OBJECTIVE To compare the risk of pneumonitis and interstitial lung disease （ILD） associated with different antibody-drug conjugates （ADC） in the treatment of breast cancer. METHODS CNKI， VIP， PubMed， Embase and other Chinese and English databases， and ClinicalTrials.gov were searched from the inception to June 15， 2025. Randomized controlled trials （RCT） about pneumonitis and ILD associated with ADC （T-DM1， T-DXd， SG， Dato-DXd， SHR-A1811，ARX788， and T-Duo） in the treatment of breast cancer were included. After literature screening， data extraction， and quality assessment， a network meta-analysis was conducted using Stata 17.0 software， and the surface under the cumulative ranking curve（SUCRA） of all interventions were ranked. RESULTS A total of 19 RCTs involving 10 556 patients were included. The overall incidence of pneumonitis with ARX788 and T-DXd was significantly higher than that with T-DM1， T-DM1 plus TPC（T-DM1combined with pertuzumab or atezolizumab）， TPC（treatment of primary care）， and SG （ P ＜0.05）， for grade 1-2 pneumonitis， ARX788 and T-DXd showed significantly higher incidence than T-DM1， T-DM1 plus TPC， and TPC （ P ＜0.05）. For both indicators， ARX788 and T-Duo were ranked as the top two by SUCRA. For the incidence of grade ≥3 pneumonitis， T-DXd and T-DM1 were significantly higher than SG （ P ＜0.05）， T-Duo and Dato-DXd were ranked as the top two by SUCRA. For overall incidence of ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， TPC， and SG （ P ＜0.05）， for the incidence of grade 1-2 ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， and TPC （ P ＜0.05）， for the incidence of grade ≥3 ILD， ARX788 was significantly higher than TPC （ P ＜0.05）. For three indicators above， ARX788 and T-DXd combined with pertuzumab were ranked as the top two by SUCRA. CONCLUSIONS Compared with other ADCs， ARX788 and T-Duo are associated with a higher risk of pneumonitis and ILD in patients with breast cancer.

Objective To explore the value of three-dimensional automated right ventricular quantification(3D Auto RV)for predicting right ventricular function dysfunction in patients with severe aortic stenosis(AS).Methods Eighty severe AS patients were retrospectively enrolled.Based on right ventricular ejection fraction(RVEF)obtained with 3D Auto RV,the patients were classified into right ventricular compensation group(RVEF≥45%,compensation group,n=56)and right ventricular function decompensation(RVEF＜45%,decompensation group,n=24)group.Ultrasonic parameters related to right ventricular structure and function were compared between groups.Univariable analysis and multivariable logistic regression were performed to observe ultrasound parameters related to right ventricular function,so as to screen out the independent predictors of right ventricular functional decompensation(dysfunction)in patients with severe AS.Results Compared with those in compensation group,right ventricular end diastolic volume and right ventricular end systolic volume of decompensation group increased,while right ventricular fractional area change,tricuspid annular plane systolic excursion,right ventricular free wall longitudinal strain(RVFWLS),septal longitudinal strain(SLS),right ventricular stroke volume and RVEF all decreased(all P＜0.05).Valvulo-arterial impedance(OR=2.337),left ventricular ejection fraction(OR=0.751)and RVFWLS/pulmonary artery systolic pressure(right ventricle-pulmonary artery coupling)(OR=0.653)were all independent predictors of right ventricular dysfunction in patients with severe AS(all P＜0.05).Conclusion 3D Auto RV could be used to effectively predict right ventricular dysfunction in patients with severe AS.

Objective To explore the value of three-dimensional automated right ventricular quantification(3D Auto RV)for predicting right ventricular function dysfunction in patients with severe aortic stenosis(AS).Methods Eighty severe AS patients were retrospectively enrolled.Based on right ventricular ejection fraction(RVEF)obtained with 3D Auto RV,the patients were classified into right ventricular compensation group(RVEF≥45%,compensation group,n=56)and right ventricular function decompensation(RVEF＜45%,decompensation group,n=24)group.Ultrasonic parameters related to right ventricular structure and function were compared between groups.Univariable analysis and multivariable logistic regression were performed to observe ultrasound parameters related to right ventricular function,so as to screen out the independent predictors of right ventricular functional decompensation(dysfunction)in patients with severe AS.Results Compared with those in compensation group,right ventricular end diastolic volume and right ventricular end systolic volume of decompensation group increased,while right ventricular fractional area change,tricuspid annular plane systolic excursion,right ventricular free wall longitudinal strain(RVFWLS),septal longitudinal strain(SLS),right ventricular stroke volume and RVEF all decreased(all P＜0.05).Valvulo-arterial impedance(OR=2.337),left ventricular ejection fraction(OR=0.751)and RVFWLS/pulmonary artery systolic pressure(right ventricle-pulmonary artery coupling)(OR=0.653)were all independent predictors of right ventricular dysfunction in patients with severe AS(all P＜0.05).Conclusion 3D Auto RV could be used to effectively predict right ventricular dysfunction in patients with severe AS.

