1.Establishment and validation of a model for femoral head necrosis after internal fixation of femoral neck fracture using logistic regression and SHAP analysis
Long LIAO ; Zepeng ZHAO ; Zongyuan LI ; Qinglong YU ; Tao ZHANG ; Jinyuan TANG ; Nan YE ; Han XU ; Bo SHI
Chinese Journal of Tissue Engineering Research 2026;30(3):626-633
BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95%Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2%and a specificity of 87.6%,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1%to 92%,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.
2.Establishment and validation of a model for femoral head necrosis after internal fixation of femoral neck fracture using logistic regression and SHAP analysis
Long LIAO ; Zepeng ZHAO ; Zongyuan LI ; Qinglong YU ; Tao ZHANG ; Jinyuan TANG ; Nan YE ; Han XU ; Bo SHI
Chinese Journal of Tissue Engineering Research 2026;30(3):626-633
BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95%Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2%and a specificity of 87.6%,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1%to 92%,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.
3.Predictive model for severe adverse reaction associated with bevacizumab based on the global trigger tool and machine learning
Yongfei FU ; Xin LONG ; Hongzhen XU ; Jian TANG ; Xiangqing LI ; Yucheng LONG ; Dong QIN
China Pharmacy 2026;37(4):497-503
OBJECTIVE To confirm trigger items for adverse drug reaction (ADR) induced by bevacizumab, to identify and analyze the occurrence of related ADR, and to establish a predictive model for severe adverse reaction (SAR) caused by this drug. METHODS Based on the global trigger tool (GTT) theory, and referencing the GTT White Paper, drug package inserts and relevant literature, trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items, electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects (divided into training and test sets at a ratio of 7∶3), candidate feature variables were selected from 39 related variables using the Boruta algorithm, and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features, Logistic Regression, Extreme Gradient Boosting, Light Gradient Boosting Machine, Random Forest, and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve (AUC) of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations (SHAP) method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined, comprising 17 laboratory indicators, 13 clinical manifestations, and 8 intervention measures. In total, 483 patients with positive trigger items were included, and 318 patients with bevacizumab-induced ADR were identified, including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% (708/1 625) and 63.84% (318/483), respectively. Bevacizumab-induced ADR involved 7 systems/organs, with the hematological system being the most frequently involved (64.15%). The Boruta algorithm selected 7 vari ables: serum potassium, hematocrit, albumin-to-globulin ratio, prealbumin, hypertension history, age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR (OR=0.234, P =0.002), while a history of hypertension (OR=2.642, P =0.006) and increased age (OR=1.040, P =0.025) were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC, F1 score and recall rate (0.761, 0.447, 0.607), compared to other models. SHAP evaluation results indicated that variables such as serum potassium, hematocrit, and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR, whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.
