Effect of a lifestyle-focused electronic patient support application for improving risk factor management, self-rated health, and prognosis in post-myocardial infarction patients: study protocol for a multi-center randomized controlled trial.

BACKGROUND: Cardiac rehabilitation (CR) programs addressing risk factor management, educational interventions, and exercise contribute to reduce mortality after myocardial infarction (MI). However, the fulfillment of guideline-recommended CR targets is currently unsatisfactory. eHealth, i.e., the use of electronic communication for healthcare, including the use of mobile smartphone applications combined with different sensors and interactive computerized programs, offers a new array of possibilities to provide clinical care. The present study aims to assess the efficacy of a web-based application (app) designed to support persons in adhering to lifestyle advice and medication as a complement to traditional CR programs for improvement of risk factors and clinical outcomes in patients with MI compared with usual care. METHODS/DESIGN: An open-label multi-center randomized controlled trial is being conducted at different CR centers from three Swedish University Hospitals. The aim is to include 150 patients with MI < 75 years of age who are confident smartphone and/or Internet users. In addition to participation in CR programs according to the usual routine at each center, patients randomized to the intervention arm will receive access to the web-based app. A CR nurse reviews the patients' self-reported data twice weekly through a medical interface at the clinic. The primary outcome of the study will be change in submaximal exercise capacity (in watts) between 2 and 4 weeks after discharge and when the patient has completed his/her exercise program at the CR center, usually around 3-6 months post-discharge. Secondary outcomes include changes in self-reported physical activity, objectively assessed physical activity by accelerometry, self-rated health, dietary, and smoking habits, body mass index, blood pressure, blood lipids, and glucose/HbA1c levels between inclusion and follow-up visits during the first year post-MI. Additionally, we will assess uptake and adherence to the application, the number of CR staff contacts, and the incidence of cardiovascular events at 1 and 3 years after the MI. Patient recruitment started in 2016, and the first study results are expected in the beginning of 2019. DISCUSSION: The present study will add evidence to whether electronic communication can be used to improve traditional CR programs for patients after MI. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03260582 . Retrospectively registered on 24 August 2017.

Cystatin B, cathepsin L and D related to surrogate markers for cardiovascular disease in children.

OBJECTIVE: This study investigated potential associations between novel biomarkers for cardiovascular disease and other surrogate markers for health. METHODS: Community sample of 170 (92 boys and 78 girls) children aged 8-11 years. Total fat mass (TBF) and abdominal fat (AFM) were measured by Dual-energy x-ray absorptiometry (DXA). Total body fat was also expressed as percentage of total body mass (BF%), and body fat distribution was calculated as AFM/TBF. Maximal oxygen uptake (VO2PEAK), systolic and diastolic blood pressure (SBP and DBP) and pulse pressure (PP) were measured. Echocardiography was performed. Left atrial size (LA) and left ventricular mass (LVM) were measured. A follow-up DXA scan was available in 152 children (84 boys and 68 girls). Frozen serum samples were analyzed for cystatin B, cathepsin L and cathepsin D. RESULTS: Partial correlations between cystatin B versus lnTBF, lnBF%, lnAFM, AFM/TBF, VO2PEAK and PP were; r = 0.38, 0.36, 0.38, 0.29, -0.25 and 0.25, P = 0.001 or less for all. Weaker predominantly non-significant correlations were found for cathepsin L, whereas cathepsin D was not related to any surrogate markers for health. No significant correlations were found between biomarkers and change in body fat over 2 years. CONCLUSION: Findings from this community-based cohort of young children show that surrogate markers for cardiovascular disease such as total fat mass, percent body fat, abdominal fat, body fat distribution, maximal oxygen uptake and pulse pressure were all associated with cystatin B. This was not found for cathepsin L or cathepsin D.

Correlation between physical activity, aerobic fitness and body fat against autonomic function profile in children.

AIM: To evaluate correlations between physical activity, VO2PEAK and body fat versus autonomic function in children. METHODS: Children (n = 98) between 10 and 12 years underwent a maximal exercise test (VO2PEAK) and dual-energy X-ray absorptiometry measured body fat. General physical activity, moderate to vigorous physical activity and vigorous physical activity were assessed by accelerometers. Deep breath test with E/I-ratio calculation and a head-up tilt test were performed. The sum of z-scores represented an index score for autonomic function profile and included E/I-ratio plus difference in blood pressure and heart rate between supine and tilted position. Correlation analyses were performed between physical activity parameters, body fat and VO2PEAK versus autonomic function profile. RESULTS: No significant correlations were found between autonomic function profile and physical activity or body fat (p > 0.05). VO2PEAK was correlated with autonomic function profile in boys (r = 0.30, p < 0.05), but not in girls (r = 0.04, NS). One girl and eight boys terminated head-up tilt test prematurely due to intolerance. Minutes of vigorous physical activity per day was lower in these boys compared with those (n = 48) who completed the head-up tilt test (5.1 ± 3.3 vs. 10.4 ± 6.6, p < 0.05). CONCLUSION: Physical activity or body fat was not associated with autonomic function profile. VO2PEAK correlated to autonomic function profile in boys.

Accelerometer measured daily physical activity and sedentary pursuits--comparison between two models of the Actigraph and the importance of data reduction.

