The Effects of Home-based Physical Activity Telemonitoring Program in Patients With Heart Failure and Muscle Wasting
NCT ID: NCT05588375
Last Updated: 2022-10-20
Study Results
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Basic Information
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UNKNOWN
NA
118 participants
INTERVENTIONAL
2022-04-21
2023-02-28
Brief Summary
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Objective: The purpose of this study is to evaluate the effect of a multi-component physical activity program based on home telemonitoring on patients with heart failure and muscle wasting. Methods: This study used an quasi-experimental study, two-group repeated measurement design. The experimental group received the Home-based exercise with telemonitoring and control group according to regular nursing care. Data were collected at baseline (T0), and post-tests will be conducted right after the intervention period (T1). Additionally, detraining effects will be measured 12 weeks after program cessation (T2) . Data were collected including demographic questionnaire, sarcopenia, cachexia assessment, clinical blood parameters from patient record, physical activity, loneliness, and quality of life.
Scientific or Clinical Implication of the Expected Results: The study results can be used to design designated interventions and provide information for policymaking.
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Detailed Description
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In this study, G power 3.1.9.7 software was used, and ANOVA: Repeated measures, between factors was selected to calculate the sample size, and the G power program (Faul et al., 2007) was used to estimate the appropriate sample size, according to previous group and family exercise programs. Results of a study of outcomes in patients with sarcopenia (Tsekoura et al., 2017), each group required 28 participants to measure grip strength between the intervention and control groups (SD = 4.2), equivalent to an effect size of 0.316, significant level α=0.05, test force β=0.95. The estimated potential attrition rate is 30%, and 118 cases are expected to be accepted, requiring 59 subjects per
Method of recruitment:
Patients with mild to moderate and stable systolic heart failure who met the NYHA first-to-third definition of the New York Heart Association were first screened from the medical records, and the outpatient physicians or nurses introduced this study to potential subjects during routine return visits. After obtaining their consent, the researchers contacted them again, and after obtaining consent, they reviewed their medical records to recruit research subjects. After reviewing the acceptance and exclusion conditions, the research purpose and explanation were carried out. After the participants agreed, the study list was included in the study. on the roster for receipt.
4.How subjects consented: The outpatient physician or nurse practitioner will introduce the study to potential subjects, and after obtaining their consent, the researcher will review the medical records and then recruit the subjects, explain the research purpose and research process, inform the participants of their rights, and the subjects who are willing to participate are invited to fill in the research consent form before closing the case.
Treatment effect evaluation and statistical analysis methods:
The questionnaire data collected in this study were first coded and typed into the computer. After the data was checked, the data was analyzed with SPSS for Windows version 24.0, and α=.05 was used as the test for statistical significance. The data analysis methods were as follows:
1. Descriptive statistics Describe basic individual attributes in percentage, mean, standard deviation, such as gender, age, religion, education, marital status, past medical history, primary caregiver, health status, sarcopenia-related measures (calf circumference, grip strength, muscle mass, 5 times of standing up and sitting down and 6 meters walking speed) and clinical blood biochemical test values, etc., as well as the scores of physical activity, loneliness and quality of life.
2. Inferential statistics Including: group difference test: (a) Chi-square test (Chi-Squire test) to test the homogeneity of category data between the control group and the intervention group. (b) Use an independent t test to test the difference in the pretest time of the continuous variable between the control group and the intervention group? Influencing factors: (a) Independent t test (independent t test) was used for the two groups with significant differences in sociodemographic characteristics, and the cases belonged to two-category variables (gender, presence or absence of other comorbidities). ) to determine whether there is a significant difference in its relationship with blood biochemical test values, physical activity, loneliness, and quality of life. (b) One-way analysis of variance:One-way ANOVA is aimed at the two groups with significant differences in sociodemographic characteristics, and the cases belong to multi-category variables (age, education level, marriage, caregiver, occupation, health status, muscle If the F value reaches a statistically significant difference, the Sheffe test is used to analyze the differences between groups to determine whether it is related to the blood biochemical Whether there are significant differences in the relationship between test values, physical activity, loneliness, and quality of life. (c) Pearson's product moment correlation coefficients to analyze the correlation between sociodemographic characteristics and variables of blood biochemical test values, physical activity, loneliness and quality of life. Effectiveness evaluation: (a) Paired-t test was used to detect within-group nursing effectiveness indicators (measurement of sarcopenia severity and cachexia severity, blood biochemical test values, health status, physical activity, loneliness and life Quality) is there any difference between the pre-test and post-test (b)Generalized estimated equation is used to put the variables with significant differences or correlations between sociodemographic and each outcome index into the model to correct the interference on the pre-test Factors to examine the differences between the experimental group and the control group in changes in sarcopenia severity and cachexia severity, physical activity, loneliness, and quality of life outcomes.
