The Effects of Intelligent Intervention Programs on Hospitalized Elderly People With Frailty.

Background:

Frailty is an aging-related syndrome with a prevalence that increases with age. However, frailty should not be considered a natural part of aging; rather, it involves multiple factors such as dependency, dynamic processes, and vulnerability . Hospitalized elderly individuals often suffer from chronic diseases and are in a stage of aging with declining physical function. During acute illness, they experience physical weakness and disease burden, which, combined with the stress and physical strain of hospitalization, prolonged bed rest, and reduced activity levels, makes them more susceptible to frailty. According to domestic research, the prevalence of frailty among hospitalized elderly patients in Taiwan is as high as 88.7% .

Frailty is significantly associated with advanced age, female gender, body mass index, comorbidities, activities of daily living (ADL), and poor nutritional status. Among patients with kidney disease, frailty-related risk factors such as fatigue, reduced activity, and decreased albumin levels are more common. Studies indicate that the prevalence of frailty among patients with kidney disease reaches 75.3%. Additionally, compared to non-frail patients with kidney disease, frail patients with kidney disease have a 2.75-fold increased risk of mortality, a 3.79-fold higher risk of discharge to long-term care facilities, an extended hospitalization duration of 4.87 days, and an increased hospital cost of $41,025.03. These findings suggest that frailty significantly increases the risk of adverse health outcomes in patients with kidney disease .

Current research indicates that frailty is reversible. A large-scale study in Europe found that early intervention during the pre-frailty or mild frailty stage is far more effective than intervention at later stages. In recent years, studies have explored multimodal interventions to mitigate frailty in hospitalized elderly patients. However, the number of randomized controlled trials remains limited, and existing studies are of low quality, with inconsistent intervention strategies and outcomes.

Furthermore, most interventional studies have been based on comprehensive geriatric assessment (CGA) and employed the Acute Care for Elderly (ACE) model, requiring interdisciplinary coordination and integration across multiple specialties . However, the organizational requirements for CGA and ACE models are substantial, making it difficult for clinical settings lacking the necessary infrastructure to implement these interventions effectively.

Therefore, this study aims to conduct a prospective investigation and develop interventional strategies to prevent and manage frailty among hospitalized elderly patients with kidney disease.

Purpose:

1. Develop an intelligent intervention program for frailty. 2. Evaluate the effectiveness of the intelligent frailty intervention program in reducing frailty levels among hospitalized elderly patients with kidney disease before discharge. 3. Assess the impact of the intelligent frailty intervention program on the daily functional abilities of hospitalized elderly patients with kidney disease. 4. Examine the effect of the intelligent frailty intervention program on the 30-day unplanned readmission rate of hospitalized elderly patients with kidney disease.

Subjects:

1. Inclusion criteria: (1) Hospitalized patients aged 65 years and older.(2) Admitted to the nephrology department or undergoing dialysis.(3) Conscious, able to express themselves independently, follow instructions, and communicate in Mandarin or Taiwanese.(4) Expected hospital stay of at least six days.(5) Assessed using the Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) and deemed to have no immediate risk for exercise participation, with normal capability for physical activity. 2. Exclusion criteria: (1) Severe visual or hearing impairments that hinder communication or assessments.(2) Significant cognitive impairment, defined as a Montreal Cognitive Assessment (MoCA) score \< 24.(3) Patients who do not consent to participate in the study.(4) Individuals unable to personally complete the consent form.(5) Patients receiving palliative care.(6) Regular participants in rehabilitation therapy.(7) Charlson Comorbidity Index (CCI) score ≥ 5. 3. Number of subjects: 78 in the experimental group and 78 in the control group 4. Recruitment method: (1) Recruitment location: A medical ward in a regional teaching hospital in northern Taiwan. (2) Recruitment through: Participants will be referred by physicians.

