ADVANCING DIGITAL HEALTH INTERVENTIONS AS A CLINICALLY APPLIED SCIENCE FOR BLOOD PRESSURE REDUCTION: A SYSTEMATIC REVIEW AND META-ANALYSIS
CCC ePoster Library. Stogios N. 10/26/19; 280537; 302
Ms. Nicolette Stogios
Ms. Nicolette Stogios
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Abstract
Discussion Forum (0)
Rate & Comment (0)
BACKGROUND: The combination of pharmacotherapy with lifestyle counselling is recommended by international heart health organizations as the optimal strategy to reduce risk factors for cardiovascular disease (CVD). Trials of digital counselling demonstrate significant efficacy in lowering systolic blood pressure (SBP), but heterogeneity of SBP outcomes is a common problem. Our initial aim was to evaluate randomized controlled trials (RCT) of digital counselling for blood pressure reduction that were cited in guideline statements by international cardiovascular societies, or in major meta-analyses. This evaluation focused on efficacy and heterogeneity of SBP outcomes, and how these outcomes were associated with (i) the degree of complexity of the intervention protocol, and (ii) whether an explicit model of behaviour change or counselling was used.

METHODS AND RESULTS: Our literature search focused on relevant taskforce guidelines, scientific statements, systematic reviews and meta-analyses published since 2010 and noted in EMBASE, Cochrane Library, psycINFO, and PubMed databases. We extracted RCT's of digital counselling for blood pressure reduction in populations with elevated cardiovascular risk factors or cardiovascular disease. Sixteen trials met inclusion criteria: pooled n = 4,408, 30% female, 89% prescribed antihypertensive medications. SBP reduction was characterized by a low-moderate standardized mean difference (SMD) of 0.39 (95% CI: 0.3, 0.5) between Digital Intervention vs. Control groups, with high-moderate heterogeneity (I^2 = 69%). This was equivalent to -8.2 mmHg for digital counselling (95% CI: -7.9 to -8.4) versus -4.2 mmHg for control (95% CI: -4.4 to -3.9), p < 0.0001. Figure 1 illustrates similar low-moderate treatment effects for SBP outcomes, with high-moderate heterogeneity, among trials with complex interventions of 3-5 treatment components. Therapeutic outcome was optimal for SBP reduction, with a moderate SMD and moderate heterogeneity (I^2 = 49%) when the intervention had multiple therapeutic components and was organized by a theoretical framework of behaviour change or counselling. This translated to -4.8 mmHg for digital counselling (95% CI: -5.09 to -4.57) versus -1.4 mmHg (95% CI: -1.89 to -0.99) for Control.

CONCLUSION: Digital health interventions optimize the efficacy of medical therapy for SBP reduction. Therapeutic outcomes are improved with adherence to recommended guidelines for the intervention design, including the use of a clinically organized protocol and multiple therapeutic components in the intervention. Given that digital health applications are projected to grow at an accelerated rate, there is opportunity to promote disruptive change in the design of behavioural counselling interventions for CVD risk factor reduction through the synergy of clinical science and digital technology.
BACKGROUND: The combination of pharmacotherapy with lifestyle counselling is recommended by international heart health organizations as the optimal strategy to reduce risk factors for cardiovascular disease (CVD). Trials of digital counselling demonstrate significant efficacy in lowering systolic blood pressure (SBP), but heterogeneity of SBP outcomes is a common problem. Our initial aim was to evaluate randomized controlled trials (RCT) of digital counselling for blood pressure reduction that were cited in guideline statements by international cardiovascular societies, or in major meta-analyses. This evaluation focused on efficacy and heterogeneity of SBP outcomes, and how these outcomes were associated with (i) the degree of complexity of the intervention protocol, and (ii) whether an explicit model of behaviour change or counselling was used.

METHODS AND RESULTS: Our literature search focused on relevant taskforce guidelines, scientific statements, systematic reviews and meta-analyses published since 2010 and noted in EMBASE, Cochrane Library, psycINFO, and PubMed databases. We extracted RCT's of digital counselling for blood pressure reduction in populations with elevated cardiovascular risk factors or cardiovascular disease. Sixteen trials met inclusion criteria: pooled n = 4,408, 30% female, 89% prescribed antihypertensive medications. SBP reduction was characterized by a low-moderate standardized mean difference (SMD) of 0.39 (95% CI: 0.3, 0.5) between Digital Intervention vs. Control groups, with high-moderate heterogeneity (I^2 = 69%). This was equivalent to -8.2 mmHg for digital counselling (95% CI: -7.9 to -8.4) versus -4.2 mmHg for control (95% CI: -4.4 to -3.9), p < 0.0001. Figure 1 illustrates similar low-moderate treatment effects for SBP outcomes, with high-moderate heterogeneity, among trials with complex interventions of 3-5 treatment components. Therapeutic outcome was optimal for SBP reduction, with a moderate SMD and moderate heterogeneity (I^2 = 49%) when the intervention had multiple therapeutic components and was organized by a theoretical framework of behaviour change or counselling. This translated to -4.8 mmHg for digital counselling (95% CI: -5.09 to -4.57) versus -1.4 mmHg (95% CI: -1.89 to -0.99) for Control.

CONCLUSION: Digital health interventions optimize the efficacy of medical therapy for SBP reduction. Therapeutic outcomes are improved with adherence to recommended guidelines for the intervention design, including the use of a clinically organized protocol and multiple therapeutic components in the intervention. Given that digital health applications are projected to grow at an accelerated rate, there is opportunity to promote disruptive change in the design of behavioural counselling interventions for CVD risk factor reduction through the synergy of clinical science and digital technology.
Code of conduct/disclaimer available in General Terms & Conditions

By clicking “Accept Terms & all Cookies” or by continuing to browse, you agree to the storing of third-party cookies on your device to enhance your user experience and agree to the user terms and conditions of this learning management system (LMS).

Cookie Settings
Accept Terms & all Cookies