mHealth Technology and CVD Risk Reduction

The Fondazione Toscana Gabriele Monasterio app: a digital health system to improve wellbeing of inpatients with heart or lung disease

BACKGROUND

An app providing material for education and entertaining is a possible way to support patients and healthcare providers in achieving person-centered care.

METHODS

An app tailored on the Fondazione Toscana Gabriele Monasterio (FTGM), a research hospital treating cardiac and lung disorders, was created. A pilot evaluation project was conducted on consecutive patients hospitalized for heart or lung disorders. Patients were asked to complete an assessment questionnaire.

RESULTS

The FTGM app provides information on diagnostic and therapeutic investigations, hospital and healthcare personnel, and includes content for entertainment and learning. It was tested on 215 consecutive patients (75% men, 66% aged >60 years, and 40% with a primary or middle school degree). Sixty-nine percentage of patients used the FTGM app, including 67% of patients aged >80 years and 65% of those with an elementary education (65%). Patients gave positive feedback on the app layout. Many (76%) looked for information on doctors and nurses in the 'People' section. Sixty-five percent of responders had used at least one of the sections called 'Music' and 'Museum visits'. The app helped many patients perceive the hospital as a more liveable place (68%), and to feel less anxious (76%), and more engaged in the diagnostic and therapeutic workup (65%). Overall, the majority of responders (87%) rated the app as 'excellent' or 'good', and almost all (95%) would have recommended other patients to use the app.

CONCLUSIONS

The FTGM app is a possible tool to improve patient wellbeing during hospitalization.

Predictors on outcomes of cardiovascular disease of male patients in Malaysia using Bayesian network analysis

OBJECTIVES

Despite extensive advances in medical and surgical treatment, cardiovascular disease (CVD) remains the leading cause of mortality worldwide. Identifying the significant predictors will help clinicians with the prognosis of the disease and patient management. This study aims to identify and interpret the dependence structure between the predictors and health outcomes of ST-elevation myocardial infarction (STEMI) male patients in Malaysian setting.

DESIGN

Retrospective study.

SETTING

Malaysian National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry years 2006-2013, which consists of 18 hospitals across the country.

PARTICIPANTS

7180 male patients diagnosed with STEMI from the NCVD-ACS registry.

PRIMARY AND SECONDARY OUTCOME MEASURES

A graphical model based on the Bayesian network (BN) approach has been considered. A bootstrap resampling approach was integrated into the structural learning algorithm to estimate probabilistic relations between the studied features that have the strongest influence and support.

RESULTS

The relationships between 16 features in the domain of CVD were visualised. From the bootstrap resampling approach, out of 250, only 25 arcs are significant (strength value ≥0.85 and the direction value ≥0.50). Age group, Killip class and renal disease were classified as the key predictors in the BN model for male patients as they were the most influential variables directly connected to the outcome, which is the patient status. Widespread probabilistic associations between the key predictors and the remaining variables were observed in the network structure. High likelihood values are observed for patient status variable stated alive (93.8%), Killip class I on presentation (66.8%), patient younger than 65 (81.1%), smoker patient (77.2%) and ethnic Malay (59.2%). The BN model has been shown to have good predictive performance.

CONCLUSIONS

The data visualisation analysis can be a powerful tool to understand the relationships between the CVD prognostic variables and can be useful to clinicians.

Feasibility and preliminary efficacy of a novel web-based physical activity intervention in adults with overweight/obesity: A pilot randomized controlled trial

BACKGROUND

Only 14% of adults with obesity attain federal guidelines for physical activity (PA), but few interventions address obesity-specific barriers to PA. We designed the web-based Physical Activity for The Heart (PATH) intervention to address this gap.

PURPOSE

Test the feasibility and preliminary efficacy of PATH for promoting PA and reducing cardiovascular disease (CVD) risk in adults with overweight/obesity.

METHODS

In a 12-week pilot RCT, participants were randomized to PATH (n = 41) or wait-list control (n = 41) groups. Treatment group received access to PATH and met twice/month with a remote coach. The control group received a self-help PA guide and newsletters on general health. Moderate-to-vigorous PA (MVPA) was assessed via Actigraph-GT3X, steps via Fitbit Charge 2™, weight via smart scale, blood pressure (BP) via Omron BP device, and lipids/HbAIC via dry blood spot. Linear mixed modeling examined between- and within-group differences in PA and CVD risk.

RESULTS

The sample (N = 82) was on average 55.9 ± 8.2 years old; mean BMI 35.5 ± 6.2 kg/m2; 57.3% white and 80.5% female. Recruitment lasted 6-months, and 12-week retention was 96.3%. Treatment group accessed PATH ≥twice/week (92.1%), spent ≥10 min/visit (89.5%) and thought the site was culturally appropriate (79%). At 12 wks, the PATH group had greater mean changes in weekly MVPA (+58.9 vs. +0.9 min, p = .024) and daily steps (+1246.4 vs. -64.2 steps, p = .002) compared to the control group. Also, the PATH group improved in weight, BMI, body fat, waist circumference, and BP (p < .05).

CONCLUSION

The PATH intervention is feasible/acceptable and demonstrated preliminary efficacy for promoting PA among adults with overweight/obesity.

Personalized knowledge to reduce the risk of stroke (PERKS-International): Protocol for a randomized controlled trial

RATIONALE

Theoretically, most strokes could be prevented through the management of modifiable risk factors. The Stroke Riskometer™ mobile phone application (hereon "The App") uses an individual's data to provide personalized information and advice to reduce their risk of stroke.

AIMS

To determine the effect of The App on a combined cardiovascular risk score (Life's Simple 7^®, LS7) of modifiable risk factors at 6 months post-randomization.

METHODS AND DESIGN

PERKS-International is a Phase III, multicentre, prospective, pragmatic, open-label, single-blinded endpoint, two-arm randomized controlled trial (RCT). Inclusion criteria are as follows: age ⩾ 35 and ⩽75 years; ⩾2 LS7 risk factors; smartphone ownership; no history of stroke/myocardial infarction/cognitive impairment/terminal illness. The intervention group (IG) will be provided with The App, and the usual care group (UCG) is provided with generic online information about risk factors, but not be informed about The App. Face-to-face assessments will be conducted at baseline and 6 months, and online at 3 and 12 months. The RCT includes a process and economic evaluation.

STUDY OUTCOMES AND SAMPLE SIZE

The primary outcome is a difference in the mean change in LS7 (seven individual items: blood pressure, cholesterol, glucose, body mass index (BMI), smoking, physical activity, and diet) from baseline to 6 months post-randomization with intention-to-treat analysis. Secondary outcomes include: change in individual LS7 items, quality of life; stroke awareness, adverse events; health service use; and costs. Based on pilot data, 790 participants (395 IG, 395 UCG) will be required to provide 80% power (two-sided α = 0.05) to detect a mean difference in the LS7 of ⩾0.40 (SD 1.61) in IG compared to 0.01 (SD 1.44) in the UCG at 6 months post-randomization.

DISCUSSION

Stroke is largely preventable. This study will provide evidence of the effectiveness of a mobile app to reduce stroke risk.

TRIAL REGISTRATION

ACTRN12621000211864.