BACKGROUND: Approximately 40% of individuals with diabetes worldwide are at risk of developing diabetic kidney disease (DKD), which is not only the leading cause of kidney failure, but also significantly increases the risk of cardiovascular disease, causing significant societal health and financial burdens. This study aimed to describe the burden of DKD and explore its cross-country epidemiological status, predict development trends, and assess its risk factors and sociodemographic transitions. METHODS: Based on the Global Burden of Diseases (GBD) Study 2021, data on DKD due to type 1 diabetes (DKD-T1DM) and type 2 diabetes (DKD-T2DM) were analyzed by sex, age, year, and location. Numbers and age-standardized rates were used to compare the disease burden between DKD-T1DM and DKD-T2DM among locations. Decomposition analysis was used to assess the potential drivers. Locally weighted scatter plot smoothing and Frontier analysis were used to estimate sociodemographic transitions of DKD disability-adjusted life years (DALYs). RESULTS: The DALYs due to DKD increased markedly from 1990 to 2021, with a 74.0% (from 2,227,518 to 3,875,628) and 173.6% (from 4,122,919 to 11,278,935) increase for DKD-T1DM and DKD-T2DM, respectively. In 2030, the estimated DALYs for DKD-T1DM surpassed 4.4 million, with that of DKD-T2DM exceeding 14.6 million. Notably, middle-sociodemographic index (SDI) quintile was responsible for the most significant DALYs. Decomposition analysis revealed that population growth and aging were major drivers for the increased DKD DALYs in most regions. Interestingly, the most pronounced effect of positive DALYs change from 1990 to 2021 was presented in high-SDI quintile, while in low-SDI quintile, DALYs for DKD-T1DM and DKD-T2DM presented a decreasing trend over the past years. Frontiers analysis revealed that there was a negative association between SDI quintiles and age-standardized DALY rates (ASDRs) in DKD-T1DM and DKD-T2DM. Countries with middle-SDI shouldered disproportionately high DKD burden. Kidney dysfunction (nearly 100.0% for DKD-T1DM and DKD-T2DM), high fasting plasma glucose (70.8% for DKD-T1DM and 87.4% for DKD-T2DM), and non-optimal temperatures (low and high, 5.0% for DKD-T1DM and 5.1% for DKD-T2DM) were common risk factors for age-standardized DALYs in T1DM-DKD and T2DM-DKD. There were other specific risk factors for DKD-T2DM such as high body mass index (38.2%), high systolic blood pressure (10.2%), dietary risks (17.8%), low physical activity (6.2%), lead exposure (1.2%), and other environmental risks. CONCLUSIONS DKD markedly increased and varied significantly across regions, contributing to a substantial disease burden, especially in middle-SDI countries. The rise in DKD is primarily driven by population growth, aging, and key risk factors such as high fasting plasma glucose and kidney dysfunction, with projections suggesting continued escalation of the burden by 2030.
Humans ; Global Burden of Disease ; Risk Factors ; Male ; Female ; Disability-Adjusted Life Years ; Diabetic Nephropathies/epidemiology* ; Middle Aged ; Diabetes Mellitus, Type 2/epidemiology* ; Adult ; Diabetes Mellitus, Type 1/complications* ; Aged ; Adolescent ; Young Adult ; Quality-Adjusted Life Years

Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.

Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.

Objective To investigate the clinical manifestations of familial adenomatous polyposis(FAP).Methods The clinical data of 100 patients with FAP diagnosed in the First Affiliated Hospital of Zhengzhou University from 2011 to 2021 were analyzed retrospectively.Results The main clinical manifestations were bloody stool(44.0%),abdominal pain(40.0%),changes of stool characteristics(25.0%),abdominal distension(18.0%)and diarrhea(17.0%);The most common types of adenomas were villous tubular adenoma(44.9%)and tubular adenoma(32.1%);Extraintestinal manifestations:3 cases of desmoid fibroma,2 cases of osteoma and 1 case of lipoma.47 cases of gastric polyps and the mostly pathological type was fundic gland polyp(34.0%).18 cases of duodenal polyps including 6 cases of adenomatous polyps and most were located at descending duodenum(61.1%).Adenoma canceration occurred in 21 patients.The average age was 38.7 and the canceration mainly occurs in the rectum.The gender,family history,age of onset,number of adenomas,diameter and pathological type of adenomas were statistically compared between patients with and without canceration.It was found that there were significant differences in gender,average age of onset,number of adenoma polyps,diameter of adenoma and pathological type between the two groups(P<0.05).Conclusions FAP is mainly characterized by bloody stool and abdominal pain,with high canceration rate.The risk factors include the age of onset,the number and size of adenomas and the pathological type.The main pathological types are villous tubular adenoma and tubular adenoma.At present,preventive colorectal resection is still the most effective way to treat FAP.No matter what type of methods patients choose,they should be followed up strictly under endoscopy in order to find the lesions in time and treat if necessary.