Research design:

1. Study design or implementation This study is a randomized clinical trial (RCT) investigating the effectiveness of an intelligent intervention program on frailty levels, daily living functions, and unexpected readmission rates among hospitalized elderly patients with kidney disease. The study adopts a double-blind, parallel-group randomized design. Eligible participants will be recruited through convenience sampling and subsequently assigned to two groups using block randomization. The experimental group will receive the intelligent intervention program, while the control group will receive standard care. The intervention involves a structured exercise program, with participants in the experimental group engaging in cycling exercises three times per week, each session lasting 30 minutes during hospitalization. After discharge, they will follow a walking program, increasing their daily step count by 1,000 steps above the average recorded during hospitalization, for a total of 12 weeks. Participant in the control group will wear a smart wristband but will only receive standard care. Structured questionnaires and medical records will be used for data collection at four time points: the first week of enrollment (T0), hospital discharge (T1), the eighth week post-enrollment (T2), and the twelfth week post-enrollment (T3). Additionally, a tri-axial accelerometer-equipped smart wristband will be used to monitor and record participants' heart rate, respiration, blood pressure, daily step count, and sleep quality. 2. Project duration and expected progress

(1) This study was conducted after IRB and RCT were approved until 12/31/2025 (2) The case will be accepted after approval by both IRB and RCT. (3) Conduct data analysis and statistics after receiving the case 3. Statistical methods and results evaluation

1. Descriptive data analysis

①. Frequency distribution and percentages will be used to describe demographic variables, disease characteristics, and frailty, including age, gender, education level, marital status, economic status, body mass index (BMI), medication history, fall history, reason for hospitalization, types of chronic diseases, dialysis status, comorbidities, and frailty status.

②. Continuous variables, including physical function, nutritional status, cognitive function, depression index, frailty level, daily step count, and daily activity level, will be described using mean, standard deviation, minimum, maximum, and range. 2. Inferential Data Analysis To examine factors associated with the study participants, independent sample t-tests and one-way analysis of variance (ANOVA) will be used to analyze the relationships between basic characteristics, disease attributes, and frailty levels. Pearson's correlation will be used to explore the relationships between physical function, nutritional status, cognitive function, depression index, and frailty level. Logistic regression analysis will be conducted to identify predictors of frailty among hospitalized elderly patients. For evaluating the effectiveness of the intervention, independent sample t-tests and chi-square tests will be used to assess the homogeneity of demographic variables, disease characteristics, frailty, physical function, nutritional status, cognitive function, depression index, frailty level, daily step count, and daily activity level between the two groups. Repeated measures ANOVA and binary logistic regression analysis will be applied to assess between-group differences in the intervention group. Generalized estimating equations (GEE) will be used to analyze the differences in intervention effectiveness between the two groups, as well as the interaction effects between group and time.

• 15-item geriatric depression scale(GDS-15) [Срок оценки: pre-intervention, baseline (T0)]
• 15-item geriatric depression scale(GDS-15) [Срок оценки: 4 weeks after intervention, discharge(T1)]
• 15-item geriatric depression scale(GDS-15) [Срок оценки: 8 Weeks after intervention(T2)]
• 15-item geriatric depression scale(GDS-15) [Срок оценки: 12 Weeks after intervention(T3)]
• the Chinese version of the Pittsburgh Sleep Quality Index(CPSQI) [Срок оценки: pre-intervention, baseline (T0)]
• the Chinese version of the Pittsburgh Sleep Quality Index(CPSQI) [Срок оценки: 4 weeks after intervention, discharge(T1)]
• the Chinese version of the Pittsburgh Sleep Quality Index(CPSQI) [Срок оценки: 8 Weeks after intervention(T2)]
• the Chinese version of the Pittsburgh Sleep Quality Index(CPSQI) [Срок оценки: 12 Weeks after intervention(T3)]
• Objective Sleep Quality [Срок оценки: pre-intervention, baseline (T0)]
• Objective Sleep Quality [Срок оценки: 4 weeks after intervention, discharge(T1)]
• Objective Sleep Quality [Срок оценки: 8 Weeks after intervention(T2)]
• Objective Sleep Quality [Срок оценки: 12 Weeks after intervention(T3)]