Objective:To explore the correlation between serum nidogen-2 (NID-2) and thoracic aortic calcification in patients with chronic kidney disease (CKD), and construct a risk prediction model based on NID-2 to evaluate its value in predicting the risk of the severe thoracic aortic calcification and cardiovascular and cerebrovascular events in CKD patients.Methods:It was a prospective cohort study. Patients with CKD at stage 3 to 5D in the Zhongda Hospital Affiliated to Southeast University from January 2022 to January 2023 were enrolled. Syngo.via software was used to evaluate the volume of thoracic aortic calcification, and enzyme-linked immunosorbent assay was employed to determine the level of serum NID-2. According to the volume of thoracic aortic calcification, the patients were divided into three groups: no calcification group, mild calcification group and severe calcification group. The top 25% of the patients were defined as no or mild calcification group, and the latter 75% were defined as severe calcification group. The follow-up period was one year. During the follow-up period, cardiovascular and cerebrovascular events, as well as all-cause death among the enrolled patients were recorded. Logistic regression analysis was used to screen the influencing factors of thoracic aortic calcification. Based on the results of logistic regression analysis, a nomogram prediction model was constructed. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve were employed to evaluate the discrimination, calibration and clinical practicality of the nomogram model.Results:A total of 132 patients were included, with 91 males (68.94%) and age of (56.51±16.37) years. There were 60 CKD 3-5 stage patients (non-dialysis, 45.45%) and 72 CKD 5D patients (dialysis, 54.55%). Serum ND-2 levels differed significantly among healthy individuals, dialysis patients and non-dialysis patients ( H=70.651, P<0.001). There was no statistically significant difference in serum NID-2 level between the no or mild calcification group and the severe calcification group in dialysis patients ( Z=350.00, P=0.426). The serum NID-2 level in the severe calcification group was significantly higher than that in the no or mild calcification group in non-dialysis patients ( Z=242.00, P=0.019). In non-dialysis patients, there was a statistically significant correlation between serum NID-2 level and volume of thoracic aortic calcification ( r=0.40, P<0.001). In dialysis patients, there was no statistically significant correlation between serum NID-2 level and volume of each segment of thoracic aortic calcification (all P>0.05). The univariate logistic regression analysis showed that, age, hemoglobin, serum albumin, estimated glomerular filtration rate, NID-2, hypertension, type 2 diabetes mellitus and cerebral infarction were correlated factors of thoracic aortic calcification in non-dialysis patients (all P<0.05). Multivariate logistic regression analysis showed that age ( OR=1.22, 95% CI 1.08-1.50, P=0.010) was an independent correlated factor of thoracic aortic calcification in non-dialysis patients. The above related variables of univariate logistic regression analysis were incorporated into a nomogram to construct a predictive model for severe vascular calcification in non-dialysis patients, yielding an AUC of 0.94 (95% CI 0.89-0.99) in ROC curve, with a sensitivity of 83% and a specificity of 95%. A nomogram model based on above variables for predicting cardiovascular and cerebrovascular events in non-dialysis patients demonstrated an AUC of 0.95 (95% CI 0.90-1.00) in ROC curve, with a sensitivity of 95% and a specificity of 87%. Conclusions:In non-dialysis patients, serum NID-2 level in the severe calcification group is significantly higher than that in the no or mild calcification group. The serum NID-2 is a related factor of thoracic aortic calcification and cardiovascular and cerebrovascular events in non-dialysis patients. The nomogram prediction model constructed by combining NID-2 with age, hemoglobin, serum albumin, estimated glomerular filtration rate, hypertension, type 2 diabetes mellitus and cerebral infarction has a high predictive value for the risk of thoracic aortic calcification as well as cardiovascular and cerebrovascular events in non-dialysis patients.

