Personalized eHealth Program for Life-style Change: Results From the "Do Cardiac Health Advanced New Generated Ecosystem (Do CHANGE 2)" Randomized Controlled Trial.

OBJECTIVE: Unhealthy life-style factors have adverse outcomes in cardiac patients. However, only a minority of patients succeed to change unhealthy habits. Personalization of interventions may result in critical improvements. The current randomized controlled trial provides a proof of concept of the personalized Do Cardiac Health Advanced New Generation Ecosystem (Do CHANGE) 2 intervention and evaluates effects on a) life-style and b) quality of life over time. METHODS: Cardiac patients (n = 150; mean age = 61.97 ± 11.61 years; 28.7% women; heart failure, n = 33; coronary artery disease, n = 50; hypertension, n = 67) recruited from Spain and the Netherlands were randomized to either the "Do CHANGE 2" or "care as usual" group. The Do CHANGE 2 group received ambulatory health-behavior assessment technologies for 6 months combined with a 3-month behavioral intervention program. Linear mixed-model analysis was used to evaluate the intervention effects, and latent class analysis was used for secondary subgroup analysis. RESULTS: Linear mixed-model analysis showed significant intervention effects for life-style behavior (Finteraction(2,138.5) = 5.97, p = .003), with improvement of life-style behavior in the intervention group. For quality of life, no significant main effect (F(1,138.18) = .58, p = .447) or interaction effect (F(2,133.1) = 0.41, p = .67) was found. Secondary latent class analysis revealed different subgroups of patients per outcome measure. The intervention was experienced as useful and feasible. CONCLUSIONS: The personalized eHealth intervention resulted in significant improvements in life-style. Cardiac patients and health care providers were also willing to engage in this personalized digital behavioral intervention program. Incorporating eHealth life-style programs as part of secondary prevention would be particularly useful when taking into account which patients are most likely to benefit. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT03178305.

Usefulness of a Lifestyle Intervention in Patients With Cardiovascular Disease.

The importance of modifying lifestyle factors in order to improve prognosis in cardiac patients is well-known. Current study aims to evaluate the effects of a lifestyle intervention on changes in lifestyle- and health data derived from wearable devices. Cardiac patients from Spain (n = 34) and The Netherlands (n = 36) were included in the current analysis. Data were collected for 210 days, using the Fitbit activity tracker, Beddit sleep tracker, Moves app (GPS tracker), and the Careportal home monitoring system. Locally Weighted Error Sum of Squares regression assessed trajectories of outcome variables. Linear Mixed Effects regression analysis was used to find relevant predictors of improvement deterioration of outcome measures. Analysis showed that Number of Steps and Activity Level significantly changed over time (F = 58.21, p < 0.001; F = 6.33, p = 0.01). No significant changes were observed on blood pressure, weight, and sleep efficiency. Secondary analysis revealed that being male was associated with higher activity levels (F = 12.53, p < 0.001) and higher number of steps (F = 8.44, p < 0.01). Secondary analysis revealed demographic (gender, nationality, marital status), clinical (co-morbidities, heart failure), and psychological (anxiety, depression) profiles that were associated with lifestyle measures. In conclusion results showed that physical activity increased over time and that certain subgroups of patients were more likely to have a better lifestyle behaviors based on their demographic, clinical, and psychological profile. This advocates a personalized approach in future studies in order to change lifestyle in cardiac patients.

Healthcare utilization in patients with first-time implantable cardioverter defibrillators (data from the WEBCARE study).

BACKGROUND: Knowledge of the level of healthcare utilization (HCU) and the predictors of high HCU use in patients with an implantable cardioverter defibrillator (ICD) is lacking. We examined the level of HCU and predictors associated with increased HCU in first-time ICD patients, using a prospective study design. METHODS: ICD patients (N = 201) completed a set of questionnaires at baseline and 3, 6, and 12 months after inclusion. A hierarchical multiple linear regression with three models was performed to examine predictors of HCU. RESULTS: HCU was highest between baseline and 3 months postimplantation and gradually decreased during 12 months follow-up. During the first year postimplantation, only depression (ß = 0.342, P = 0.002) was a significant predictor. Between baseline and 3 months follow-up, younger age (ß = -0.220, P < 0.01), New York Heart Association class III/IV (ß = 0.705, P = 0.01), and secondary indication (ß = 0.148, P = 0.05) were independent predictors for increased HCU. Between 3 and 6 months follow-up, younger age (ß = -0.151, P = 0.05) and depression (ß = 0.370, P < 0.001) predicted increased HCU. Between 6 and 12 months only depression (ß = 0.355, P = 0.001) remained a significant predictor. CONCLUSIONS: Depression was an important predictor of increased HCU in ICD patients in the first year postimplantation, particularly after 3 months postimplantation. Identifying patients who need additional care and provide this on time might better meet patients' needs and lower future HCU.