4.Erjingwan Alleviate Inflammatory Response and Apoptosis in Skeletal Muscle Cells of Sarcopenia via SIRT1/Nrf2/HO-1 Signaling Pathway
Long SHI ; Yang LI ; Hongyu YAN ; Tianle ZHOU ; Zhiwen ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):57-66
ObjectiveTo investigate the effects of the classical Chinese medicine compound prescription Erjingwan on the inflammatory response and apoptosis of skeletal muscle cells in a mouse model of sarcopenia and decipher the mechanism based on the silent information regulator 1 (SIRT1)/nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) signaling pathway. MethodsForty C57/BL6 male mice were randomized into a control group, a model group, and groups with different doses of Erjingwan (8,16,32 g·kg-1). The mouse model of sarcopenia was established by D-gal-induced skeletal muscle senescence. The body weight and grip strength of mice treated with different doses of Erjingwan were examined to evaluate their physiological functions. Hematoxylin-eosin (HE) staining and Masson staining were used to observe the pathological changes and fibrosis in the skeletal muscle of mice. Enzyme-linked immunosorbent assay (ELISA) was adopted to determine the levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in the serum samples of mice, and biochemical tests were conducted to quantify the levels of superoxide dismutase (SOD), malondialdehyde (MDA), and glutathione (GSH) in the serum. The protein and mRNA levels of SIRT1, Nrf2, B-cell lymphoma (Bcl-2), and Bcl-2-associated X protein (Bax) were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR), respectively. ResultsAfter 4 weeks of drug intervention, the model group exhibited significant reductions in body weight and grip strength (P0.01) compared with the control group. Compared with the model group, all doses of Erjingwan increased the body weight in mice at week 8 (P0.01) and grip strength from week 6 (P0.01). HE staining revealed clear muscle fiber structure in the control group, muscle fiber rupture and atrophy in the model group, and dose-dependent repair of muscle fiber structure in the Erjingwan groups. Masson staining showed minimal collagen fibers and mild fibrosis in the control group, collagen fiber proliferation and severe fibrosis in the model group, and collagen proliferation with dose-dependent inhibition of fibrosis in the Erjingwan groups. ELISA results showed that serum levels of TNF-α and IL-6 were elevated in the model group compared with those in the control group (P0.01). After intervention, the low-dose Erjingwan group exhibited a decreased TNF-α level (P0.05), while the medium and high-dose groups showed decreases in both TNF-α and IL-6 levels (P0.01). Biochemical assays revealed that the model group had decreased SOD and GSH levels (P0.01) and an increased MDA level (P0.01) compared with the control group. The medium and high-dose Erjingwan groups exhibited increases in SOD and GSH levels (P0.01) and decreases in MDA level (P0.01), compared with the model group. WB and Real-time PCR results showed that compared with the control group, the model group presented down-regulated protein and mRNA levels of SIRT1, Nrf2, HO-1, and Bcl-2 in the muscle tissue (P0.01) and up-regulated protein and mRNA levels of Bax (P0.01). Compared with the model group, Erjingwan at different doses up-regulated the protein levels of SIRT1, Nrf2, HO-1, and Bcl-2 (P0.01) and down-regulated the protein and mRNA levels of Bax (P0.01) in the muscle tissue. Low-dose Erjingwan elevated the mRNA levels of Nrf2 and HO-1 (P0.05, P0.01), and medium and high-dose Erjingwan up-regulated the mRNA levels of SIRT1, Nrf2, HO-1, and Bcl-2 (P0.01). ConclusionErjingwan reduced the content of inflammatory factors in skeletal muscle cells, improved the antioxidant capacity, and attenuated pathological changes and fibrosis in the muscle of the mouse model of sarcopenia by regulating the SIRT1/Nrf2/HO-1 pathway, inflammatory response, and apoptosis network.
5.Yimei Baijiang Formula Treats Colitis-associated Colorectal Cancer in Mice via NF-κB Signaling Pathway
Qian WU ; Xin ZOU ; Chaoli JIANG ; Long ZHAO ; Hui CHEN ; Li LI ; Zhi LI ; Jianqin LIU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):119-130
