1.Risk factors analysis of portal vein thrombosis in liver cirrhosis and establishment of a prediction model
Qingqing YAO ; Wen SHI ; Miaojia YAN ; Hongxia LI
Journal of Xi'an Jiaotong University(Medical Sciences) 2025;46(2):310-316
Objective To explore the risk factors for portal vein thrombosis(PVT)in patients with cirrhosis in the decompensated stage and construct a risk prediction model for PVT so as to improve the early diagnosis rate of decompensated liver cirrhosis PVT.Methods The clinical data of patients with cirrhosis in the decompensated stage admitted to Department of Gastroenterology,The First Affiliated Hospital of Xi'an Jiaotong University between June 2018 and June 2023 were collected and divided into cirrhosis PVT group(n=135)and cirrhosis non-PVT group(n=225)according to whether or not portal vein thrombosis was formed.We made a univariate analysis of the general data,laboratory indexes,liver function scores and imaging findings of the patients in the two groups,and indexes with statistically significant differences were included in binary Logistic regression for multifactorial analysis to screen out independent risk factors.A predictive model of binary Logistic regression was established based on the independent risk factors.The clinical data of the validation set were incorporated into the model,the accuracy of the prediction model was evaluated by receiver operating curve(ROC),and the practicability of the model was evaluated by consistency curve to complete the validation and evaluation of the constructed prediction model.Internal stability of the model was verified with Bootstrap method.Finally,R software(4.3.1)was used to draw a nomogram of the prediction model to visualize the model.Results Univariate analysis revealed statistically significant differences between patients in the PVT and non-PVT groups in the following five aspects:history of splenectomy,history of endoscopic varicose vein treatment,portal vein diameter,and neutrophil-to-lymphocyte ratio(P<0.05).Binary Logistics regression analysis showed that a history of splenectomy(P=0.002,OR=3.012,95%CI:1.500-6.047),a history of endoscopic varicose vein treatment(P=0.001,OR=2.276,95%CI:1.400-3.698),widening of portal vein diameter(P=0.007,OR=1.942,95%CI:1.202-3.136),increased neutrophil-to-lymphocyte ratio(P=0.009,OR=1.886,95%CI:1.170-3.041),and elevated D-dimer(P<0.001,OR=3.725,95%CI:2.149-6.485)were independent risk factors for the formation of portal vein thrombosis in patients with cirrhosis in the decompensated stage of cirrhosis chemically presented(P<0.05).The area under the ROC curve of the predictive model and the model after internal validation was 0.760 and 0.7494,respectively.The model still had good prediction ability and accuracy in the verification set.Conclusion A history of splenectomy,history of endoscopic varicose vein treatment,widening of portal vein diameter,increased neutrophil-to-lymphocyte ratio,and elevated D-dimer concentration are independent risk factors for the formation of portal vein thrombosis in patients with decompensated cirrhosis.The Logistic prediction model and visual nomogram constructed based on the above independent risk factors have a good ability to predict the occurrence of PVT in patients with decompensated cirrhosis and have important clinical guiding significance for early screening patients with PVT in decompensated cirrhosis.
