Objective:To explore the current situation of ageism among older adults in megacity communities and analyze its influencing factors.Methods:From November to December 2023, convenience sampling was used to select 200 older adults who visited the Niujie Community Health Service Center in Xicheng District, Beijing as the research subject. A survey was conducted on older adults using the General Information Questionnaire, Barthel Index, 15-Item Geriatric Depression Scale, Family Adaptation, Partnership, Growth, Affection and Resolve Scale (Family APGAR Scale), Rosenberg Self-Esteem Scale, Social Support Rating Scale, Lubben Social Network Scale, and Ageism Questionnaire. Multiple linear regression was used to analyze the influencing factors of ageism among older adults in the community.Results:A total of 200 questionnaires were distributed and 200 valid questionnaires were collected, with a valid response rate of 100.00% (200/200). The total score of ageism among 200 older adults in the community was (3.55±0.31), with objective and subjective scores of (3.59±0.28) and (3.50±0.48), respectively. Multiple linear regression showed that occupational status, pre-retirement or current work, family care, self-esteem, and social support were the influencing factors of ageism among older adults in the community ( P<0.05) . Conclusions:Ageism among older adults is influenced by various factors. Medical and nursing staff should focus on older adults who are retired, mainly engaged in physical work, and have poor family and social support when formulating intervention strategies. Community health workers should regularly organize activities to encourage older adults to actively participate, enhance their sense of social participation, reduce ageism, so as to promote healthy aging.

Objective:To investigate the status and influencing factors of different types of cognitive frailty in aged inpatients with hypertension.Methods:Totally 300 aged patients with hypertension admitted to the Cardiology, Geriatrics, and Endocrinology Departments of Xuanwu Hospital, Capital Medical University, from April to October 2022 were selected by convenience sampling. Data were collected using a general information questionnaire, the Fried Frailty Phenotype (FP), the Mini-Mental State Examination (MMSE), the 9-item Subjective Cognitive Decline Questionnaire-9 (SCD-Q9), the Morisky Medication Adherence Scale (MMAS), the Pittsburgh Sleep Quality Index (PSQI), the Hospital Anxiety and Depression Scale (HADS), the Social Support Rating Scale (SSRS), and the Mini Nutritional Assessment (MNA) .Results:A total of 300 questionnaires were distributed and returned, yielding a 100.00% response rate. Among the 300 aged hypertensive patients, 74 were diagnosed with reversible cognitive frailty (RCF) and 98 with potentially reversible cognitive frailty (PRCF). Logistic vegression analysis showed that, factors influencing RCF included daily exercise habits and the use of thiazide diuretics ( P<0.05) ; factors influencing PRCF included age, pre-retirement occupation, daily exercise habits, sleep quality, Barthel Index score, and serum albumin levels ( P<0.05) . Conclusions:The status of both RCF and PRCF is relatively high among aged inpatients with hypertension. The influencing factors for different types of cognitive frailty vary. Targeted interventions based on both common and specific influencing factors should be developed to reverse or slow the progression of cognitive frailty in aged hypertensive patients.

Objective To investigate the independent influences on the occurrence of ICU Acquired Weakness(ICU-AW)in elderly patients undergoing third-and fourth-level surgeries,to construct a prediction model and draw a column-line diagram,and to internally validate the model.Methods A convenience sampling method was used to select 186 elderly patients undergoing tertiary and quaternary surgeries who were hospitalized in 3 tertiary A hospitals in Beijing from May to December 2022 as the study subjects.Single-factor and multifactor logistic regression were used to analyze the risk factors for ICU-AW in elderly patients undergoing third-and fourth-degree surgeries.A risk prediction model was established and the model was visualized by drawing a column-line diagram,and the receiver operator characteristic curve(ROC)and the Hosmer-Lemeshow tests were applied to verify the predictive effect of the model.Results ICU-AW occurred in 40 of 186 cases in the modeling group,with an incidence rate of 21.5％.The results of univariate analysis showed that the 2 groups of preoperative physiology score and surgical severity score included in the physiology and surgical severity scoring system,age,presence of cardiac disease,hemoglobin(within 24 h of admission to the ICU),blood urea nitrogen(within 24 h of admission to the ICU),blood creatinine(within 24 h of admission to the ICU),presence of braking,mode of establishment of mechanical ventilation,presence of nutritional therapy,number of sedative or analgesic drugs used,whether vasoactive drugs were used,whether diuretics were used,and the level of hemoglobin,blood urea nitrogen and blood creatinine within 24 h after admission to ICU the difference is statistically significant(P＜0.05).The results of multifactorial logistic regression analysis showed that preoperative physiology scores included in the physiology and surgical severity scoring system,the presence of cardiac disease,the presence of braking,the presence of nutritional therapy,and the number of sedative or analgesic medications used were the predictors of the occurrence of ICU-AW in elderly patients undergoing third-and fourth-degree surgeries(OR were 1.364,2.344,5.568,5.823,1.109,all P＜0.05).The above 5 factors were plotted as independent variables in a column-line graph,and the area under the ROC curve of the model was 0.859(95％CI 0.793～0.924),with an optimal critical value of 0.156,a sensitivity of 0.875,a specificity of 0.705,and a Hosmer-Lemeshow goodness-of-fit test of x2=3.906,P=0.865,Brier score of 0.109,and a decision analysis curve indicating that patients could benefit.Conclusion The predictive effect of the constructed model is good,and it can be used as a reference for early and rapid identification of the risk of ICU-AW in elderly patients undergoing third-and fourth-degree surgeries by clinical staff,and timely provision of preventive intervention programs.

Objective:To carry out high-risk foot examination and grading combined with two examination methods for inpatients with type 2 diabetes, and explore the influencing factors of the occurrence and development of high-risk foot, and investigate their foot care behavior status.Methods:From July 2021 to January 2022, 409 patients with diabetes who were admitted to the Department of Endocrinology, Department of Geriatrics, Department of Cardiology, Urology Surgery and Department of Ophthalmology of Xuanwu Hospital of Capital Medical University were selected as research subjects by convenience sampling. The General Information Questionnaire, Standardized Process of At-risk Foot Screening and Stratification for Diabetic Patients, InIow's Screening for the High-Risk Diabetic Foot: A 60-Second Tool, and Foot Care Behavior Questionnaire for Diabetic Patients. Single factor analysis and Logistic regression analysis were used to explore the factors influencing the occurrence and development of high-risk foot in type 2 diabetes patients. A total of 409 questionnaires were distributed, and 392 valid questionnaires were collected, with an effective response rate of 95.8% (392/409) .Results:Among 392 patients, the detection rate of high-risk diabetic foot (HRDF) was 76.3% (299/392), and the proportion of high-risk foot grade 2 was the largest (193). Age ( OR=1.042, P<0.01) and years of hypertension ( OR=1.030, P<0.05) were independent influencing factors for the occurrence of HRDF, with statistically significant differences. Taking the high risk foot grade 3 as a reference, cerebrovascular disease [ OR=16.408, 95% CI (1.323, 203.417) ], diabetes course [ OR=1.066, 95% CI (1.008, 1.128) ], education level in middle school [ OR=0.180, 95% CI (0.056, 0.581) ], education level in primary school and below [ OR=0.126, 95% CI (0.019, 0.841) ] were independent influencing factors for the progress of high risk foot. The foot care behavior of high-risk foot patients with high risk levels was not superior to that of patients with low risk levels. Conclusions:The combination of the two screening methods can meet the examination needs of clinical and nursing medical staff for inpatients with type 2 diabetes. Emphasizing the influencing factors of HRDF occurrence and development can provide reference for early identification of high-risk foot.