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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05588375
Other study ID # 110236-E
Secondary ID
Status Recruiting
Phase N/A
First received
Last updated
Start date April 21, 2022
Est. completion date February 28, 2023

Study information

Verified date April 2022
Source Far Eastern Memorial Hospital
Contact Shu-Wen Chang
Phone 886277282152
Email irb@mail.femh.org.tw
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

Introduction: Muscle wasting is a serious complication that affects a large proportion of patients with heart failure (HF). Muscle wasting is a strong predictor of frailty and reduced survival in HF patients. Currently, standard treatments for slowing muscle loss in patients with HF are not available. The main intervention remains various types of physical activity programs. Telemonitoring is a promising strategy for improving heart failure outcomes by making it possible to monitor patients remotely. There are numerous examples of home-based exercise programs administered through telehealth services that have been beneficial for maintaining physical activity levels. These results highlight the potential utility of telehealth services for combatting sedentarism and muscle wasting among epidemic and post-epidemic phases. 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.


Description:

This study adopts an quasi-experimental study, two-group repeated-measures research design, purposive sampling, and after baseline assessment. Both the experimental group and the control group were patients included in the case management of heart failure in the hospital. The experimental group received 59 cases who participated in remote home sports, and the control group received 59 cases who received routine care for heart failure case management. 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.


Recruitment information / eligibility

Status Recruiting
Enrollment 118
Est. completion date February 28, 2023
Est. primary completion date February 28, 2023
Accepts healthy volunteers No
Gender All
Age group 20 Years to 99 Years
Eligibility Inclusion Criteria: 1. Patients with mild to moderate and stable systolic heart failure as defined by the New York Heart Association NYHA Class I to III; 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: 1. Cognitive dysfunction or psychiatric disturbance (based on medical records); 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).

Study Design


Related Conditions & MeSH terms


Intervention

Behavioral:
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.

Locations

Country Name City State
Taiwan Far Eastern Memorial Hospital Taipei city

Sponsors (1)

Lead Sponsor Collaborator
Far Eastern Memorial Hospital

Country where clinical trial is conducted

Taiwan, 

References & Publications (11)

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, Dahlström 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. Erratum in: Eur J Heart Fail. 2017 Mar;19(3):438. — View Citation

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. Erratum in: Eur J Heart Fail. 2020 Apr;22(4):759. — View Citation

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). pii: E6549. doi: 10.3390/ijms21186549. Review. — View Citation

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. — View Citation

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. — View Citation

Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, Falk V, González-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. — View Citation

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. — View Citation

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. Review. — View Citation

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. Review. — View Citation

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. — View Citation

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. — View Citation

* Note: There are 11 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Change from baseline in hand grip at week 12 and week 24 Measured with a Jamar Hydraulic Hand Dynamometer(kg). This hand dynamometer is ideal for routine screening of grip strength and hand function. This hand strength test also features a dual-scale readout displaying isometric grip force from 0 - 90kg.(M<28kg; Female<18kg for low grip strength) Change =(Week 12 score-baseline score; week 24 score-baseline score) baseline and week 12 and week 24
Primary Change from baseline in The five-repetition sit-to-stand test at week 12 and week 24 The score is the amount of time (to the nearest decimal in seconds) it takes a patient to transfer from a seated to a standing position and back to sitting five times.
Change =(Week 12 score-baseline score; week 24 score-baseline score)
baseline and week 12 and week 24
Primary Change from baseline in six-meter walking speed test at week 12 and week 24 In order to obtain accurate data, an acceleration zone and a deceleration zone of 1.5 m. Measure the time it takes the patient to actually walk six meters. The score is the amount of time (to the nearest decimal in seconds)meters are given before and after the measurement zone.
Change =(Week 12 score-baseline score; week 24 score-baseline score)
baseline and week 12 and week 24
Primary Change from baseline in Skeletal muscle mass index (SMI) at week 12 and week 24 The SMI was calculated by dividing the limb skeletal muscle mass (kg) by the square of the height (m 2). Determined by bioelectrical impedance analysis ( for males with SMI <7.0 kg/m2 and females with SMI <5.7 kg/m2).
Change =(Week 12 score-baseline score; week 24 score-baseline score)
baseline and week 12 and week 24
Secondary Change from baseline in the international physical activity questionnaire - short form; IPAQ-SF at week 12 and week 24 The IPAQ-SF asks about three specific types of activity undertaken in the three domains introduced above and sitting. The specific types of activity that are assessed are walking, moderate-intensity activities, and vigorous-intensity activities; frequency (measured in days per week) and duration (time per day) are collected separately for each specific type of activity.
Measure of volume of activity can be computed by weighting each type of activity by its energy requirements defined in METS (METs are multiples of the resting metabolic rate) to yield a score in METñminutes. A MET-minute is computed by multiplying the MET score by the minutes performed. Walking = 3.3 METs, Moderate PA = 4.0 METs and Vigorous PA = 8.0 METs
Low-intensity physical activity: < 599 MET-min/week)
Moderate-intensity physical activity: 600 Met-min/week.
High-intensity physical activity: >3000 Met-min/week
baseline and week 12 and week 24
Secondary Change from baseline in (Mini Nutritional Assessment-Short Form;MNA-SF) at week 12 and week 24 Nutrition(Mini Nutritional Assessment-Short Form; MNA-SF):
(1)12 to 14 points: Well-nourished (2)8 to 11 points: Potentially malnourished (3) 0 to 7 points: Malnourished Change =(Week 12 score-baseline score; week 24 score-baseline score)
baseline and week 12 and week 24
Secondary Change from baseline in loneliness(3-item loneliness scales) at week 12 and week 24 loneliness(3-item loneliness scales) : The total score is 3 to 9 points, and a score of 6 or more is judged to be lonely.
Change =(Week 12 score-baseline score; week 24 score-baseline score)
baseline and week 12 and week 24
Secondary Change from baseline in (The 5-level EQ-5D version ;EQ-5D-5L) at week 12 and week 24 (The 5-level EQ-5D version; EQ-5D-5L): A single EQ-5D score (EQ-index) was obtained by weighting the population standard reference values established by the time trade-off (TTO). In this study, the standard reference value established by Japan, which is similar to Taiwan's public sentiment, is used to calculate and weight the scores (20) Change =(Week 12 score-baseline score; week 24 score-baseline score) baseline and week 12 and week 24
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