Objective To explore the influencing factors of cognitive impairment in non-dialysis patients with chronic kidney disease(CKD).Methods A total of 60 hospitalized non-dialysis patients with CKD in the Department of Nephrology of Northern Jiangsu People's Hospital Affiliated to Yangzhou University from September 2022 to September 2023 were enrolled as research objects.According to the estimated glomerular filtration rate(eGFR),they were divided into stage 1 to 2 of CKD group[eGFR ≥60 mL/(min·1.73 m2)]with 23 cases,the stage 3 of CKD group[eGFR 30～＜60 mL/(min·1.73 m2)]with 20 cases,and stage 4 to 5 of CKD group[eGFR＜30 mL/(min·1.73 m2)]with 17 cases.The Montreal Cognitive Assessment Scale(MoCA)was used to evaluate the cognitive function of the patients.Basic data and common clinical laboratory in-dicators on hospital admission were collected to analyze the differences in cognitive function levels under different renal function statuses and to explore the influencing factors of cognitive impairment.Results The incidence rates of cognitive impairment in the stage 1 to 2 of CKD group,stage 3 of CKD group,and stage 4 to 5 of CKD group were 47.8％,85.0％,and 94.1％respectively,the median MoCA scored 26,24 and 20 respectively,with statistically significant between-group differ-ences(P＜0.05).Cognitive function was significantly negatively correlated with age(r=-0.634,P＜0.001),blood urea nitrogen(BUN)(r=-0.574,P＜0.001),serum creatinine(Cr)(r=-0.417,P＜0.001),cystatin C(Cys-C)(r=-0.327,P=0.011),serum β2-microglobulin(β2-MG)(r=-0.259,P=0.046),and N-terminal pro-brain natriuretic peptide(NT-proBNP)(r=-0.474,P＜0.001),and was significantly positively correlated with hemoglobin(HB)(r=0.401,P=0.001)and eGFR(r=0.485,P＜0.001).Multivariate Logistic regression analysis showed that age(P=0.006)and NT-proBNP(P=0.041)were influencing factors of cognitive im-pairment in non-dialysis patients with CKD.Receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC),sensitivity,and specificity of age for prediction were 0.860,0.864 and 0.812 respectively,the AUC,sensitivity,and specificity of NT-proBNP for pre-diction were 0.808,0.795 and 0.875 respectively,and the combined prediction of age and NT-proBNP had an AUC,sensitivity,and specificity of 0.893,0.955,and 0.750,respectively.Conclusion As renal function deteriorates,the incidence rate and severity of cognitive impairment in non-dialysis patients with CKD tend to increase.Advanced age,renal function deterioration,high NT-proBNP level,and anemia are associated with the occurrence of cognitive impairment in non-di-alysis patients with CKD,among which age and NT-proBNP are influencing factors for cognitive im-pairment.

Objectives:To evaluate the hemodynamic impact of different bypass grafting methods on the left anterior descending(LAD)artery using computational fluid dynamics,providing a theoretical basis for optimizing coronary artery bypass grafting.Methods:A patient-specific 3D coronary model was constructed using SimVascular software,including an in-situ internal mammary artery graft(model 1)and three free grafts of varying diameters(model 2:2 mm internal mammary artery free graft;model 3 and model 4:3 mm and 4 mm great saphenous vein free grafts).The hemodynamic parameters of the native artery and grafts were compared among the four bypass grafting models.Results:All four bypass grafting models supply sufficient blood flow for the severely stenosed LAD.LAD flow was slightly lower in the model 1.Free internal mammary artery grafts showed higher flow and wall shear stress.4 mm great saphenous vein free grafts presented with maximum flow but lowest shear stress,3 mm great saphenous vein free grafts offered better hemodynamic stability.Conclusions:Computational fluid dynamics analysis indicates that free internal mammary grafts could provide superior hemodynamics,while larger grafts result in lower shear stress,which might affect long-term graft patency.These findings thus provide experimental evidences useful for optimizing LAD bypass strategies.

