiety and depression in PC patients after castration and build a risk prediction *** A retrospective analysis was performed on the data of 120 PC cases treated in Xi'an People's Hospital between January 2019 and January *** patient cohort was divided into a training group(n=84)and a validation group(n=36)at a ratio of 7:*** patients’anxiety symptoms and depression levels were assessed 2 wk after surgery with the Self-Rating Anxiety Scale(SAS)and the Selfrating Depression Scale(SDS),*** regression was used to analyze the risk factors affecting negative mood,and a risk prediction model was *** In the training group,35 patients and 37 patients had an SAS score and an SDS score greater than or equal to 50,*** on the scores,we further subclassified patients into two groups:a bad mood group(n=35)and an emotional stability group(n=49).Multivariate logistic regression analysis showed that marital status,castration scheme,and postoperative Visual Analogue Scale(VAS)score were independent risk factors affecting a patient's bad mood(Prisk scores than emotionally stable patients(Prisk prediction model for predicting bad mood in the training group was 0.743,the specificity was 70.96%,and the sensitivity was 66.03%,while in the validation

关键词： Prostate cancer Castration Anxiety and depression risk factors risk prediction model

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risk prediction model of Gallbladder Disease in Shanghai Middle-Aged and Elderly People Based on Neural Networks

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Journal of Shanghai Jiaotong university(Science) 2022年第2期27卷 153-159页

作者： Yuan Xiaoqi Zhu Lelan Xu Qiongfan Gao Wei Shanghai General Hospital Nanjing Medical UniversityNanjing211100China Shanghai General Hospital Shanghai Jiao Tong UniversityShanghai200080China School of Materials Science and Engineering Southeast UniversityNanjing211189China

This paper discusses the risk factors related to gallbladder disease in Shanghai,improves the accuracy of risk prediction,and provides a theoretical basis for scientific diagnosis and universality of gallbladder *** selected 3462 data of middle-aged and elderly health check-up patients in a general hospital in Shanghai,and divided into gallbladder disease group according to color doppler ultrasound diagnosis ***-factor analysis screened out 8 important risk factors,which were used as an analysis variable of multi-layer perceptron neural network and binary logistic regression to construct the prediction model of gallbladder *** prediction accuracy of the multi-layer perceptron neural network risk prediction model is 76%.The area under the receiver operating characteristic curve(AUC)is 0.82,the maximum Youden index is 0.44,the sensitivity is 79.51,and the specificity is *** prediction accuracy of the multi-layer perceptron neural network model is better than that of the binary logistic regression prediction *** overall prediction accuracy of the binary logistic regression prediction model is 75.60%,the AUC is 0.81,the maximum Youden index is 0.42,the sensitivity is 74.48,and the specificity is *** the objective risk prediction of gallbladder disease in middle-aged and elderly people in Shanghai,the risk prediction model based on the multi-layer perceptron neural network has a better prediction performance than the binary logistic regression model,which provides a theoretical basis for preventive treatment and intervention.

关键词： neural networks gallbladder disease risk prediction model

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Development and application of hepatocellular carcinoma risk prediction model based on clinical characteristics and liver related indexes

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World Journal of Gastrointestinal Oncology 2023年第8期15卷 1486-1496页

作者： Zhi-Jie Liu Yue Xu Wen-Xuan Wang Bin Guo Guo-Yuan Zhang Guang-Cheng Luo Qiang Wang Department of Clinical Transfusion Affiliated Hospital of North Sichuan Medical CollegeNanchong 637000Sichuan ProvinceChina Department of Clinical Laboratory Affiliated Hospital of North Sichuan Medical CollegeNanchong 637000Sichuan ProvinceChina Department of Radiology Nanchong Central HospitalNanchong 637000Sichuan ProvinceChina

