Abstract Body (Do not enter title and authors here): Hypothesis and Purpose
Patients with acute coronary syndromes (ACS) are at high risk of recurrent cardiovascular disease (CVD) events. Most are not on lipid-lowering therapy (LLT) at admission and LLT is typically initiated before discharge. Under current standard-of-care (SoC) pathways, additional LLT adjustments are often needed over months or years post-ACS to achieve low-density lipoprotein cholesterol (LDL-C) goals. This stepwise optimization relies solely on achieved LDL-C levels rather than estimated CVD risk reductions from further LDL-C lowering through adjunctive LLT or intensified statin monotherapy.
We hypothesized that a Decision Support System (DSS) providing information on residual CVD risk and potential benefits of various LLTs may lead to earlier optimization compared to SoC (Figure 1). If confirmed, integrating a pragmatic DSS into electronic health records could accelerate LDL-C goal achievement and improve patient outcomes.
Study Design and Methods
An interventional, parallel-assignment, statistician-blinded, cluster-randomized controlled trial with a 16-week follow-up. The primary endpoint will be analyzed with a generalized linear mixed model (GLM) with fixed effects for country and site type and a random effect for study site. The secondary endpoints will be analyzed using Kaplan-Meier plots, Cox proportional hazards and GLM models.
Sample Size
1140 patients from 42 sites in the UK, Italy, and Spain, randomized to the DSS or SoC (tabulated in Figure 2).
Population Studied
Adults <80 years hospitalized ≤72 hours post-ACS.
Intervention
A DSS offering clinicians patient-specific absolute 10-year risk of atherosclerotic CVD and potential risk reductions over time for different LLT regimens and combinations (Fig. 1).
Power Calculations
Up to 48 clusters of 33 participants each are needed to detect a 10% higher use of combination LLT in the DSS group vs the SoC group (15% vs 5%) within 4 months post-ACS (End of Study), with 90% power and an intraclass correlation coefficient of 0.1.
Primary End Point
Proportion of patients undergoing intensified monotherapy or initiating/escalating combination LLT in DSS vs SoC.
Secondary End Points
Time to intensification/escalation of LLT and differences in LDL-C levels and goal achievement.
Outcomes
Baseline patient characteristics in each arm are available in Fig. 2. The primary and secondary endpoints will be analyzed and presented.
Funding
This work from Imperial College London is supported by Sanofi Winthrop Industrie.