BACKGROUND: Renal osteodystrophy (ROD) is a skeletal pathology associated with chronic kidney disease-mineral and bone disorder (CKD-MBD) that is characterized by aberrant bone mineralization and remodeling. ROD increases the risk of fracture and mortality in CKD patients. The underlying mechanisms of ROD remain elusive, partially due to the absence of an appropriate animal model. To address this gap, we established a stable mouse model of ROD using an optimized adenine-enriched diet and conducted exploratory analyses through ribonucleic acid sequencing (RNA-seq). METHODS: Eight-week-old male C57BL/6J mice were randomly allocated into three groups: control group ( n = 5), adenine and high-phosphate (HP) diet group ( n = 20), and the optimized adenine-containing diet group ( n = 20) for 12 weeks. We assessed the skeletal characteristics of model mice through blood biochemistry, microcomputed tomography (micro-CT), and bone histomorphometry. RNA-seq was utilized to profile gene expression changes of ROD. We elucidated the functions of differentially expressed genes (DEGs) using gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA). DEGs were validated via quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: By the fifth week, adenine followed by an HP diet induced rapid weight loss and high mortality rates in the mouse group, precluding further model development. Mice with optimized adenine diet-induced ROD displayed significant abnormalities in serum creatinine and blood urea nitrogen levels, accompanied by pronounced hyperparathyroidism and hyperphosphatemia. The femur bone mineral density (BMD) of the model mice was lower than that of control mice, with substantial bone loss and cortical porosity. ROD mice exhibited substantial bone turnover with an increase in osteoblast and osteoclast markers. Transcriptomic profiling revealed 1907 genes with upregulated expression and 723 genes with downregulated expression in the femurs of ROD mice relative to those of control mice. Pathway analyses indicated significant enrichment of upregulated genes in the sphingolipid metabolism pathway. The significant upregulation of alkaline ceramidase 1 ( Acer1 ), alkaline ceramidase 2 ( Acer2 ), prosaposin-like 1 ( Psapl1 ), adenosine A1 receptor ( Adora1 ), and sphingosine-1-phosphate receptor 5 ( S1pr5 ) were successfully validated in mouse femurs by qRT-PCR. CONCLUSIONS Optimized adenine diet mouse model may be a valuable proxy for studying ROD. RNA-seq analysis revealed that the sphingolipid metabolism pathway is likely a key player in ROD pathogenesis, thereby providing new avenues for therapeutic intervention.
Animals ; Mice ; Chronic Kidney Disease-Mineral and Bone Disorder/genetics* ; Male ; Disease Models, Animal ; Mice, Inbred C57BL ; Sphingolipids/metabolism* ; Transcriptome/genetics* ; Signal Transduction/genetics* ; X-Ray Microtomography ; Adenine

Cellular senescence, stable cell cycle arrest that can be triggered in normal cells in response to various intrinsic and extrinsic stressors, has been highlighted as one of the most important mechanisms involved in kidney diseases. It not only serves as a fundamental biological process promoting normal organogenesis and successful wound repair but also contributes to organ dysfunction, tissue fibrosis, and the generalized aging phenotype. Moreover, senescent cells exhibit reduced regenerative capacity, which impairs renal function recovery from injuries. Importantly, senescent cells are involved in immune regulation via secreting a diverse array of proinflammatory and profibrotic factors known as senescence-associated secretory phenotype (SASP) with autocrine, paracrine, and endocrine activities. Thus, eliminating detrimental senescent cells or inhibiting SASP production holds great promise for developing innovative therapeutic strategies for kidney diseases. In this review, we summarize the current knowledge of the intricate mechanisms and hallmarks of cellular senescence in kidney diseases and emphasize novel therapeutic targets, including epigenetic regulators, G protein-coupled receptors, and lysosome-related proteins. Particularly, we highlight the recently identified senotherapeutics, which provide new therapeutic strategies for treating kidney diseases.