BACKGROUND Hepatocellular carcinoma(HCC)is difficult to diagnose with poor therapeutic effect,high recurrence rate and has a low survival *** survival of patients with HCC is closely related to the stage of *** present,no specific serolo-gical indicator or method to predict HCC,early diagnosis of HCC remains a challenge,especially in China,where the situation is more *** To identify risk factors associated with HCC and establish a risk prediction model based on clinical characteristics and liver-related *** The clinical data of patients in the Affiliated Hospital of North Sichuan Medical College from 2016 to 2020 were collected,using a retrospective study *** results of needle biopsy or surgical pathology were used as the grouping criteria for the experimental group and the control group in this *** on the time of admission,the cases were divided into training cohort(n=1739)and validation cohort(n=467).Using HCC as a dependent variable,the research indicators were incorporated into logistic univariate and multivariate *** HCC risk prediction model,which was called NSMC-HCC model,was then established in training cohort and verified in validation *** Logistic univariate analysis showed that,gender,age,alpha-fetoprotein,and protein induced by vitamin K absence or antagonist-II,gamma-glutamyl transferase,aspartate aminotransferase and hepatitis B surface antigen were risk factors for HCC,alanine aminotransferase,total bilirubin and total bile acid were protective factors for *** the cut-off value of the NSMC-HCC model joint prediction was 0.22,the area under receiver operating characteristic curve(AUC)of NSMC-HCC model in HCC diagnosis was 0.960,with sensitivity 94.40%and specificity 95.35%in training cohort,and AUC was 0.966,with sensitivity 90.00%and specificity 94.20%in validation *** early-stage HCC diagnosis,the AUC of NSMC-HCC model was 0.946,with sensitivity 85.93%and specificity 93.

关键词： Hepatocellular carcinoma risk prediction model Logistic regression model Tumour markers Metabolic markers Clinical characteristics

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A Readmission risk prediction model for Elderly Patients with Coronary Heart Disease

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Journal of Clinical and Nursing Research 2022年第2期6卷 126-133页

作者： Yan-Ling Li Xiao-Hui Qi Yi-Lin Wang Jin Jiao Jing Li Jia Meng Yan Su Xiao-Jing Du Yan Wang Gui-Ping Sun Hui Wang Affiliated Hospital of Hebei University Baoding 071000Hebei ProvinceChina School of Basic Medicine of Shandong University Jinan 250012Shandong ProvinceChina Nursing School of Hebei University Baoding 071000Hebei ProvinceChina

Objective:To analyze the independent risk factors and establish a risk prediction model by investigating the readmission of elderly patients with coronary heart disease(CHD)within 1 year after ***:A total of 480 CHD patients,who were hospitalized in the Affiliated Hospital of Hebei University from October 2019 to December 2020,were included in this study.A general data scale,mental health status scale,the Clinical Frailty Scale,Pittsburgh Sleep Quality Index,as well as the Family Adaptability and Cohesion Evaluation Scale were used to collect *** to the number of readmissions due to CHD within 1 year after discharge,the patients were divided into two groups:the readmission group(n=212)and the no readmission group(n=268).General data,laboratory examination indicators,frailty,mental health status,sleep status,as well as family intimacy and adaptability were compared between the two *** regression was used to analyze the independent risk factors for the readmission of these patients,and R software was used to construct a line diagram model for predicting readmission of elderly patients with ***:Five factors including body mass index(OR=1.045),low density lipoprotein(OR=1.123),frailty(OR=1.946),mental health(OR=1.099),as well as family intimacy and adaptability(OR=0.928)were included to construct the risk prediction model for the readmission of elderly patients with CHD within 1 year after *** ROC curve showed that the area under the curve for predicting readmission of elderly patients with CHD was 0.816;Hosmer-Lemeshow goodness of fit test showed X2=1.456 and P=0.989;the maximum Youden index corresponding to the predicted value of risk was *** results showed that the model could accurately predict the risk of readmission in elderly patients with CHD within 1 year after ***:This study constructed a line diagram model based on five independent risk factors of the readmission of elderly patients

关键词： Elderly patients Coronary heart disease(CHD) Readmission risk prediction model

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Development and validation of a predictive model for acute-onchronic liver failure after transjugular intrahepatic portosystemic shunt

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World Journal of Gastrointestinal Surgery 2024年第5期16卷 1301-1310页

作者： Wei Zhang Ya-Ni Jin Chang Sun Xiao-Feng Zhang Rui-Qi Li Qin Yin Jin-Jun Chen Yu-Zheng Zhuge Department of Gastroenterology Nanjing Drum Tower HospitalThe Affiliated Hospital of Medical SchoolNanjing UniversityNanjing 210000Jiangsu ProvinceChina Hepatology Unit Department of Infectious DiseasesNanfang HospitalSouthern Medical UniversityGuangzhou 510000Guangdong ProvinceChina Co-first authors:Wei Zhang and Ya-Ni Jin