Objective:To examine the validity and reliability of the Chinese version of the Body Acceptance by Others Scale-2(BAOS-2)in adults.Methods:Totally 616 adults(aged 18-56 years)were selected to test the structural validity,and internal consistency reliability of the scale.The Body Appreciation Scale-2(BAS-2),Func-tionality Appreciation Scale(FAS),Self-Compassion Scale(SCS),Self-Esteem Scale(SES)and Satisfaction with Life Scale(SWLS)were used as criteria to test criterion validity.A sample of 55 adults was retested 2 weeks later for the test-retest reliability.Results:The exploratory factor analysis extracted one factor,and the factor loading range of each item was 0.59-0.76.The confirmatory factor analysis showed that the factor model fit indices were acceptable(x2/df=2.99,CFI=0.91,GFI=0.90,TLI=0.89,RMR=0.04,RMSEA=0.08).The scores of the Chinese version of BAOS-2 were positively correlated with the scores of BAS-2,FAS,SCS,SES and SWLS(r=0.43-0.66,Ps＜0.001).The Cronbach a of the Chinese version of BAOS-2 was 0.90,and the test-retest reliabili-ty(ICC)was 0.65.Conclusion:The Chinese version of the Body Acceptance by Others Scale-2(BAOS-2)has i-deal validity and reliability.

Objective To explore the differences of bone age of radius,ulna,metacarpophalangeal and carpal bones in children with different physiques.Methods Radiographs of children's wrists aged between 4 and 12 years were collected.The bone age of radius,ulna,metacarpophalangeal,and carpal bones were assessed using the Chinese Children's Bone Age Score,and the difference between the two bone ages(the former minus the latter)was recorded.According to gender,age,and physical grouping,the physical group was divided into normal and abnormal groups.The abnormal group was further divided into thin,overweight,and obese groups.A comparative analysis was conducted to determine the differences in bone age between normal and abnormal groups for both males and females at all ages.Results A total of 3 028 children were included,and the differences between the two bone age results for normal boys aged 7-12 years and normal girls aged 5-12 years were not statistically significant(P＞0.05).In boys,there was no significant difference in bone age between the normal group and the thin group(P＞0.05),the difference in bone age between the normal and thin groups at the age of 5-6 years was greater than that between the overweight and obese groups,and the difference was statistically significant(P＜0.05),the difference in bone age between the normal group at 11-12 years and the thin group at 11 years was smaller than that between the overweight and obese groups(P＜0.05).The difference in bone age was smaller in the normal group than in the thin group at 6 years of age for girls(P＜0.05),and larger in the thin group than in the overweight and obese groups at 5 to 6 years old(P＜0.05).Conclusion The difference in bone age between the TW-C RUS series and TW-C C series bone age values is influenced by the child's gender,physique,and age.The difference in bone age between the majority of normal children and the thin group is not statistically significant,but differed from the overweight and obese groups at some ages,most are the overweight and obese boys.

Objective:To understand the frailty perception and coping experiences of elderly patients with hip fractures from the patients' perspective, providing insights for healthcare professionals on managing frailty.Methods:A purposive sampling method was used to select 12 elderly patients with hip fractures and frailty who were hospitalized at Tenth People's Hospital of Tongji University from September to October 2023. A phenomenological approach was adopted for this qualitative study, conducting semi-structured interviews to explore the patients' frailty perceptions and coping experiences. NVivo 11.0 software and Colaizzi's seven-step analysis method were used to organize and analyze the interview data.Results:The frailty perceptions of elderly hip fracture patients were categorized into four themes: multidimensional physiological challenges (e.g., aging of the body, nutritional imbalances, pain and sleep disturbances) ; limitations in daily life (e.g., mobility impairments, avoidance of social activities) ; heavy psychological burdens (e.g., uncertainty about the illness, low self-efficacy, feelings of guilt towards the family) ; insufficient social support (e.g., lack of age-friendly environments and limited medical policy coverage). The patients' coping strategies were grouped into two themes: active coping (e.g., self-encouragement, peer support, actively seeking relevant knowledge and guidance) ; passive coping (e.g., neglecting the situation) .Conclusions:Frailty brings multiple negative impacts on the physical, psychological, daily life and social aspects of elderly hip fracture patients; while most patients adopt a positive attitude towards frailty, some exhibit signs of emotional exhaustion and passivity. Medical staff should pay attention to the frailty perceptions of elderly hip fracture patients, identify related symptoms early, provide comprehensive support to alleviate the physical and psychological burden, and encourage patients to face frailty challenges optimistically, adopting proactive measures to slow its progression.