Humans ; Cellular Senescence/genetics* ; Kidney Diseases/pathology* ; Senescence-Associated Secretory Phenotype/physiology* ; Animals ; Epigenesis, Genetic/physiology*

Objective To investigate the clinical features of chronic hepatitis C(CHC)patients with hepatitis C virus genotype 3(HCV GT3)infection and the risk factors for disease progression.Methods A multicenter retrospective cohort study was conducted among 1 002 CHC patients from 11 clinical centers in Northwest China from December 2017 to November 2023,and according to their genotype,they were divided into GT1,GT2,GT3,and GT6 groups.Clinical features were compared between the patients with different genotypes.The one-way analysis of variance was used for comparison of normally distributed continuous data between groups,and the Scheffe test was used for further comparison between two groups.The Kruskal-Wallis H test was used for comparison of data with skewed distribution between groups;the chi-square test or Fisher test was used for comparison of categorical data between groups.The multivariate logistic regression analysis was used to explore the influencing factors for the progression of CHC to liver cirrhosis.Results In terms of the genotype,there were 427 patients with GT1 infection,242 with GT2 infection,299 with GT3 infection(210 patients with GT3a infection,87 with GT3b infection,and 2 with unclassified genotype),and 34 with GT6 infection.The patients with GT3 infection had a significantly younger age than those with GT1 infection(51.3±0.5 years vs 53.2±0.6 years,P<0.05)or GT2 infection(51.3±0.5 years vs 53.7±0.8 years,P<0.05),and for the patients with liver cirrhosis,the patients with GT3 infection had a significantly younger age than those with GT1 infection(52.1±0.5 years vs 59.4±0.9 years,P<0.001)or GT2 infection(52.1±0.5 years vs 58.1±1.1 years,P<0.001).Among the patients with GT3 infection,male patients accounted for 77.9%and the patients with liver cirrhosis accounted for 46.2%,which were significantly higher than those among the patients with GT1,GT2 or GT6 infection(all P<0.001).At baseline,the patients with GT3 infection had significantly higher levels of alanine aminotransferase(ALT)and aspartate aminotransferase(AST)than those with GT1 or GT2 infection,significantly higher aspartate aminotransferase-to-platelet ratio index(APRI)and fibrosis-4(FIB4)than those with GT1,GT2 or GT6 infection,a significantly lower platelet count(PLT)than those with GT2 or GT6 infection,a significantly higher level of alpha-fetoprotein than those with GT2 or GT6 infection,and a significantly lower level of albumin(Alb)than those with GT6 infection(all P<0.05).There were no significant differences between the patients with GT3a infection and those with GT3b infection in age,sex,the proportion of patients with liver cirrhosis,comorbidities,HCV RNA quantification,PLT,ALT,AST,alkaline phosphatase,Alb,APRI,and FIB-4(all P>0.05).The multivariate logistic regression analysis showed that PLT≤150×109/L(odds ratio[OR]=10.72,95%confidence interval[CI]:5.76-35.86,P<0.001)and Alb≤35 g/L(OR=3.74,95%CI:1.22-11.45,P=0.021)were risk factors for liver cirrhosis.Conclusion Most CHC patients with GT3 infection are male in Northwest China,and compared with the patients with other genotypes,such patients tend to have a younger age of onset and higher degrees of liver inflammation activity and fibrosis.Low PLT and a low level of Alb are risk factors for progression to liver cirrhosis in CHC patients with GT3 infection.

Objective:Investigate key genes influencing vascular calcification through bioinformatics analysis and experimental validation.Methods:Three vascular calcification datasets (GSE159832, GSE229679 and GSE37558) were obtained from the Gene Expression Omnibus database. Subsequently, gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and conventional gene set enrichment analysis (GSEA) were performed on the common differential expressed genes(DEGs). For in vitro validation, a vascular smooth muscle cell calcification model was established by stimulating mouse primary vascular smooth muscle cells with high phosphate and calcium chloride (Pi+CaCl 2). Cells were divided into a control group and a Pi+CaCl 2 group. To investigate the role of TK1, cells were transfected with TK1-targeting siRNA (siTK1) or control siRNA (siControl) prior to Pi+CaCl 2 stimulation, creating siControl+Pi+CaCl 2 and siTK1+Pi+CaCl 2 groups. The association between key DEGs and vascular calcification was assessed at the protein and mRNA levels using Western blot and quantitative real-time PCR, respectively. Changes in the phosphorylation of the downstream effector, AKT (p-AKT/AKT), were also measured. Results:A total of 2275, 449, and 381 DEGs were identified from the three vascular calcification datasets (GSE159832, GSE229679, and GSE37558), respectively. Two common DEGs-phosphoserine aminotransferase 1 and thymidine kinase 1 (TK1)-were identified across all datasets. GO enrichment analysis revealed that TK1 was significantly enriched in pathways related to ribosome biogenesis, assembly, and rRNA processing and maturation. GSEA-KEGG analysis indicated significant enrichment in the PI3K-AKT signaling pathway, pathways in cancer, neurodegenerative diseases, cytoskeleton, and smooth muscle contraction. Conventional GSEA of TK1 further confirmed significant enrichment in pathways including dynein, epithelial tight junctions, axon guidance, and vascular smooth muscle contraction pathways. At the experimental level, both protein and mRNA expression of TK1, along with the p-AKT/AKT ratio, were significantly lower in the Pi+CaCl 2 group compared to the control group (all P<0.05). Furthermore, compared to the siControl+Pi+CaCl 2 group, the siTK1+Pi+CaCl 2 group exhibited decreased expression of differentiation markers, increased expression of calcification markers, and a further reduced p-AKT/AKT ratio (all P<0.05). Conclusion:Integrated bioinformatics and cellular validation demonstrate a correlation between TK1 expression and vascular calcification, suggesting a potential protective role for TK1 in this pathological process.

