The Effects of Intelligent Intervention Programs on Hospitalized Elderly People With Frailty.
NCT ID: NCT06875024
Last Updated: 2025-04-03
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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Recruitment Status
NOT_YET_RECRUITING
Clinical Phase
NA
Total Enrollment
156 participants
Study Classification
INTERVENTIONAL
Study Start Date
2025-04-15
Study Completion Date
2026-12-31
Brief Summary
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Background: As the aging population grows, hospitalized elderly individuals with frailty have become a major concern. Frailty is a complex syndrome linked to aging, marked by dependency and vulnerability. Elderly patients often face chronic diseases, making them more susceptible to frailty. Studies show frailty prevalence in hospitalized elderly patients is 88.7%, and 75.3% among kidney disease patients. Frailty is associated with advanced age, female gender, low body mass index, comorbidities, and poor nutrition, increasing the risks of falls, hospitalization, and mortality. Frail kidney disease patients face worse outcomes. However, frailty is reversible with early intervention. Current treatments, based on comprehensive geriatric assessment (CGA), require significant resources. This study aims to explore frailty prevention and care through research and intervention development.
Purpose: To explore the effectiveness of an intelligent intervention program in improving frailty among hospitalized elderly individuals.
Methods: An experimental research design was adopted. A total of 156 hospitalized elderly patients with kidney disease who met the inclusion criteria were recruited through convenience sampling. Participants were randomly assigned to either the experimental group (n = 78) or the control group (n = 78). The experimental group received a 12-week intelligent intervention program, while the control group received routine care.Subsequently, data on frailty level, daily living function 30 days after discharge, and unexpected readmission rate 30 days after discharge will be collected by researchers and analyzed using SPSS 22.0, including chi-square tests, repeated measures ANOVA, and Generalized Estimating Equations (GEE) for intra-group and inter-group comparisons of each outcome variable.
Expected research results: This study aims to understand the current status and influencing factors of frailty among hospitalized elderly patients with kidney disease and to develop an intelligent intervention program. The goal is to provide clinical nursing staff with a frailty care strategy for hospitalized patients, effectively reducing frailty among elderly inpatients, improving their daily functional ability after discharge, and decreasing hospital readmission rates.
Condition or disease: frailty Intervention/treatment: intelligent intervention program
Purpose: To explore the effectiveness of an intelligent intervention program in improving frailty among hospitalized elderly individuals.
Methods: An experimental research design was adopted. A total of 156 hospitalized elderly patients with kidney disease who met the inclusion criteria were recruited through convenience sampling. Participants were randomly assigned to either the experimental group (n = 78) or the control group (n = 78). The experimental group received a 12-week intelligent intervention program, while the control group received routine care.Subsequently, data on frailty level, daily living function 30 days after discharge, and unexpected readmission rate 30 days after discharge will be collected by researchers and analyzed using SPSS 22.0, including chi-square tests, repeated measures ANOVA, and Generalized Estimating Equations (GEE) for intra-group and inter-group comparisons of each outcome variable.
Expected research results: This study aims to understand the current status and influencing factors of frailty among hospitalized elderly patients with kidney disease and to develop an intelligent intervention program. The goal is to provide clinical nursing staff with a frailty care strategy for hospitalized patients, effectively reducing frailty among elderly inpatients, improving their daily functional ability after discharge, and decreasing hospital readmission rates.
Condition or disease: frailty Intervention/treatment: intelligent intervention program
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Detailed Description
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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.
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.
Conditions
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Frailty in Older Adults
Study Design
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Allocation Method
RANDOMIZED
Intervention Model
PARALLEL
Primary Study Purpose
HEALTH_SERVICES_RESEARCH
Blinding Strategy
DOUBLE
Participants
Outcome Assessors
Study Groups
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Control group
The control group received usual care.
Group Type
NO_INTERVENTION
No interventions assigned to this group
Experimental group
The experimental group will receive an intelligent intervention program, which includes cycling training during hospitalization and daily walking training after discharge, supplemented by monitoring and tracking using a smart wristband.
Group Type
EXPERIMENTAL
Intelligent intervention programs
Intervention Type
BEHAVIORAL
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. 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.
Interventions
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Intelligent intervention programs
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. 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.
Intervention Type
BEHAVIORAL
Eligibility Criteria
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Inclusion Criteria
* Hospitalized patients aged 65 years and older. (、
* Admitted to the nephrology department or undergoing dialysis.
* Conscious, able to express themselves independently, follow instructions, and communicate in Mandarin or Taiwanese.
* Expected hospital stay of at least six days.
* 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.
* Admitted to the nephrology department or undergoing dialysis.
* Conscious, able to express themselves independently, follow instructions, and communicate in Mandarin or Taiwanese.