(e) Questionnaires or other research-related materials:
(1) Basic data: Demographic data includes health status data, such as age, gender, occupation, income, education level, marital status, etc., which are filled in by the participants themselves; and the health status data, which is checked by the researchers from the medical records. Height, weight, number of heartbeats, systolic and diastolic blood pressure (mmHg), body mass index (BMI), medications and their quantities, surgical history, and other comorbidities within the last three months , The reason for the most recent admission, the reason for the most recent emergency, the reason for the most recent visit, the fatigue state and nutritional status, (Mini Nutritional Assessment Short-Form, MNA-SF) and other related data evaluation.
Conditions
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Study Design
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NON_RANDOMIZED
PARALLEL
PREVENTION
SINGLE
Study Groups
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home-based physical activity telemonitoring program
The home telehealth physical activity training program is a telemedicine physical activity training that uses Google Meet software to communicate and supervise through webcams. The exercise process is supervised and guided by a trained critical care nurse. The experimental group participated in a telehealth physical activity training program. The telemedicine physical activity training program included a 3-month online intervention (exercise diary, exercise training education, and 24 exercise sessions for patients) and a 3-month follow-up after exercise.
home-based physical activity telemonitoring program
The home telehealth physical activity training program is a telemedicine physical activity training that uses Google Meet software to communicate and supervise through webcams.
walk 2-3 days a week
Maintain daily physical activity and lifestyle and walk for 30 minutes 2-3 days a week for three months
home-based physical activity telemonitoring program
The home telehealth physical activity training program is a telemedicine physical activity training that uses Google Meet software to communicate and supervise through webcams.
Interventions
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home-based physical activity telemonitoring program
The home telehealth physical activity training program is a telemedicine physical activity training that uses Google Meet software to communicate and supervise through webcams.
Eligibility Criteria
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Inclusion Criteria
2. Resting left ventricular ejection fraction (LVEF) ≤ 50%;
3. Over 20 years old;
4. Be able to communicate in Chinese and Taiwanese and participate in the research voluntarily;
5. cases consistent with sarcopenia, cachexia, or both.
Exclusion Criteria
2. Patients with tumors;
3. Signs of acute infection two months ago;
4. Severe knee or back pain;
5. Severely impaired mobility;
6. Engaged in exercise training within the past 3 months;
7. Hospitalization for CHF or change in CHF therapy within 1 month, unstable angina, fixed cardiac pacemaker;
8. Inability to use a smartphone (including those without internet access or unable to operate communication software such as Line and Google Meet).
20 Years
99 Years
ALL
No
Sponsors
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Far Eastern Memorial Hospital
OTHER
Responsible Party
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Principal Investigators
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Heng-Hsin Tung
Role: STUDY_CHAIR
School of Nursing, National Yang Ming Chiao Tung University
Locations
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Far Eastern Memorial Hospital
Taipei, , Taiwan
Countries
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Central Contacts
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Facility Contacts
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References
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Crespo-Leiro MG, Anker SD, Maggioni AP, Coats AJ, Filippatos G, Ruschitzka F, Ferrari R, Piepoli MF, Delgado Jimenez JF, Metra M, Fonseca C, Hradec J, Amir O, Logeart D, Dahlstrom U, Merkely B, Drozdz J, Goncalvesova E, Hassanein M, Chioncel O, Lainscak M, Seferovic PM, Tousoulis D, Kavoliuniene A, Fruhwald F, Fazlibegovic E, Temizhan A, Gatzov P, Erglis A, Laroche C, Mebazaa A; Heart Failure Association (HFA) of the European Society of Cardiology (ESC). European Society of Cardiology Heart Failure Long-Term Registry (ESC-HF-LT): 1-year follow-up outcomes and differences across regions. Eur J Heart Fail. 2016 Jun;18(6):613-25. doi: 10.1002/ejhf.566.