Objective:To extract and summarize the best available evidence on frailty management for elderly patients with hip fractures, providing a reference for developing clinically applicable management protocols.Methods:Following the "6S" evidence model, a systematic search was conducted across national and international databases and guideline websites for evidence on frailty management in elderly hip fracture patients, including guidelines, evidence summaries, systematic reviews, best practices, and expert consensus, with a search period from June 2018 to December 2023. Two researchers independently evaluated the quality of the literature, selecting studies that met inclusion criteria and extracting relevant evidence.Results:A total of 2 589 articles were identified, with 20 articles included: seven guidelines, two best practice standards, one evidence summary, seven expert consensus documents, and three systematic reviews. The best evidence was summarized across six domains: frailty screening, multidisciplinary collaboration, pain management, nutritional management, functional exercise, and discharge guidance, yielding 45 recommendations.Conclusions:The best evidence for frailty management in elderly patients with hip fractures summarized in this study offers valuable insights and scientific guidance for clinical healthcare providers. When applying this evidence, it is recommended to first adapt it to local contexts, considering factors such as institutional environment, healthcare policies, and patient preferences, before conducting implementation research on evidence translation.

Objective:To understand the frailty perception and coping experiences of elderly patients with hip fractures from the patients' perspective, providing insights for healthcare professionals on managing frailty.Methods:A purposive sampling method was used to select 12 elderly patients with hip fractures and frailty who were hospitalized at Tenth People's Hospital of Tongji University from September to October 2023. A phenomenological approach was adopted for this qualitative study, conducting semi-structured interviews to explore the patients' frailty perceptions and coping experiences. NVivo 11.0 software and Colaizzi's seven-step analysis method were used to organize and analyze the interview data.Results:The frailty perceptions of elderly hip fracture patients were categorized into four themes: multidimensional physiological challenges (e.g., aging of the body, nutritional imbalances, pain and sleep disturbances) ; limitations in daily life (e.g., mobility impairments, avoidance of social activities) ; heavy psychological burdens (e.g., uncertainty about the illness, low self-efficacy, feelings of guilt towards the family) ; insufficient social support (e.g., lack of age-friendly environments and limited medical policy coverage). The patients' coping strategies were grouped into two themes: active coping (e.g., self-encouragement, peer support, actively seeking relevant knowledge and guidance) ; passive coping (e.g., neglecting the situation) .Conclusions:Frailty brings multiple negative impacts on the physical, psychological, daily life and social aspects of elderly hip fracture patients; while most patients adopt a positive attitude towards frailty, some exhibit signs of emotional exhaustion and passivity. Medical staff should pay attention to the frailty perceptions of elderly hip fracture patients, identify related symptoms early, provide comprehensive support to alleviate the physical and psychological burden, and encourage patients to face frailty challenges optimistically, adopting proactive measures to slow its progression.

Objective:To extract and summarize the best available evidence on frailty management for elderly patients with hip fractures, providing a reference for developing clinically applicable management protocols.Methods:Following the "6S" evidence model, a systematic search was conducted across national and international databases and guideline websites for evidence on frailty management in elderly hip fracture patients, including guidelines, evidence summaries, systematic reviews, best practices, and expert consensus, with a search period from June 2018 to December 2023. Two researchers independently evaluated the quality of the literature, selecting studies that met inclusion criteria and extracting relevant evidence.Results:A total of 2 589 articles were identified, with 20 articles included: seven guidelines, two best practice standards, one evidence summary, seven expert consensus documents, and three systematic reviews. The best evidence was summarized across six domains: frailty screening, multidisciplinary collaboration, pain management, nutritional management, functional exercise, and discharge guidance, yielding 45 recommendations.Conclusions:The best evidence for frailty management in elderly patients with hip fractures summarized in this study offers valuable insights and scientific guidance for clinical healthcare providers. When applying this evidence, it is recommended to first adapt it to local contexts, considering factors such as institutional environment, healthcare policies, and patient preferences, before conducting implementation research on evidence translation.