Objective To investigate the clinical features of chronic hepatitis C(CHC)patients with hepatitis C virus genotype 3(HCV GT3)infection and the risk factors for disease progression.Methods A multicenter retrospective cohort study was conducted among 1 002 CHC patients from 11 clinical centers in Northwest China from December 2017 to November 2023,and according to their genotype,they were divided into GT1,GT2,GT3,and GT6 groups.Clinical features were compared between the patients with different genotypes.The one-way analysis of variance was used for comparison of normally distributed continuous data between groups,and the Scheffe test was used for further comparison between two groups.The Kruskal-Wallis H test was used for comparison of data with skewed distribution between groups;the chi-square test or Fisher test was used for comparison of categorical data between groups.The multivariate logistic regression analysis was used to explore the influencing factors for the progression of CHC to liver cirrhosis.Results In terms of the genotype,there were 427 patients with GT1 infection,242 with GT2 infection,299 with GT3 infection(210 patients with GT3a infection,87 with GT3b infection,and 2 with unclassified genotype),and 34 with GT6 infection.The patients with GT3 infection had a significantly younger age than those with GT1 infection(51.3±0.5 years vs 53.2±0.6 years,P<0.05)or GT2 infection(51.3±0.5 years vs 53.7±0.8 years,P<0.05),and for the patients with liver cirrhosis,the patients with GT3 infection had a significantly younger age than those with GT1 infection(52.1±0.5 years vs 59.4±0.9 years,P<0.001)or GT2 infection(52.1±0.5 years vs 58.1±1.1 years,P<0.001).Among the patients with GT3 infection,male patients accounted for 77.9%and the patients with liver cirrhosis accounted for 46.2%,which were significantly higher than those among the patients with GT1,GT2 or GT6 infection(all P<0.001).At baseline,the patients with GT3 infection had significantly higher levels of alanine aminotransferase(ALT)and aspartate aminotransferase(AST)than those with GT1 or GT2 infection,significantly higher aspartate aminotransferase-to-platelet ratio index(APRI)and fibrosis-4(FIB4)than those with GT1,GT2 or GT6 infection,a significantly lower platelet count(PLT)than those with GT2 or GT6 infection,a significantly higher level of alpha-fetoprotein than those with GT2 or GT6 infection,and a significantly lower level of albumin(Alb)than those with GT6 infection(all P<0.05).There were no significant differences between the patients with GT3a infection and those with GT3b infection in age,sex,the proportion of patients with liver cirrhosis,comorbidities,HCV RNA quantification,PLT,ALT,AST,alkaline phosphatase,Alb,APRI,and FIB-4(all P>0.05).The multivariate logistic regression analysis showed that PLT≤150×109/L(odds ratio[OR]=10.72,95%confidence interval[CI]:5.76-35.86,P<0.001)and Alb≤35 g/L(OR=3.74,95%CI:1.22-11.45,P=0.021)were risk factors for liver cirrhosis.Conclusion Most CHC patients with GT3 infection are male in Northwest China,and compared with the patients with other genotypes,such patients tend to have a younger age of onset and higher degrees of liver inflammation activity and fibrosis.Low PLT and a low level of Alb are risk factors for progression to liver cirrhosis in CHC patients with GT3 infection.