* Expected hospital stay of at least six days.
* 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.
Exclusion Criteria
* Severe visual or hearing impairments that hinder communication or assessments.
* Significant cognitive impairment, defined as a Montreal Cognitive Assessment (MoCA) score \< 24.
* Patients who do not consent to participate in the study.
* Individuals unable to personally complete the consent form.
* Patients receiving palliative care.
* Regular participants in rehabilitation therapy.
* Charlson Comorbidity Index (CCI) score ≥ 5.
* Significant cognitive impairment, defined as a Montreal Cognitive Assessment (MoCA) score \< 24.
* Patients who do not consent to participate in the study.
* Individuals unable to personally complete the consent form.
* Patients receiving palliative care.
* Regular participants in rehabilitation therapy.
* Charlson Comorbidity Index (CCI) score ≥ 5.
Minimum Eligible Age
65 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
No
Sponsors
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National Taipei University of Nursing and Health Sciences
OTHER
Sponsor Role
lead
Responsible Party
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Chia Jung Hsieh
professor
Responsibility Role
PRINCIPAL_INVESTIGATOR
Locations
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National Taipei University of Nursing and Health Sciences, Taipei,
Taipei, , Taiwan
Site Status
Countries
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Taiwan
Central Contacts
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Facility Contacts
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References
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Zotcheva E, Haberg AK, Wisloff U, Salvesen O, Selbaek G, Stensvold D, Ernstsen L. Effects of 5 Years Aerobic Exercise on Cognition in Older Adults: The Generation 100 Study: A Randomized Controlled Trial. Sports Med. 2022 Jul;52(7):1689-1699. doi: 10.1007/s40279-021-01608-5. Epub 2021 Dec 8.
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Yeh AY, Pressler SJ, Algase D, Struble LM, Pozehl BJ, Berger AM, Giordani BJ. Sleep-Wake Disturbances and Episodic Memory in Older Adults. Biol Res Nurs. 2021 Apr;23(2):141-150. doi: 10.1177/1099800420941601. Epub 2020 Jul 10.
Reference Type
BACKGROUND
Wilkinson TJ, Miksza J, Zaccardi F, Lawson C, Nixon AC, Young HML, Khunti K, Smith AC. Associations between frailty trajectories and cardiovascular, renal, and mortality outcomes in chronic kidney disease. J Cachexia Sarcopenia Muscle. 2022 Oct;13(5):2426-2435. doi: 10.1002/jcsm.13047. Epub 2022 Jul 19.
Reference Type
BACKGROUND
Wei YC, Chen CK, Lin C, Chen PY, Hsu PC, Lin CP, Shyu YC, Huang WY. Normative Data of Mini-Mental State Examination, Montreal Cognitive Assessment, and Alzheimer's Disease Assessment Scale-Cognitive Subscale of Community-Dwelling Older Adults in Taiwan. Dement Geriatr Cogn Disord. 2022;51(4):365-376. doi: 10.1159/000525615. Epub 2022 Jul 12.
Reference Type
BACKGROUND
Pan, A. N., Lin, V. L., Hsu, P. C. & Chen, H. C.(2022) The Associations of Subjective and Objective Sleep Quality and Mood Symptoms among Patients with Bipolar Disorder: A Longitudinal Study. The Journal of Psychiatric Mental Health Nursing, 17(3), 26-36. https://doi-org.mhdla.flysheet.com.tw:8443/10.6847/TJPMHN.202212_17(3).04
Reference Type
BACKGROUND
Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, Cummings JL, Chertkow H. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005 Apr;53(4):695-9. doi: 10.1111/j.1532-5415.2005.53221.x.
Reference Type
BACKGROUND
Gregg LP, Bossola M, Ostrosky-Frid M, Hedayati SS. Fatigue in CKD: Epidemiology, Pathophysiology, and Treatment. Clin J Am Soc Nephrol. 2021 Sep;16(9):1445-1455. doi: 10.2215/CJN.19891220. Epub 2021 Apr 15.
Reference Type
BACKGROUND
Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-56. doi: 10.1093/gerona/56.3.m146.
Reference Type
BACKGROUND
Ekerstad N, Dahlin Ivanoff S, Landahl S, Ostberg G, Johansson M, Andersson D, Husberg M, Alwin J, Karlson BW. Acute care of severely frail elderly patients in a CGA-unit is associated with less functional decline than conventional acute care. Clin Interv Aging. 2017 Aug 8;12:1239-1249. doi: 10.2147/CIA.S139230. eCollection 2017.
