Budhi Setianto Purwowiyoto

Background: The risk of rehospitalization in patients with heart failure (HF) has initiated various efforts to prevent and simultaneously improve quality of life. Self-monitoring at home is one option, and technology is increasingly being used for this purpose. Objective: This pilot study aimed to evaluate the feasibility and preliminary effects of a digital home monitoring intervention on patient-reported outcomes and 30-day readmissions among patients with HF in Indonesia. Methods: A mixed methods pilot study was conducted, combining qualitative system development and quantitative evaluation. Patients were assigned to an intervention group (digital monitoring) or control group (standard care). Readmission rates were compared using chi-square tests and odds ratios. Changes in Kansas City Cardiomyopathy Questionnaire scores were analyzed using linear mixed-effects models. Results: A total of 60 patients were included (n=30, 50% in the intervention group; n=30, 50% in the control group). Readmission occurred in 20% (6/30) of patients in the intervention group and 43.3% (13/30) of patients in the control group (odds ratio 0.33, 95% CI 0.10‐1.09; P =.10). Linear mixed-effects analysis showed greater improvement in Kansas City Cardiomyopathy Questionnaire overall summary score in the intervention group ( P =.02). Improvements were observed in the physical limitation, symptom frequency, symptom burden, quality of life, and social limitation domains. During follow-up, 3.3% (1/30) of the patients in the intervention group died of non–HF-related causes, and 10% (3/30) of the patients in the control group died due to HF. Conclusions: This pilot study suggests that digital home monitoring is feasible and associated with improvements in patient-reported outcomes, with a potential signal toward reduced readmission. Larger studies are needed to confirm effectiveness.

BACKGROUND The risk of rehospitalization in heart failure (HF) patients has initiated various preventive efforts and to simultaneously improve the quality of life (QoL) of the patients. Self-monitoring at home is one option, and technology is increasingly being used for this purpose. OBJECTIVE To reduce the risk of hospital readmission and maintain the QoL of HF patients through self-monitoring with the assistance of a digital application. METHODS Starting with determining the need for HF services in National Cardiovascular Center Jakarta in 2024, an application called FineHeart was built and tested on HF patients in a quasi-experimental pilot study. After the User Acceptance Test was completed, HF patients were recruited as intervention group and control group participants. Quality of Life was measured with the Kansas City Cardiomyopathy Questionnaire (KCCQ) before and after the test. The readmission rate and 4 of the KCCQ parameters were analysed between the 2 groups. RESULTS Of the 72 patients who met the inclusion criteria, thirty participated in the intervention group and thirty in the control group who had signed the consent form. In the intervention group, after 30 days, 22 people complied using the FineHeart application prototype (73.3%), six were readmitted (20%), and one died not because of HF (3.3%). In the control group, 10 were readmitted (33.3%), and three died because of HF (10%). There was a significant relationship between adherence to application usage and an increase in Quality-of-Life scores (p<0.029) and Overall Summary Score (p<0.001)), but not in Self-efficacy and Social Limitation Scores. CONCLUSIONS The findings of this study provide a potential benefit for HF patients to perform self-monitoring at home in collaboration with the hospital team by using FineHeart app. Patient adherence may reduce the risk of readmission and improve QoL. Multicenter studies on larger groups of patients are needed to confirm these preliminary results.

Background: Heart failure leads to reduced quality of life, high hospitalization rates, mortality rates, and treatment costs where out-of-hospital self-monitoring can help with management and prevention of hospitalization and digital apps can help with this. The purpose of this review was getting all information of the studies regarding self-monitoring assisted by mobile health or digital application for heart failure patients.Subjects and Method: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols for a Scoping Review (PRISMA-ScR), literature searches were developed by searching the databases: PubMed.gov, ScienceDirect, SpringerLink, Google Scholar. Following the eligibility criteria, articles that included were analyzed to get the result.Results: Mostly the studies were conducted in 2016 and 2017 (20% each, n=5), less studies in 2018, 2019, 2020, and increased again in 2021 (16%, n=4). The studies were done 57% in USA (n=13), both Australia and Canada were 9% (n=2), and other countries. The designs of the studies were mostly RCT (74%, n=17). Sample size was variative mostly less than 50 participants (39%, n=9). There were 65% of the studies measured the daily body weight (n=15), others used vital signs 57%, medication adherence 39%, and other items. QoL was the most in the outcome (61%, n=14). Main findings mostly showed positive impact on self-monitoring with digital application.Conclusion: Using mobile apps for heart failure patients’ self-monitoring created the positive impacts in the expected outcomes, mostly for quality of life.