ObjectiveTo explore the effects of Yimei Baijiang formula (YMBJF) on colitis-associated colorectal cancer (CAC) and the nuclear factor kappaB (NF-κB) signaling pathway in mice. MethodsSixty male Balb/c mice of 4-6 weeks old were randomized into 6 groups: Normal, model, capecitabine (0.83 g
6.Erjingwan Alleviate Inflammatory Response and Apoptosis in Skeletal Muscle Cells of Sarcopenia via SIRT1/Nrf2/HO-1 Signaling Pathway
Long SHI ; Yang LI ; Hongyu YAN ; Tianle ZHOU ; Zhiwen ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):57-66
ObjectiveTo investigate the effects of the classical Chinese medicine compound prescription Erjingwan on the inflammatory response and apoptosis of skeletal muscle cells in a mouse model of sarcopenia and decipher the mechanism based on the silent information regulator 1 (SIRT1)/nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) signaling pathway. MethodsForty C57/BL6 male mice were randomized into a control group, a model group, and groups with different doses of Erjingwan (8,16,32 g·kg-1). The mouse model of sarcopenia was established by D-gal-induced skeletal muscle senescence. The body weight and grip strength of mice treated with different doses of Erjingwan were examined to evaluate their physiological functions. Hematoxylin-eosin (HE) staining and Masson staining were used to observe the pathological changes and fibrosis in the skeletal muscle of mice. Enzyme-linked immunosorbent assay (ELISA) was adopted to determine the levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in the serum samples of mice, and biochemical tests were conducted to quantify the levels of superoxide dismutase (SOD), malondialdehyde (MDA), and glutathione (GSH) in the serum. The protein and mRNA levels of SIRT1, Nrf2, B-cell lymphoma (Bcl-2), and Bcl-2-associated X protein (Bax) were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR), respectively. ResultsAfter 4 weeks of drug intervention, the model group exhibited significant reductions in body weight and grip strength (P0.01) compared with the control group. Compared with the model group, all doses of Erjingwan increased the body weight in mice at week 8 (P0.01) and grip strength from week 6 (P0.01). HE staining revealed clear muscle fiber structure in the control group, muscle fiber rupture and atrophy in the model group, and dose-dependent repair of muscle fiber structure in the Erjingwan groups. Masson staining showed minimal collagen fibers and mild fibrosis in the control group, collagen fiber proliferation and severe fibrosis in the model group, and collagen proliferation with dose-dependent inhibition of fibrosis in the Erjingwan groups. ELISA results showed that serum levels of TNF-α and IL-6 were elevated in the model group compared with those in the control group (P0.01). After intervention, the low-dose Erjingwan group exhibited a decreased TNF-α level (P0.05), while the medium and high-dose groups showed decreases in both TNF-α and IL-6 levels (P0.01). Biochemical assays revealed that the model group had decreased SOD and GSH levels (P0.01) and an increased MDA level (P0.01) compared with the control group. The medium and high-dose Erjingwan groups exhibited increases in SOD and GSH levels (P0.01) and decreases in MDA level (P0.01), compared with the model group. WB and Real-time PCR results showed that compared with the control group, the model group presented down-regulated protein and mRNA levels of SIRT1, Nrf2, HO-1, and Bcl-2 in the muscle tissue (P0.01) and up-regulated protein and mRNA levels of Bax (P0.01). Compared with the model group, Erjingwan at different doses up-regulated the protein levels of SIRT1, Nrf2, HO-1, and Bcl-2 (P0.01) and down-regulated the protein and mRNA levels of Bax (P0.01) in the muscle tissue. Low-dose Erjingwan elevated the mRNA levels of Nrf2 and HO-1 (P0.05, P0.01), and medium and high-dose Erjingwan up-regulated the mRNA levels of SIRT1, Nrf2, HO-1, and Bcl-2 (P0.01). ConclusionErjingwan reduced the content of inflammatory factors in skeletal muscle cells, improved the antioxidant capacity, and attenuated pathological changes and fibrosis in the muscle of the mouse model of sarcopenia by regulating the SIRT1/Nrf2/HO-1 pathway, inflammatory response, and apoptosis network.