BACKGROUND: Delayed platelet engraftment is a common complication after umbilical cord blood transplantation (UCBT), and there is no standard therapy. Avatrombopag (AVA) is a second-generation thrombopoietin (TPO) receptor agonist (TPO-RA) that has shown efficacy in immune thrombocytopenia (ITP). However, few reports have focused on its efficacy in patients diagnosed with thrombocytopenia after allogeneic hematopoietic stem cell transplantation (allo-HSCT). METHODS: We conducted a retrospective study at the First Affiliated Hospital of the University of Science and Technology of China to evaluate the efficacy of AVA as a first-line TPO-RA in 65 patients after UCBT; these patients were compared with 118 historical controls. Response rates, platelet counts, megakaryocyte counts in bone marrow, bleeding events, adverse events and survival rates were evaluated in this study. Platelet reconstitution differences were compared between different medication groups. Multivariable analysis was used to explore the independent beneficial factors for platelet implantation. RESULTS: Fifty-two patients were given AVA within 30 days post-UCBT, and the treatment was continued for more than 7 days to promote platelet engraftment (AVA group); the other 13 patients were given AVA for secondary failure of platelet recovery (SFPR group). The median time to platelet engraftment was shorter in the AVA group than in the historical control group (32.5 days vs . 38.0 days, Z  = 2.095, P  = 0.036). Among the 52 patients in the AVA group, 46 achieved an overall response (OR) (88.5%), and the cumulative incidence of OR was 91.9%. Patients treated with AVA only had a greater 60-day cumulative incidence of platelet engraftment than patients treated with recombinant human thrombopoietin (rhTPO) only or rhTPO combined with AVA (95.2% vs . 84.5% vs . 80.6%, P  <0.001). Patients suffering from SFPR had a slightly better cumulative incidence of OR (100%, P  = 0.104). Patients who initiated AVA treatment within 14 days post-UCBT had a better 60-day cumulative incidence of platelet engraftment than did those who received AVA after 14 days post-UCBT (96.6% vs . 73.9%, P  = 0.003). CONCLUSION Compared with those in the historical control group, our results indicate that AVA could effectively promote platelet engraftment and recovery after UCBT, especially when used in the early period (≤14 days post-UCBT).
Humans ; Female ; Male ; Thrombocytopenia/etiology* ; Adult ; Retrospective Studies ; Cord Blood Stem Cell Transplantation/adverse effects* ; Middle Aged ; Adolescent ; Young Adult ; Thiazoles/adverse effects* ; Platelet Count ; Receptors, Thrombopoietin/agonists* ; Child ; Thiophenes

Objective:To explore the core factors of self-management and quality of life (QOL) in patients with chronic obstructive pulmonary disease (COPD) and the internal relationship between these two constructs.Methods:A convenience sampling method was used to enroll 210 COPD patients who visited the Fifth Affiliated Hospital, Sun Yat-sen University from January to December 2022. Data were collected using Self-Management Scale and 36-item Short-Form. A relationship network between self-management and QOL was constructed via network analysis, and centrality indicators and network stability were calculated.Results:A total of 210 questionnaires were distributed, and 205 valid questionnaires were recovered, with an effective recovery rate of 97.6%. Emotional management was identified as the core node in both the overall network and the self-management subnetwork (2.064), while vitality was the core node in the QOL subnetwork (0.730). The relationship between self-management and QOL was mainly manifested through the strong association between emotional management and role-emotion.Conclusions:Emotional management is the core factor in the relationship between self-management and QOL in COPD patients. The overall network of self-management and QOL is influenced by the strong association between emotional management and role-emotion.

Objective:To construct a prediction model for bowel preparation failure in patients undergoing colonoscopy.Methods:A total of 378 inpatients from the Department of Gastroenterology who underwent colonoscopy at the Fifth Affiliated Hospital of Sun Yat-sen University from August 2021 to May 2022 were selected by convenience sampling. The quality of bowel preparation was evaluated using the Boston Bowel Preparation Scale (BBPS). Baseline demographic information, relevant clinical data, and laboratory test results after admission were collected. Logistic regression analysis was performed to identify factors influencing bowel preparation failure and to construct the prediction model. The discriminative ability, calibration, and clinical utility of the model were evaluated using receiver operating characteristic (ROC) curve, nomogram calibration curve, and decision curve analysis.Results:According to BBPS scores, 199 of the 378 patients experienced bowel preparation failure. Logistic regression analysis showed that a history of abdominal surgery, dyslipidemia, hypertension, liver cirrhosis, and colonoscopy timing were independent predictors of bowel preparation failure ( P<0.05). The area under the ROC curve of the constructed model was 0.835 (95% confidence interval: 0.759-0.874). The calibration curve indicated that the deviation between predicted and actual outcomes was small. The decision curve analysis showed favorable clinical utility within a threshold probability range of 0.18-0.85. Conclusions:The prediction model for bowel preparation failure constructed in this study demonstrated good discrimination, calibration, and clinical utility. The model can effectively predict the quality of bowel preparation in patients undergoing colonoscopy, provide scientific support for clinical decision-making, and help optimize bowel preparation regimens, thereby improving the success rate and safety of colonoscopy.