BACKGROUND: Very few validation studies have been performed between different generations of the commonly used Actigraph accelerometers. We compared daily physical activity data generated from the old generation Actigraph model 7164 with the new generation Actigraph GT1M accelerometer in 15 young females for eight consecutive days. We also investigated if different wear time thresholds had any impact on the findings. Minutes per day of moderate and vigorous physical activity (MVPA), vigorous physical activity (VPA) and very vigorous physical activity (VVPA) were calculated. Moreover, minutes of sedentary pursuits per day were calculated. FINDINGS: There were significant (P < 0.05) differences between the Actigraph 7164 and the GT1M concerning MVPA (61 ± 21vs. 56 ± 23 min/day), VPA (12 ± 8 vs. 9 ± 3 min/day) and VVPA (3.2 ± 3.0 vs. 0.3 ± 1.1 min/day). The different wear time thresholds had little impact on minutes per day in different intensities. Median minutes of sedentary pursuits per day ranged from 159 to 438 minutes depending on which wear time threshold was used (i.e. 10, 30 or 60 minutes), whereas very small differences were observed between the two different models. CONCLUSIONS: Data from the old generation Actigraph 7164 and the new generation Actigraph GT1M accelerometers differ, where the Actigraph GT1M generates lower minutes spent in free living physical activity. Median minutes of sedentary pursuits per day are highly dependent on which wear time threshold that is used, and not by accelerometer model.

Head-to-head comparison between Actigraph 7164 and GT1M accelerometers in adolescents.

We compared, head-to-head, the old generation Actigraph model 7164 with the new generation Actigraph GT1M accelerometer. A total of 15 randomly selected teenagers (eight girls and seven boys) were investigated. They performed a treadmill test wearing the two kinds of accelerometers around the waist simultaneously. The treadmill test consisted of three different levels of speed 4, 6 and 8 km h(-1) for four consecutive minutes. Accelerometer counts per 1 sec epoch for the Actigraph GT1M versus the Actigraph 7164 were at 4 km h(-1) 21·6 ± 12·9 versus 26·5 ± 11·5 counts, at 6 km h(-1) 56·0 ± 23·2 versus 62·9 ± 25·6 counts and at 8 km h(-1) 142·6 ± 37·2 versus 156·4 ± 34·9 counts (P<0·01 for all levels of speed). Data from the old generation Actigraph 7164 and the new generation Actigraph GT1M accelerometers differ, where the Actigraph GT1M generates 10-23% lower values. Correction equation for Actigraph GT1M was Actigraph 7164 = 5·2484 +  Actigraph GT1M counts × 1·0448. These results need to be taken into consideration when using these devices.

Tracking of physical activity with accelerometers over a 2-year time period.

BACKGROUND: Limited data exist of tracking and changes in accelerometer-measured physical activity in children. METHODS: Physical activity was assessed by accelerometers for 4 days in 167 children (boys, n = 90; girls n = 77) age 9.8 ± 0.6 years. Follow-up measurement was made 2.0 ± 0.1 yrs later (range 1.9-2.1 yrs). General physical activity (GPA) was defined as mean count/minute. Minutes of inactivity; light, moderate, and vigorous physical activity (LMVPA); moderate and vigorous physical activity (MVPA); and vigorous physical activity (VPA) per day were calculated both as absolute values and as percentage of total registration time. RESULTS: Spearman rank order correlation indicated low tracking of MVPA and VPA in girls (r = .25-0.33, P < .05), and low-moderate tracking of GPA, inactivity, LMVPA, MVPA and VPA in boys (r = .23-0.40, P < .05). Time in inactivity increased at follow-up by 5%-14%. Most of the assessed physical activity variables were decreased at follow-up by 6% to 30%. CONCLUSIONS: Physical activity tracks at a low-moderate degree from age 10-12 years, which confirm previous investigations that have used self-report assessments. The low-moderate tracking of physical activity variables indicate that those who were most active initially remained most active. Increasing inactive behavior was observed and that several other physical activity variables were decreased at follow-up.

Lack of physical activity in young children is related to higher composite risk factor score for cardiovascular disease.

AIM: This study evaluates whether accelerometer-measured physical activity is related to higher composite risk factor scores for cardiovascular disease (CVD) in children. METHODS: Cross-sectional study that included 223 children aged 7.9-11.1 years (boys n = 123, girls n = 100). Daily physical activity was assessed by accelerometers for 4 days. Body fat was quantified by dual X-ray absorptiometry. Maximal oxygen uptake was measured during a maximal exercise test. Resting heart rate and blood pressure were measured. Z-scores [(value for the individual - mean value for group)/SD] were calculated for each variable, and the sum of different risk factor z-scores used as an index of composite risk factors score for CVD. RESULTS: Partial correlations, from General Linear Model, between moderate to vigorous physical activity (MVPA), vigorous physical activity (VPA) and general physical activity versus index of composite risk factor score were in boys 0.29, 0.33 and 0.30 (all p < 0.05), respectively. The corresponding correlations in girls were -0.28, -0.32 (both p < 0.05) and -0.18 (NS), respectively. CONCLUSION: Low amounts of MVPA and VPA were related to higher composite risk factor scores for CVD in children aged 8-11 years.