Reference Type
BACKGROUND
Chou, M.-H., Chen, F.-J., Chiu, C.-F., & Lin, Y.-D. (2019). Frailty status and its influencing factors among elderly hospitalized patients. The VGH Nursing, 36(1), 27-38. https://doi.org/10.6142/vghn.201903_36(1).0003
Reference Type
BACKGROUND
Chin, W. C., Liu, C. Y., Lee, C. P., & Chu, C. L. (2014). Validation of Five Short Versions of the Geriatric Depression Scale in the Elder Population in Taiwan. Taiwanese Journal of Psychiatry, 28 (3), 156-163+ii. https://www-airitilibrary-com.mhdla.flysheet.com.tw:8443/Article/Detail?DocID=10283684-201409-201410200065-201410200065-156-163+ii
Reference Type
BACKGROUND
Checa-Lopez M, Costa-Grille A, Alvarez-Bustos A, Carnicero-Carreno JA, Sinclair A, Scuteri A, Landi F, Solano-Jaurrieta JJ, Bellary S, Rodriguez-Manas L. Effectiveness of a randomized intervention by a geriatric team in frail hospital inpatients in non-geriatric settings: FRAILCLINIC project. J Cachexia Sarcopenia Muscle. 2024 Feb;15(1):361-369. doi: 10.1002/jcsm.13374. Epub 2023 Nov 28.
Reference Type
BACKGROUND
Chang, H. Y., Hsieh, Y. W., Hsueh, I. P. & Hsieh, C. L. (2006). A Forty-year Retrospective of Assessment of Activities of Daily Living. Taiwan Journal of Physical Medicine and Rehabilitation,34(2), 63-71. https://doi-org.mhdla.flysheet.com.tw:8443/10.6315/2006.34(2)01
Reference Type
BACKGROUND
Tsai PS, Wang SY, Wang MY, Su CT, Yang TT, Huang CJ, Fang SC. Psychometric evaluation of the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI) in primary insomnia and control subjects. Qual Life Res. 2005 Oct;14(8):1943-52. doi: 10.1007/s11136-005-4346-x.
Reference Type
BACKGROUND
Neborak JM, Press VG, Parker WF, Rojas JC, Byron M, Goyal S, Meltzer DO, Mokhlesi B, Arora VM. Association of preadmission insomnia symptoms with objective in-hospital sleep and clinical outcomes among hospitalized patients. J Clin Sleep Med. 2024 May 1;20(5):681-687. doi: 10.5664/jcsm.10964.
Reference Type
BACKGROUND
Jiang X, Li D, Shen W, Shen X, Liu Y. In-Hospital Outcomes of Patients on Maintenance Dialysis With Frailty: 10-year Results From the US National Inpatient Sample Database. J Ren Nutr. 2020 Nov;30(6):526-534. doi: 10.1053/j.jrn.2019.12.007. Epub 2020 Feb 13.
Reference Type
BACKGROUND
Jarach CM, Tettamanti M, Nobili A, D'avanzo B. Social isolation and loneliness as related to progression and reversion of frailty in the Survey of Health Aging Retirement in Europe (SHARE). Age Ageing. 2021 Jan 8;50(1):258-262. doi: 10.1093/ageing/afaa168.
Reference Type
BACKGROUND
Jaiswal SJ, Kang DY, Wineinger NE, Owens RL. Objectively measured sleep fragmentation is associated with incident delirium in older hospitalized patients: Analysis of data collected from an randomized controlled trial. J Sleep Res. 2021 Jun;30(3):e13205. doi: 10.1111/jsr.13205. Epub 2020 Oct 13.
Reference Type
BACKGROUND
Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989 May;28(2):193-213. doi: 10.1016/0165-1781(89)90047-4.
Reference Type
BACKGROUND
Other Identifiers
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CJHsieh
Identifier Type: -
Identifier Source: org_study_id
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Frailty Prevention Program to Prevent Frailty Among Older African Americans
NCT03585972
COMPLETED
NA
Geriatric Trauma Care Program for Living Alone Older Adults With Injuries
NCT06902636
RECRUITING
NA
Geriatric Education and Its Effect on Certain Aspects of Hospital Care of the Nursing Home Patients - 12 Month Retrospective Study
NCT01213225
COMPLETED
The Effects of a Tele-health Program
NCT05267444
COMPLETED
NA
Successful Aging and Frailty
NCT03963050
UNKNOWN
NA
Comprehensive Geriatric Assessment in the Elderly Subjects (PROMISING)
NCT05822154
UNKNOWN
Multifactorial Intervention on Frailty in Vulnerable Older Adults
NCT02554994
COMPLETED
NA
Geriatric Hip Fractures Caregiver Programme
NCT05393349
UNKNOWN
NA
Comprehensive Validation of Frailty Assessment Tools in Older Adults in Different Clinical and Social Settings
NCT02637518
UNKNOWN
Trajectory of Frailty and Cognitive Dysfunction in Older Adults
NCT06276166
NOT_YET_RECRUITING