7.Yimei Baijiang Formula Treats Colitis-associated Colorectal Cancer in Mice via NF-κB Signaling Pathway
Qian WU ; Xin ZOU ; Chaoli JIANG ; Long ZHAO ; Hui CHEN ; Li LI ; Zhi LI ; Jianqin LIU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):119-130
ObjectiveTo explore the effects of Yimei Baijiang formula (YMBJF) on colitis-associated colorectal cancer (CAC) and the nuclear factor kappaB (NF-κB) signaling pathway in mice. MethodsSixty male Balb/c mice of 4-6 weeks old were randomized into 6 groups: Normal, model, capecitabine (0.83 g
8.Key scientific issues and breakthrough paths to eliminate the harm of hepatitis B virus infection
Yixue WANG ; Bo PENG ; Lei WEI ; Quanxin LONG ; Yuchen XIA ; Yinyan SUN ; Wenhui LI
Journal of Clinical Hepatology 2026;42(1):2-6
Hepatitis B virus (HBV) exclusively infects liver parenchymal cells and forms covalently closed circular DNA (cccDNA) within their nuclei. HBV cccDNA serves as the essential template for viral gene transcription, the sole source of progeny virus production, and the key driver of viral antigen expression, and it is the molecular basis for the persistence of HBV infection. Therefore, elimination and/or functional silencing of cccDNA is the key to eradicate chronic HBV infection. This article discusses the critical scientific issues that need to be solved during elimination of the harm of HBV infection from the perspectives of the synthesis, transcription, and clearance of cccDNA, as well as the impact of nonparenchymal cells on cccDNA, in order to provide a reference for eradicating HBV infection in the future.
9.Predictive modle for violence risk in hospitalized schizophrenia patients based on support vector machine
Huan LIU ; Peifang SHI ; Kun ZHANG ; Li KANG ; Yan ZHANG ; Long NA ; Binhong WANG ; Meiqing HE
Sichuan Mental Health 2026;39(1):27-35
BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness, unpredictability, high severity, and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia, to identify the key factors influencing the occurrence of violent behavior in these patients, so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases, eleventh edition (ICD-11) were collected to form the modeling cohort. They were randomly divided into a training set (n=140) and a test set (n=60) at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator (LASSO) regression algorithm, the feature variables were screened and dimension-reduced. The support vector machine (SVM) from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, precision, sensitivity, specificity, F1 value, and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores (r=0.580, P<0.01), a positive correlation between hospitalization compliance and current disease status (r=0.550, P=0.003), and a positive correlation between educational level and family per capita monthly income (r=0.367, P<0.01). The SVM model achieved an AUC of 0.853, accuracy of 0.800, precision of 0.810, sensitivity of 0.895, specificity of 0.636, F1 value of 0.850, and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients, which is helpful for the early identification of violent risks in such patients. [Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City (number, Y2023006)]
10.Quality evaluation of Marsdenia tenacissimae from different producing areas based on multi-component quantitative combined with chemometrics
Yue LONG ; Yang HU ; Ling HE ; Lichao ZHU ; Li SHAO
Journal of China Pharmaceutical University 2026;57(1):46-53
A quantitative method for the analysis of the multi-component contents in Marsdenia tenacissimae was established, and the quality differences were evaluated by principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), factor analysis (FA) and weighted technique for order preference by similarity to ideal solution (TOPSIS) method. The contents of chlorogenic acid, cryptochlorogenic acid, sinapic acid, tenacigenoside A, tenacissoside G, tenacissoside I, tenacissoside H, drevogenin A, betulinic acid and lupeol were determined by HPLC wavelength switching method. At the same time, the contents of alcohol-soluble extract and total ash were detected. PCA, OPLS-DA and FA methods were used to identify the origin of M. tenacissimae from different producing areas. According to the OPLS-DA model, the index weight was determined to construct the weighted TOPSIS evaluation model. The qualities of M. tenacissimae from different producing areas were analyzed by model scoring results. The contents of 12 indexes in 18 batches of M. tenacissimae varied to different degrees, and the repeatability and accuracy of the test method were satisfactory. PCA analysis divided 18 batches of M. tenacissimae into three categories. OPLS-DA identified five main potential quality markers, including tenacissoside A, tenacissoside I, lupeol, tenacissoside H and chlorogenic acid. The evaluation results of FA and weighted TOPSIS method were consistent, which showed that the quality of M. tenacissimae from Yunnan and Guizhou was better. The established multi-component quantitative analysis method is accurate and reliable, the chemometrics model has strong predictive ability, and the evaluation results of FA and weighted TOPSIS method are scientific and objective. The combination of the four methods can clearly determine the qualities of M. tenacissimae from different producing areas.

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