BACKGROUND Transjugular intrahepatic portosystemic shunt(TIPS)is a cause of acute-onchronic liver failure(ACLF).AIM To investigate the risk factors of ACLF within 1 year after TIPS in patients with cirrhosis and construct a prediction *** In total,379 patients with decompensated cirrhosis treated with TIPS at Nanjing Drum Tower Hospital from 2017 to 2020 were selected as the training cohort,and 123 patients from Nanfang Hospital were included in the external validation *** and multivariate logistic regression analyses were performed to identify independent *** prediction model was established based on the Akaike information *** and external validation were conducted to assess the performance of the *** Age and total bilirubin(TBil)were independent risk factors for the incidence of ACLF within 1 year after *** developed a prediction model comprising age,TBil,and serum sodium,which demonstrated good discrimination and calibration in both the training cohort and the external validation *** Age and TBil are independent risk factors for the incidence of ACLF within 1 year after TIPS in patients with decompensated *** model showed satisfying predictive value.

关键词： Acute-on-chronic liver failure Transjugular intrahepatic portosystemic shunt Influencing factor analysis risk prediction model Nomogram

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Nomogram prediction model called“ADPLCP”for predictinglinezolid-associated thrombocytopenia in elderly individuals

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Journal of Intensive Medicine 2023年第3期3卷 268-274页

作者： Yanxin Liu Jiang Wang Tingting Liu Kun Xiao Peng Yan Xiangqun Fang Lixin Xie Department of Pulmonary and Critical Care Medicine The Second Medical CenterNational Clinical Research Center for Geriatric DiseasesChinese PLA GeneralHospitalBeijing 100853China Centre of Pulmonary and Critical Care Medicine Chinese PLA General HospitalBeijing 100853China

Background:Linezolid-associated thrombocytopenia(LAT)leads to drug withdrawal associated with a poor *** risk factors for LAT have been identified;however,the sample size of previous studies was small,data from elderly individuals are limited,and a simple risk score scale was not established to predict LAT at anearly stage,making it difficult to identify and intervene in LAT at an early ***:In this single-center retrospective case-control study,we enrolled elderly patients treated with linezolidin the intensive care unit from January 2015 to December *** the data of enrolled patients,includingdemographic information and laboratory findings at baseline,were *** analyzed the incidence andrisk factors for LAT and established a nomogram risk prediction model for LAT in the elderly ***:A total of 428 elderly patients were enrolled,and the incidence of LAT was 35.5%(152/428).Age≥80 years old(OR=1.980;95%CI:1.179–3.325;P=0.010),duration of linezolid≥10 days(OR=1.100;95%CI:1.050–1.152;Pprediction model called“ADPLCP”(age,duration,platelet,leukocyte,creatinine clearance,protein)was established based on logistic *** area under the curve(AUC)of ADPLCP was 0.802(95%CI:0.748–0.856;Prisk stratification for LAT was performed based on“ADPLCP.”Total points ofrisk,and the possibility of LAT wasrisk,and the possibility of LAT was 32.0–67.5%.A total point>150 was defined

关键词： Linezolid-associated thrombocytopenia Nomogram risk prediction model Elderly individuals

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Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores:evidence from the China Kadoorie Biobank

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Chinese Medical Journal 2023年第20期136卷 2476-2483页

作者： Songchun Yang Dong Sun Zhijia Sun Canqing Yu Yu Guo Jiahui Si Dianjianyi Sun Yuanjie Pang Pei Pei Ling Yang Iona YMillwood Robin GWalters Yiping Chen Huaidong Du Zengchang Pang Dan Schmidt Rebecca Stevens Robert Clarke Junshi Chen Zhengming Chen Jun Lv Liming Li On Behalf of the China Kadoorie Biobank Collaborative Group Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijing 100191China Department of Dermatology Xiangya HospitalCentral South UniversityChangshaHunan 410008China Peking University Center for Public Health and Epidemic Preparedness&Response Beijing 100191China Fuwai Hospital Chinese Academy of Medical Sciences Beijing 100730China Medical Research Council Population Health Research Unit at the University of Oxford Oxford OX37LFUK Clinical Trial Service Unit and Epidemiological Studies Unit(CTSU) Nuffield Department of Population HealthUniversity of OxfordOxford OX37LFUK Qingdao Center of Disease Control and Prevention QingdaoShandong 266033China China National Center for Food Safety risk Assessment Beijing 100738China 不详