Objective:To explore the correlation between serum nidogen-2 (NID-2) and thoracic aortic calcification in patients with chronic kidney disease (CKD), and construct a risk prediction model based on NID-2 to evaluate its value in predicting the risk of the severe thoracic aortic calcification and cardiovascular and cerebrovascular events in CKD patients.Methods:It was a prospective cohort study. Patients with CKD at stage 3 to 5D in the Zhongda Hospital Affiliated to Southeast University from January 2022 to January 2023 were enrolled. Syngo.via software was used to evaluate the volume of thoracic aortic calcification, and enzyme-linked immunosorbent assay was employed to determine the level of serum NID-2. According to the volume of thoracic aortic calcification, the patients were divided into three groups: no calcification group, mild calcification group and severe calcification group. The top 25% of the patients were defined as no or mild calcification group, and the latter 75% were defined as severe calcification group. The follow-up period was one year. During the follow-up period, cardiovascular and cerebrovascular events, as well as all-cause death among the enrolled patients were recorded. Logistic regression analysis was used to screen the influencing factors of thoracic aortic calcification. Based on the results of logistic regression analysis, a nomogram prediction model was constructed. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve were employed to evaluate the discrimination, calibration and clinical practicality of the nomogram model.Results:A total of 132 patients were included, with 91 males (68.94%) and age of (56.51±16.37) years. There were 60 CKD 3-5 stage patients (non-dialysis, 45.45%) and 72 CKD 5D patients (dialysis, 54.55%). Serum ND-2 levels differed significantly among healthy individuals, dialysis patients and non-dialysis patients ( H=70.651, P<0.001). There was no statistically significant difference in serum NID-2 level between the no or mild calcification group and the severe calcification group in dialysis patients ( Z=350.00, P=0.426). The serum NID-2 level in the severe calcification group was significantly higher than that in the no or mild calcification group in non-dialysis patients ( Z=242.00, P=0.019). In non-dialysis patients, there was a statistically significant correlation between serum NID-2 level and volume of thoracic aortic calcification ( r=0.40, P<0.001). In dialysis patients, there was no statistically significant correlation between serum NID-2 level and volume of each segment of thoracic aortic calcification (all P>0.05). The univariate logistic regression analysis showed that, age, hemoglobin, serum albumin, estimated glomerular filtration rate, NID-2, hypertension, type 2 diabetes mellitus and cerebral infarction were correlated factors of thoracic aortic calcification in non-dialysis patients (all P<0.05). Multivariate logistic regression analysis showed that age ( OR=1.22, 95% CI 1.08-1.50, P=0.010) was an independent correlated factor of thoracic aortic calcification in non-dialysis patients. The above related variables of univariate logistic regression analysis were incorporated into a nomogram to construct a predictive model for severe vascular calcification in non-dialysis patients, yielding an AUC of 0.94 (95% CI 0.89-0.99) in ROC curve, with a sensitivity of 83% and a specificity of 95%. A nomogram model based on above variables for predicting cardiovascular and cerebrovascular events in non-dialysis patients demonstrated an AUC of 0.95 (95% CI 0.90-1.00) in ROC curve, with a sensitivity of 95% and a specificity of 87%. Conclusions:In non-dialysis patients, serum NID-2 level in the severe calcification group is significantly higher than that in the no or mild calcification group. The serum NID-2 is a related factor of thoracic aortic calcification and cardiovascular and cerebrovascular events in non-dialysis patients. The nomogram prediction model constructed by combining NID-2 with age, hemoglobin, serum albumin, estimated glomerular filtration rate, hypertension, type 2 diabetes mellitus and cerebral infarction has a high predictive value for the risk of thoracic aortic calcification as well as cardiovascular and cerebrovascular events in non-dialysis patients.

Objective:Investigate key genes influencing vascular calcification through bioinformatics analysis and experimental validation.Methods:Three vascular calcification datasets (GSE159832, GSE229679 and GSE37558) were obtained from the Gene Expression Omnibus database. Subsequently, gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and conventional gene set enrichment analysis (GSEA) were performed on the common differential expressed genes(DEGs). For in vitro validation, a vascular smooth muscle cell calcification model was established by stimulating mouse primary vascular smooth muscle cells with high phosphate and calcium chloride (Pi+CaCl 2). Cells were divided into a control group and a Pi+CaCl 2 group. To investigate the role of TK1, cells were transfected with TK1-targeting siRNA (siTK1) or control siRNA (siControl) prior to Pi+CaCl 2 stimulation, creating siControl+Pi+CaCl 2 and siTK1+Pi+CaCl 2 groups. The association between key DEGs and vascular calcification was assessed at the protein and mRNA levels using Western blot and quantitative real-time PCR, respectively. Changes in the phosphorylation of the downstream effector, AKT (p-AKT/AKT), were also measured. Results:A total of 2275, 449, and 381 DEGs were identified from the three vascular calcification datasets (GSE159832, GSE229679, and GSE37558), respectively. Two common DEGs-phosphoserine aminotransferase 1 and thymidine kinase 1 (TK1)-were identified across all datasets. GO enrichment analysis revealed that TK1 was significantly enriched in pathways related to ribosome biogenesis, assembly, and rRNA processing and maturation. GSEA-KEGG analysis indicated significant enrichment in the PI3K-AKT signaling pathway, pathways in cancer, neurodegenerative diseases, cytoskeleton, and smooth muscle contraction. Conventional GSEA of TK1 further confirmed significant enrichment in pathways including dynein, epithelial tight junctions, axon guidance, and vascular smooth muscle contraction pathways. At the experimental level, both protein and mRNA expression of TK1, along with the p-AKT/AKT ratio, were significantly lower in the Pi+CaCl 2 group compared to the control group (all P<0.05). Furthermore, compared to the siControl+Pi+CaCl 2 group, the siTK1+Pi+CaCl 2 group exhibited decreased expression of differentiation markers, increased expression of calcification markers, and a further reduced p-AKT/AKT ratio (all P<0.05). Conclusion:Integrated bioinformatics and cellular validation demonstrate a correlation between TK1 expression and vascular calcification, suggesting a potential protective role for TK1 in this pathological process.