Objectives: In Indonesia, the poor prognosis and high hospital readmission rates of patients with heart failure (HF) have yet to receive focused attention. However, machine learning (ML) approaches can help to mitigate these problems. We aimed to determine which ML models best predicted HF severity and hospital readmissions and could be used in a patient self-monitoring mobile application.Methods: In a retrospective cohort study, we collected the data of patients admitted with HF to the Siloam Diagram Heart Center in 2020, 2021, and 2022. Data was analyzed using the Orange data mining classification method. ML support algorithms, including artificial neural network (ANN), random forest, gradient boosting, Naïve Bayes, tree-based models, and logistic regression were used to predict HF severity and hospital readmissions. The performance of these models was evaluated using the area under the curve (AUC), accuracy, and F1-scores.Results: Of the 543 patients with HF, 3 (0.56%) were excluded due to death on admission. Hospital readmission occurred in 138 patients (25.6%). Of the six algorithms tested, ANN showed the best performance in predicting both HF severity (AUC = 1.000, accuracy = 0.998, F1-score = 0.998) and readmission for HF (AUC = 0.998, accuracy = 0.975, F1-score = 0.972). Other studies have shown variable results for the best algorithm to predict hospital readmission in patients with HF.Conclusions: The ANN algorithm performed best in predicting HF severity and hospital readmissions and will be integrated into a mobile application for patient self-monitoring to prevent readmissions.

Dwiputra B, et al. J Lipid Atheroscler. 2024 May;13(2):89-96. https://doi.org/10.12997/jla.2024.13.2.89

Cardiac rehabilitation (CR) reduces mortality and morbidity in coronary heart disease (CHD); however, patients show a lack of adherence to CR. Alternatively, telehealth interventions have shown promising results for improving target outcomes in CR. This study aimed to review the effect of smartphone-based CR on the functional capacity of CHD patients. A literature search was performed using PubMed, MEDLINE, Embase, and Cochrane Library on 21 March, 2022 to find randomised controlled trials on smartphone usage in CR to improve functional capacity. Outcomes included maximal oxygen consumption (VO2 max), a 6-min walk test (6-MWT), quality of life, smoking cessation, and modifiable risk factors. Eleven trials recruiting CHD patients were reviewed. Wearable devices connected to smartphone- or chat-based applications were commonly used for CR delivery. Most trials managed to provide exercise prescriptions, education on medication adherence and controlling risk factors, and psychosocial counselling through the intervention. Functional capacity improved significantly following smartphone-based CR in CHD patients compared to control groups, as measured by VO2 max and 6-MWT; patients were more likely to quit smoking. Compared to traditional care, smartphones that delivered CR to CHD patients demonstrate superior outcomes regarding increasing functional capacity. There is no significant improvement on lipid profile, blood pressure, HbA1C, body mass index, and quality of life. It can be used either alone or as an adjunct. Ultimately, the patients’ preferences and circumstances should be considered.

Purpose: Our study aimed at determining and comparing the mechanism of cardiovascular protection variables in moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT) in patients with stable coronary heart disease (CHD) after coronary stenting. Participants and Methods: This experimental study used the same subject and cross-over design, involving eleven stable CHD patients after coronary stenting. These were randomly divided into two groups; MICT for 29 minutes at 50– 60% heart rate reserve and HIIT with 4x4 minute intervals at 60– 80% heart rate reserve, each followed by three minutes of active recovery at 40– 50% heart rate reserve. These were conducted three times a week for two weeks. The participants’ levels of adrenaline, noradrenaline, endothelial nitric oxide synthase (eNOS), extracellular superoxide dismutase (EC-SOD) activity assayed, and flow-mediated dilatation (FMD) were examined before and after treatments were completed. Results: The HIIT significantly increased the levels of noradrenaline and eNOS compared with MICT (p< 0.05). Also, HIIT was better in maintaining EC-SOD activity and FMD compared with MICT (p< 0.05). Through the noradrenalin pathway, HIIT had a direct and significant effect on eNOS and FMD (p< 0.05) but MICT, through the noradrenaline pathways, had a direct and significant effect on eNOS (p< 0.05), and through the EC-SOD activity pathways had a direct and significant effect on FMD (p< 0.05). MICT reduced EC-SOD activity and also decreased the FMD value. Conclusion: HIIT is superior to MICT in increasing cardiovascular protection by increasing the concentrations of noradrenalin and eNOS, maintaining EC-SOD activity, and FMD in stable CHD patients after coronary stenting.