Background:Several studies have reported that polygenic risk scores(PRSs)can enhance risk prediction of coronary artery disease(CAD)in European ***,research on this topic is far from sufficient in non-European countries,including *** aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese ***:Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training(n=28,490)and testing sets(n=72,150).Ten previously developed PRSs were evaluated,and new ones were developed using clumping and thresholding or LDpred *** PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing *** risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide *** of the 10-year first CAD events was assessed using hazard ratios(HRs)and measures of model discrimination,calibration,and net reclassification improvement(NRI).Hard CAD(nonfatal I21-I23 and fatal I20-I25)and soft CAD(all fatal or nonfatal I20-I25)were analyzed ***:In the testing set,1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 *** HR per standard deviation of the optimal PRS was 1.26(95%CI:1.19-1.33)for hard *** on a traditional CAD risk prediction model containing only non-laboratory-based information,the addition of PRS for hard CAD increased Harrell’s C index by 0.001(-0.001 to 0.003)in women and 0.003(0.001 to 0.005)in *** the different high-risk thresholds ranging from 1%to 10%,the highest categorical NRI was 3.2%(95%CI:0.4-6.0%)at a high-risk threshold of 10.0%in *** association of the PRS with soft CAD was much weaker than with hard CAD,leading to minimal or no improvement in the soft CAD ***:In this Chinese population sam

关键词： Coronary artery disease Polygenic risk score risk prediction model Chinese population

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A male-ABCD algorithm for hepatocellular carcinoma risk prediction in HBs Ag carriers

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Chinese Journal of Cancer Research 2021年第3期33卷 352-363页

作者： Yuting Wang Minjie Wang He Li Kun Chen Hongmei Zeng Xinyu Bi Zheng Zhu Yuchen Jiao Yong Wang Jian Zhu Hui Zhao Xiang Liu Chunyun Dai Chunsun Fan Can Zhao Deyin Guo Hong Zhao Jianguo Zhou Dongmei Wang Zhiyuan Wu Xinming Zhao Wei Cui Xuehong Zhang Jianqiang Cai Wanqing Chen Chunfeng Qu State Key Lab of Molecular Oncology National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of Clinical Laboratory National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Office of Cancer Screening National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China National Central Cancer Registry National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of Hepatobiliary Surgery National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of Diagnostic Radiology National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of Ultrasonography National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Qidong Liver Cancer Institute&Qidong People’s Hospital Qidong 226200China Lingbi Center for Disease Control and Prevention Suzhou 234200China Mengcheng Center for Disease Control and Prevention Bozhou 233500China Sheyang Center for Disease Control and Prevention Yancheng 224300China Shenqiu County Center for Disease Control and Prevention Zhoukou 411624China Dancheng Center for Disease Control and Prevention Zhoukou 477150China Channing Division of Network Medicine Department of MedicineBrigham and Womens Hospital and Harvard Medical SchoolBostonMA 02115USA Department of Nutrition T

Objective: Hepatocellular carcinoma(HCC) development among hepatitis B surface antigen(HBs Ag) carriers shows gender disparity, influenced by underlying liver diseases that display variations in laboratory tests. We aimed to construct a risk-stratified HCC prediction model for HBs Ag-positive male ***: HBs Ag-positive males of 35-69 years old(N=6,153) were included from a multi-center populationbased liver cancer screening study. Randomly, three centers were set as training, the other three centers as validation. Within 2 years since initiation, we administrated at least two rounds of HCC screening using Bultrasonography and α-fetoprotein(AFP). We used logistic regression models to determine potential risk factors,built and examined the operating characteristics of a point-based algorithm for HCC risk ***: With 2 years of follow-up, 302 HCC cases were diagnosed. A male-ABCD algorithm was constructed including participant's age, blood levels of GGT(γ-glutamyl-transpeptidase), counts of platelets, white cells,concentration of DCP(des-γ-carboxy-prothrombin) and AFP, with scores ranging from 0 to 18.3. The area under receiver operating characteristic was 0.91(0.90-0.93), larger than existing models. At 1.5 points of risk score,26.10% of the participants in training cohort and 14.94% in validation cohort were recognized at low risk, with sensitivity of identifying HCC remained 100%. At 2.5 points, 46.51% of the participants in training cohort and 33.68% in validation cohort were recognized at low risk with 99.06% and 97.78% of sensitivity, respectively. At 4.5 points, only 20.86% of participants in training cohort and 23.73% in validation cohort were recognized at high risk,with positive prediction value of 22.85% and 12.35%, ***: Male-ABCD algorithm identified individual's risk for HCC occurrence within short term for their HCC precision surveillance.