Hao G, Wang X, Chen Z, Zhang L, Zhang Y, Wei B, Zheng C, Kang Y, Jiang L, Zhu Z, Zhang J, Wang Z, Gao R; China Hypertension Survey Investigators. Prevalence of heart failure and left ventricular dysfunction in China: the China Hypertension Survey, 2012-2015. Eur J Heart Fail. 2019 Nov;21(11):1329-1337. doi: 10.1002/ejhf.1629.
Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, Falk V, Gonzalez-Juanatey JR, Harjola VP, Jankowska EA, Jessup M, Linde C, Nihoyannopoulos P, Parissis JT, Pieske B, Riley JP, Rosano GM, Ruilope LM, Ruschitzka F, Rutten FH, van der Meer P; Authors/Task Force Members; Document Reviewers. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail. 2016 Aug;18(8):891-975. doi: 10.1002/ejhf.592. Epub 2016 May 20. No abstract available.
Tsekoura M, Kastrinis A, Katsoulaki M, Billis E, Gliatis J. Sarcopenia and Its Impact on Quality of Life. Adv Exp Med Biol. 2017;987:213-218. doi: 10.1007/978-3-319-57379-3_19.
Martone AM, Bianchi L, Abete P, Bellelli G, Bo M, Cherubini A, Corica F, Di Bari M, Maggio M, Manca GM, Marzetti E, Rizzo MR, Rossi A, Volpato S, Landi F. The incidence of sarcopenia among hospitalized older patients: results from the Glisten study. J Cachexia Sarcopenia Muscle. 2017 Dec;8(6):907-914. doi: 10.1002/jcsm.12224. Epub 2017 Sep 14.
Platz E, Jhund PS, Claggett BL, Pfeffer MA, Swedberg K, Granger CB, Yusuf S, Solomon SD, McMurray JJ. Prevalence and prognostic importance of precipitating factors leading to heart failure hospitalization: recurrent hospitalizations and mortality. Eur J Heart Fail. 2018 Feb;20(2):295-303. doi: 10.1002/ejhf.901. Epub 2017 Sep 4.
von Haehling S. Muscle wasting and sarcopenia in heart failure: a brief overview of the current literature. ESC Heart Fail. 2018 Dec;5(6):1074-1082. doi: 10.1002/ehf2.12388. No abstract available.
Scherbakov N, Doehner W. Cachexia as a common characteristic in multiple chronic disease. J Cachexia Sarcopenia Muscle. 2018 Dec;9(7):1189-1191. doi: 10.1002/jcsm.12388. Epub 2019 Jan 13. No abstract available.
Lena A, Anker MS, Springer J. Muscle Wasting and Sarcopenia in Heart Failure-The Current State of Science. Int J Mol Sci. 2020 Sep 8;21(18):6549. doi: 10.3390/ijms21186549.
Valentova M, Anker SD, von Haehling S. Cardiac Cachexia Revisited: The Role of Wasting in Heart Failure. Heart Fail Clin. 2020 Jan;16(1):61-69. doi: 10.1016/j.hfc.2019.08.006.
Vest AR, Chan M, Deswal A, Givertz MM, Lekavich C, Lennie T, Litwin SE, Parsly L, Rodgers JE, Rich MW, Schulze PC, Slader A, Desai A. Nutrition, Obesity, and Cachexia in Patients With Heart Failure: A Consensus Statement from the Heart Failure Society of America Scientific Statements Committee. J Card Fail. 2019 May;25(5):380-400. doi: 10.1016/j.cardfail.2019.03.007. Epub 2019 Mar 13.
Other Identifiers
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110236-E
Identifier Type: -
Identifier Source: org_study_id
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