Objective This study aims to explore the application value of spectral CT and perfusion CT parameters in the pathological classification and prognostic assessment of lung cancer.Methods A total of 94 lung cancer patients confirmed by pathology at Shanghai Chest Hospital from January 2023 to November 2024 were included in the study,including 49 cases of lung adenocarcinoma(LUAD),30 cases of lung squamous cell carci-noma(LUSC),and 15 cases of small cell lung cancer(SCLC).All patients underwent spectral CT combined with perfusion scanning using a 256-slice Revolution Apex from GE.Two radiologists independently measured the spectral and perfusion parameters of the three groups of images,including spectral curve slope(K),iodine concentration in the lesion area(ICL),effective atomic number(Zeff),surface permeability(PS),and perfusion index(PI),and established a lung cancer pathological subtype discrimination prediction model based on spectral CT radiomics features.All subjects were randomly divided into a training group and a validation group at a ratio of 3∶1.The discrimination efficacy of the spectral discrimination model between different pathological subtypes and the discrimination efficacy of arterial and venous phase images were compared in multiple dimensions.The performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results Statistical analysis showed that the spectral curve slope,ICL,NIC,and Zeff of LUAD patients were significantly higher than those of LUSC and SCLC patients(P<0.05),while there were no significant differences in these parameters between LUSC and SCLC patients(P>0.05).Among the perfusion CT parameters,surface permeability(PS)showed significant differences among the three groups(P<0.05),while blood volume(BV),blood flow(BF),perfusion index(PI),time to peak(TTP),and mean transit time(MTT)did not show statistical differences.The multi-factor logistic regression model based on spectral parameters showed strong discriminatory performance:the area under the curve(AUC)of the LUAD and LUSC discrimination model was 0.806/0.77(training group/test group)in the arterial phase and 0.867/0.9(training group/test group)in the venous phase;the AUC of the LUAD and SCLC discrimination model was 0.885/0.883(training group/test group)in the arterial phase and 0.851/0.776(training group/test group)in the venous phase.Conclusion This study indicates that the multi-dimensional functional metabolic analysis indicators of spectral and perfusion CT imaging have significant value in the differential diagnosis of lung cancer pathological subtypes.The diagnostic model constructed by combining multiple spectral parameters can significantly improve the discrimination efficacy of lung adenocarcinoma,squamous cell carcinoma,and small cell lung cancer,providing precise imaging evidence for the formulation of individualized treatment plans.

The significance of the retinal neurovascular unit(NVU)in glaucoma has been established,and it holds po-tential as an effective therapeutic target for neurodegenerative disorders such as glaucoma in the future.NVUs are a cell community composed of neurons,glial cells,and vascular cells,and they engage in the physiological and pathological inter-actions between retinal neurovasculature through neurovascular coupling(NVC).As a representative neurodegenerative disorder of the retina,glaucoma is closely associated with retinal microvasculature and glial cells,rendering the normal functioning of the NVU particularly crucial.In this paper,the structural foundation of the NVU was reviewed,including the leading and coordinating roles of retinal neurons and glial cells in the NVU,and the role of NVCs in regulating retinal blood flow,metabolism,and the clearance of toxic substances.Furthermore,the associations of the components of the NVU and their functional abnormalities with glaucoma were elucidated.This paper will deepen the understanding of the mechanisms of glaucoma from a neurovascular perspective,and provide new preventive directions or therapeutic targets for neuropro-tection in glaucoma.