Objective To investigate the practice and barriers to functional monitoring of autogenous arteriove-nous fistula(AVF)in hemodialysis centers in China.Methods Using convenience sampling,from March to April 2022,a questionnaire was designed based on the literature of AVF functional monitoring,and a total of 527 hemodialysis centers in China were investigated from 3 aspects,including monitoring process and system,monitoring method and cont ent,and monitoring team construction.Results 506 questionnaires were effectively recovered,with a recovery rate of 96.02％.The implementation rate of the 12 entries of AVF functional monitoring ranged from 12.65％～79.84％,with an overall score of(4.97±3.03).The scores had statistically significant differences in 6 admin-istrative regions of China in monitoring process and system,monitoring method and content,and monitoring team building,as well as the total scores(P＜0.001).Barriers were centered on management specification,human resource allocation,professional training,and healthcare costs.Conclusion Hospital administrators should construct and per-fect the relevant management system according to the scale and actual situation of different hemodialysis centers,strengthen the supervision of AVF functional monitoring as well as the personalised management of monitoring pro-tocols,and promote the development of a multidisciplinary cooperation model for vascular access.

Objective:To identify the risk factors, and develop and validate a risk prediction model for abnormal bone mass in end-stage renal disease (ESRD) patients.Methods:It was a retrospective cross-sectional study. The clinical and laboratory data of ESRD patients who were hospitalized in the Department of Nephrology, Zhongda Hospital Affiliated to Southeast University from January 2022 to May 2023 were collected retrospectively. The patients were randomly divided into training and validation cohorts at a ratio of 7∶3. They were further divided into normal and abnormal bone mass groups according to the T value measured by dual-energy X-ray absorptiometry (DXA). Then, backward stepwise regression and least absolute shrinkage and selection operator (LASSO) were respectively used to develop the risk prediction model for abnormal bone mass in ESRD patients. Akaike information criterion (AIC), bayesian information criterion (BIC), and accuracy were used to evaluate the performance of these two models, after which the preferable model was selected. Moreover, the receiver operating characteristic (ROC) curve, calibration curve, Hosmer-Lemeshow test, and decision curve analyses (DCA) were applied to evaluate the diagnostic performance of the preferable model. Finally, a dynamic nomogram for individual assessment was constructed based on the preferable model.Results:A total of 254 ESRD patients were enrolled, including 160 (63.0%) males, 161 (63.4%) hemodialysis patients, and 202 (79.5%) patients with abnormal bone mass. There was no significant difference in the prevalence of abnormal bone mass between training group ( n=178) and validation group ( n=76) (79.2% vs. 80.3%, χ2=0.036, P=0.849). The final variables and variable parameters included in the LASSO and stepwise regression models were the same, which were five variables: age, body mass index, hypertension, diabetes, and osteocalcin. Both models also had the same AIC, BIC, and accuracy in the training group, which were 113.45, 132.54, and 0.837, respectively. Therefore, the LASSO model and the stepwise regression model performed consistently in this study and could be considered as the same model, hereafter referred to as the Model. The Model's area under the ROC curve in the training and validation groups was 0.923 (95% CI 0.884-0.963) and 0.809 (95% CI 0.675-0.943), respectively. The optimal cutoff for the training group was 0.858, with a sensitivity of 0.801, a specificity of 0.973 and an accuracy of 0.837; when this cutoff value was taken, the validation group's sensitivity was 0.689, specificity was 0.800, and accuracy was 0.711. The Model demonstrated excellent performance in the calibration curve, Hosmer-Lemeshow test ( P>0.05), and DCA. Finally, based on the five predictors of the Model, a dynamic nomogram was created for clinicians to enter baseline clinical parameters for early identification of high-risk patients with abnormal bone mass. Conclusions:A dynamic nomogram for abnormal bone mass in ESRD patients is constructed with good predictive performance based on the prediction model, which can be used as a practical approach for the personalized early screening and auxiliary diagnosis of the potential risk factors and assist physicians in making a personalized diagnosis for patients.