关键词： Hepatocellular carcinoma asymptotic HBs Ag carriers risk prediction model screening laboratory tests

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Predicting lymph node metastasis in colorectal cancer:An analysis of influencing factors to develop a risk model

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World Journal of Gastrointestinal Surgery 2023年第10期15卷 2234-2246页

作者： Yun-Peng Lei Qing-Zhi Song Shuang Liu Ji-Yan Xie Guo-Qing Lv Department of Gastrointestinal Surgery Peking University Shenzhen HospitalShenzhen 518036Guangdong ProvinceChina Department of Gastrointestinal Surgery Shenzhen Peking University-The Hong Kong University of Science and Technology Medical CenterPeking University Shenzhen HospitalShenzhen 518036Guangdong ProvinceChina

BACKGROUND Colorectal cancer(CRC)is a significant global health issue,and lymph node metastasis(LNM)is a crucial prognostic *** prediction of LNM is essential for developing individualized treatment strategies for patients with ***,the prediction of LNM is challenging and depends on various factors such as tumor histology,clinicopathological features,and molecular *** most reliable method to detect LNM is the histopathological examination of surgically resected specimens;however,this method is invasive,time-consuming,and subject to sampling errors and interobserver *** To analyze influencing factors and develop and validate a risk prediction model for LNM in CRC based on a large patient *** This study retrospectively analyzed 300 patients who underwent CRC surgery at two Peking University Shenzhen hospitals between January and December 2021.A deep learning approach was used to extract features potentially associated with LNM from primary tumor histological images while a logistic regression model was employed to predict LNM in CRC using machine-learning-derived features and clinicopathological variables as *** The prediction model constructed for LNM in CRC was based on a logistic regression framework that incorporated machine learning-extracted features and clinicopathological *** model achieved high accuracy(0.86),sensitivity(0.81),specificity(0.87),positive predictive value(0.66),negative predictive value(0.94),area under the curve for the receiver operating characteristic(0.91),and a low Brier score(0.10).The model showed good agreement between the observed and predicted probabilities of LNM across a range of risk thresholds,indicating good calibration and clinical *** The present study successfully developed and validated a potent and effective risk-prediction model for LNM in patients with *** model utilizes machine-learning-derived features extracted from pr

关键词： Colorectal cancer Lymph node metastasis Machine learning risk prediction model Clinicopathological factors Individualized treatment strategies

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risk factors of concurrent urinary sepsis in patients with diabetes mellitus comorbid with upper urinary tract calculi

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世界糖尿病杂志:英文版(电子版) 2023年第9期14卷 1403-1411页

作者： Jian-Jie Gou Chao Zhang Hai-Song Han Hong-Wei Wu Department of Urology Surgery People’s Hospital of JinchengJincheng 048000Shanxi ProvinceChina Emergency Department People’s Hospital of JinchengJincheng 048000Shanxi ProvinceChina

BACKGROUND Urinary sepsis is frequently seen in patients with diabetes mellitus(DM)complicated with upper urinary tract calculi(UUTCs).Currently,the known risk factors of urinary sepsis are not *** To analyze the risk factors of concurrent urinary sepsis in patients with DM complicated with UUTCs by logistic *** We retrospectively analyzed 384 patients with DM complicated with UUTCs treated in People’s Hospital of Jincheng between February 2018 and May *** patients were screened according to the inclusion and exclusion criteria,and 204 patients were *** patients were assigned to an occurrence group(n=78)and a nonoccurrence group(n=126).Logistic regression was adopted to analyze the risk factors for urinary sepsis,and a risk prediction model was *** Gender,age,history of lumbago and abdominal pain,operation time,urine leukocytes(U-LEU)and urine glucose(U-GLU)were independent risk factors for patients with concurrent urinary sepsis(Prisk score=0.794×gender+0.941×age+0.901×history of lumbago and abdominal pain-1.071×operation time+1.972×U-LEU+1.541×*** occurrence group had notably higher risk scores than the nonoccurrence group(Prisk score for forecasting concurrent urinary sepsis in patients was 0.801,with specificity of 73.07%,sensitivity of 79.36%and Youden index of 52.44%.CONCLUSION Sex,age,history of lumbar and abdominal pain,operation time,ULEU and UGLU are independent risk factors for urogenic sepsis in diabetic patients with UUTC.

关键词： Diabetes mellitus Upper urinary tract calculi Urinary sepsis risk factors risk prediction model Logistic regression Concurrent urinary sepsis

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