Objective This study aims to explore the application value of spectral CT and perfusion CT parameters in the pathological classification and prognostic assessment of lung cancer.Methods A total of 94 lung cancer patients confirmed by pathology at Shanghai Chest Hospital from January 2023 to November 2024 were included in the study,including 49 cases of lung adenocarcinoma(LUAD),30 cases of lung squamous cell carci-noma(LUSC),and 15 cases of small cell lung cancer(SCLC).All patients underwent spectral CT combined with perfusion scanning using a 256-slice Revolution Apex from GE.Two radiologists independently measured the spectral and perfusion parameters of the three groups of images,including spectral curve slope(K),iodine concentration in the lesion area(ICL),effective atomic number(Zeff),surface permeability(PS),and perfusion index(PI),and established a lung cancer pathological subtype discrimination prediction model based on spectral CT radiomics features.All subjects were randomly divided into a training group and a validation group at a ratio of 3∶1.The discrimination efficacy of the spectral discrimination model between different pathological subtypes and the discrimination efficacy of arterial and venous phase images were compared in multiple dimensions.The performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results Statistical analysis showed that the spectral curve slope,ICL,NIC,and Zeff of LUAD patients were significantly higher than those of LUSC and SCLC patients(P<0.05),while there were no significant differences in these parameters between LUSC and SCLC patients(P>0.05).Among the perfusion CT parameters,surface permeability(PS)showed significant differences among the three groups(P<0.05),while blood volume(BV),blood flow(BF),perfusion index(PI),time to peak(TTP),and mean transit time(MTT)did not show statistical differences.The multi-factor logistic regression model based on spectral parameters showed strong discriminatory performance:the area under the curve(AUC)of the LUAD and LUSC discrimination model was 0.806/0.77(training group/test group)in the arterial phase and 0.867/0.9(training group/test group)in the venous phase;the AUC of the LUAD and SCLC discrimination model was 0.885/0.883(training group/test group)in the arterial phase and 0.851/0.776(training group/test group)in the venous phase.Conclusion This study indicates that the multi-dimensional functional metabolic analysis indicators of spectral and perfusion CT imaging have significant value in the differential diagnosis of lung cancer pathological subtypes.The diagnostic model constructed by combining multiple spectral parameters can significantly improve the discrimination efficacy of lung adenocarcinoma,squamous cell carcinoma,and small cell lung cancer,providing precise imaging evidence for the formulation of individualized treatment plans.

Objective:To explore the core factors of self-management and quality of life (QOL) in patients with chronic obstructive pulmonary disease (COPD) and the internal relationship between these two constructs.Methods:A convenience sampling method was used to enroll 210 COPD patients who visited the Fifth Affiliated Hospital, Sun Yat-sen University from January to December 2022. Data were collected using Self-Management Scale and 36-item Short-Form. A relationship network between self-management and QOL was constructed via network analysis, and centrality indicators and network stability were calculated.Results:A total of 210 questionnaires were distributed, and 205 valid questionnaires were recovered, with an effective recovery rate of 97.6%. Emotional management was identified as the core node in both the overall network and the self-management subnetwork (2.064), while vitality was the core node in the QOL subnetwork (0.730). The relationship between self-management and QOL was mainly manifested through the strong association between emotional management and role-emotion.Conclusions:Emotional management is the core factor in the relationship between self-management and QOL in COPD patients. The overall network of self-management and QOL is influenced by the strong association between emotional management and role-emotion.

Objective:To construct a prediction model for bowel preparation failure in patients undergoing colonoscopy.Methods:A total of 378 inpatients from the Department of Gastroenterology who underwent colonoscopy at the Fifth Affiliated Hospital of Sun Yat-sen University from August 2021 to May 2022 were selected by convenience sampling. The quality of bowel preparation was evaluated using the Boston Bowel Preparation Scale (BBPS). Baseline demographic information, relevant clinical data, and laboratory test results after admission were collected. Logistic regression analysis was performed to identify factors influencing bowel preparation failure and to construct the prediction model. The discriminative ability, calibration, and clinical utility of the model were evaluated using receiver operating characteristic (ROC) curve, nomogram calibration curve, and decision curve analysis.Results:According to BBPS scores, 199 of the 378 patients experienced bowel preparation failure. Logistic regression analysis showed that a history of abdominal surgery, dyslipidemia, hypertension, liver cirrhosis, and colonoscopy timing were independent predictors of bowel preparation failure ( P<0.05). The area under the ROC curve of the constructed model was 0.835 (95% confidence interval: 0.759-0.874). The calibration curve indicated that the deviation between predicted and actual outcomes was small. The decision curve analysis showed favorable clinical utility within a threshold probability range of 0.18-0.85. Conclusions:The prediction model for bowel preparation failure constructed in this study demonstrated good discrimination, calibration, and clinical utility. The model can effectively predict the quality of bowel preparation in patients undergoing colonoscopy, provide scientific support for clinical decision-making, and help optimize bowel preparation regimens, thereby improving the success rate and safety of colonoscopy.