2.Risk factors analysis of portal vein thrombosis in liver cirrhosis and establishment of a prediction model
Qingqing YAO ; Wen SHI ; Miaojia YAN ; Hongxia LI
Journal of Xi'an Jiaotong University(Medical Sciences) 2025;46(2):310-316
Objective To explore the risk factors for portal vein thrombosis(PVT)in patients with cirrhosis in the decompensated stage and construct a risk prediction model for PVT so as to improve the early diagnosis rate of decompensated liver cirrhosis PVT.Methods The clinical data of patients with cirrhosis in the decompensated stage admitted to Department of Gastroenterology,The First Affiliated Hospital of Xi'an Jiaotong University between June 2018 and June 2023 were collected and divided into cirrhosis PVT group(n=135)and cirrhosis non-PVT group(n=225)according to whether or not portal vein thrombosis was formed.We made a univariate analysis of the general data,laboratory indexes,liver function scores and imaging findings of the patients in the two groups,and indexes with statistically significant differences were included in binary Logistic regression for multifactorial analysis to screen out independent risk factors.A predictive model of binary Logistic regression was established based on the independent risk factors.The clinical data of the validation set were incorporated into the model,the accuracy of the prediction model was evaluated by receiver operating curve(ROC),and the practicability of the model was evaluated by consistency curve to complete the validation and evaluation of the constructed prediction model.Internal stability of the model was verified with Bootstrap method.Finally,R software(4.3.1)was used to draw a nomogram of the prediction model to visualize the model.Results Univariate analysis revealed statistically significant differences between patients in the PVT and non-PVT groups in the following five aspects:history of splenectomy,history of endoscopic varicose vein treatment,portal vein diameter,and neutrophil-to-lymphocyte ratio(P<0.05).Binary Logistics regression analysis showed that a history of splenectomy(P=0.002,OR=3.012,95%CI:1.500-6.047),a history of endoscopic varicose vein treatment(P=0.001,OR=2.276,95%CI:1.400-3.698),widening of portal vein diameter(P=0.007,OR=1.942,95%CI:1.202-3.136),increased neutrophil-to-lymphocyte ratio(P=0.009,OR=1.886,95%CI:1.170-3.041),and elevated D-dimer(P<0.001,OR=3.725,95%CI:2.149-6.485)were independent risk factors for the formation of portal vein thrombosis in patients with cirrhosis in the decompensated stage of cirrhosis chemically presented(P<0.05).The area under the ROC curve of the predictive model and the model after internal validation was 0.760 and 0.7494,respectively.The model still had good prediction ability and accuracy in the verification set.Conclusion A history of splenectomy,history of endoscopic varicose vein treatment,widening of portal vein diameter,increased neutrophil-to-lymphocyte ratio,and elevated D-dimer concentration are independent risk factors for the formation of portal vein thrombosis in patients with decompensated cirrhosis.The Logistic prediction model and visual nomogram constructed based on the above independent risk factors have a good ability to predict the occurrence of PVT in patients with decompensated cirrhosis and have important clinical guiding significance for early screening patients with PVT in decompensated cirrhosis.
3.Recommendations for the diagnosis and treatment of rheumatic diseases-related hemophagocytic syndrome in China
Qian WANG ; Yini WANG ; Qiang WANG ; Miaojia ZHANG ; Hongsheng SUN ; Chongyang LIU ; Zhao WANG ; Yan ZHAO
Chinese Journal of Internal Medicine 2023;62(1):23-30
Hemophagocytic syndrome (HPS), which is currently named as hemophagocytic lymphohistiocytosis (HLH), is a hyperinflammatory syndrome characterized by persistent fever, hepatosplenomegaly, pancytopenia and hemophagocytosis found in bone marrow, liver, spleen and lymph nodes due to excessive activation of macrophages and cytotoxic T cells. Macrophage activation syndrome (MAS) is a specific form of HLH induced by autoinflammatory/autoimmune disorders which can be life-threatening and requires multiple disciplines. In order to improve clinicians′ understanding of MAS and standardize the clinical diagnosis and treatment practice of MAS, the rheumatology branch of Chinese Rheumatology Association organized domestic experts to formulate the diagnosis and treatment standard, in order to improve the diagnosis and treatment level of MAS and improve the prognosis of patients.
4.Method of double data entry and quality control by REDCap system
Miaojia YAN ; Peng ZHAO ; Lichen WU ; Kun XU ; Hong YAN ; Lingxia ZENG ; Baibing MI ; Shaonong DANG
Chinese Journal of Epidemiology 2021;42(5):918-922
In medical research, the quality of data is the key to success. Thus, data quality control becomes an important part of ensuring the research's high quality. REDCap system is an emerging data acquisition system in medical research, which is gradually applied in research at home and abroad. It is a hot issue to realize double data entry and data quality control in using the REDCap system, which researchers are concerned about when this system is supposed to apply. This article will systematically introduce how to use the REDCap system for double data entry and quality control from the aspects of research project creation, data collection tool design, double data entry, data checking and exporting.

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