Objective:To develop a scale on hospice care perception and attitude in family members of critically ill patients, so as to provide a valid tool for measuring the cognition and attitude level of hospice care among family members of critically ill patients.Methods:During May 2022 to 2023, an initial pool of scale entries was formed through the literature analysis method and group discussion. The scale′s first draft was formed by applying the Delphi correspondence method and a small sample pre-survey. The developed scale was administered to 98 family members of critically ill patients in Shandong Provincial Hospital Affiliated to Shandong First Medical University to test the reliability and validity of scale.Results:The results of exploratory factor analysis extracted 5 explanatory factors with a cumulative contribution rate of 77.65%. The developed Hospice Care Perceptions and Attitudes of Families of Critically Ill Patients Scale had 19 items. The content validity of 0.922 and a Cronbach alpha coefficient of 0.816 showed good validity and reliability.Conclusions:The scale has sufficient reliability and can be used to assess cognitive and attitudinal levels of hospice care in family members of critically ill patients.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

OBJECTIVE: To investigate the characteristics of Vitamin D (VitD) and bone metabolism in patients with knee osteoarthritis (KOA) concurrent with osteoporosis (OP). METHODS: A retrospective analysis was performed on 240 patients who were admitted to the orthopedics department between March 2019 and March 2024. Patients were stratified into four distinct groups according to their respective disease categories.There were 90 patients in the simple KOA group, comprising 13 males and 77 females, age ranged from 50 to 91 years old with an average of (68.48±8.96) years old. There were 90 patients in the simple OP group, comprising 7 males and 83 females, age ranged from 52 to 88 years old with an average of (69.60±8.94 )years old. There were 30 patients in the KOA with OP group, comprising 1 male and 29 females, age ranged from 51 to 91 years old with an average of(69.03±7.93) years old. There were 30 patients in the physical examination group, comprising 5 males and 25 females, age ranged from 53 to 79 years old with an average of(64.93±6.51) years old. The general data and the levels of osteocalcin (OC), β-CrossLaps, parathyroid hormone(PTH) and VitD in each group were observed. RESULTS: The level of VitD in KOA with OP group (19.62±10.38) ng·ml^-1 and OP group (20.65±10.50) ng·ml^-1 was lower than that in physical examination group (27.46±8.00) ng·ml^-1 and KOA group (24.01±9.11) ng·ml^-1 (P<0.05). There were significant differences in β- CrossLaps and PTH levels among the four groups (P<0.001, P=0.019, respectively), while there was no significant difference in OC levels (P=0.763). Compared with the two simple disease groups, the KOA with OP group had higher levels of β - CrossLaps(0.81±0.30) ng·ml^-1 (P<0.001). There were significant differences in β-CrossLaps and PTH between the simple KOA group(0.54±0.22) ng·ml^-1, (46.03±18.08) pg·ml^-1 and the physical examination group (0.44±0.19) ng·ml^-1, (36.65±9.63) pg·mL^-1(P=0.038;P=0.006). There was a significant difference in PTH between the OP group(43.85±14.30) ng·ml-1, and the physical examination group, P=0.004. There was a significant difference in Kallgren-Lawrence grading between KOA with OP group and KOA group (P=0.006). Within KOA with OP group, the differences of β-CrossLaps and VitD levels among different K-L grades were statistically significant (P=0.016). The level of OC, β-CrossLaps and PTH within KOA with OP group was significantly different at different VitD levels (P=0.013, P=0.033, P=0.046). CONCLUSION Patients with KOA complicated by OP exhibit greater disturbances in bone metabolism and reduced VitD levels, particularly reflected by elevated β-CrossLaps. These findings underscore the importance of early monitoring of bone turnover and VitD supplementation in advanced-stage KOA with bone loss.
Humans ; Female ; Male ; Middle Aged ; Aged ; Vitamin D/blood* ; Osteoporosis/complications* ; Aged, 80 and over ; Osteoarthritis, Knee/complications* ; Retrospective Studies ; Bone and Bones/metabolism* ; Parathyroid Hormone/metabolism* ; Osteocalcin/metabolism*