A multidisciplinary care team model, or Heart Team approach, has become a central tenet of cardiovascular care. Though initially applied to the management of heart transplantation and subsequently complex coronary artery disease, the Heart Team is now utilized broadly across cardiovascular medicine, including in the treatment of valvular disease, pulmonary embolism, cardiogenic shock, high-risk pregnancies in patients with pre-existing cardiovascular disease, and adult congenital heart disease. The Heart Team model improves interdisciplinary collaboration among specialties, adherence to societal guidelines, and shared decision-making with patients and families. In this review, we highlight the development and rationale supporting the Heart Team model, address the challenges of implementing a multidisciplinary care team, and discuss the optimal methods to continue to build, optimize, and implement this approach.

AIM: Patients with heart failure with reduced ejection fraction and low systolic blood pressure (SBP) have high mortality, hospitalizations, and poorly tolerate evidence-based medical treatment. Omecamtiv mecarbil may be particularly helpful in such patients. This study examined its efficacy and tolerability in patients with SBP ≤100 mmHg enrolled in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC-HF). METHODS AND RESULTS: The GALACTIC-HF enrolled patients with baseline SBP ≥85 mmHg with a primary outcome of time to cardiovascular death or first heart failure event. In this analysis, patients were divided according to their baseline SBP (≤100 vs. >100 mmHg). Among the 8232 analysed patients, 1473 (17.9%) had baseline SBP ≤100 mmHg and 6759 (82.1%) had SBP >100 mmHg. The primary outcome occurred in 715 (48.5%) and 2415 (35.7%) patients with SBP ≤100 and >100 mmHg, respectively. Patients with lower SBP were at higher risk of adverse outcomes. Omecamtiv mecarbil, compared with placebo, appeared to be more effective in reducing the primary composite endpoint in patients with SBP ≤100 mmHg [hazard ratio (HR), 0.81; 95% confidence interval (CI), 0.70-0.94] compared with those with SBP >100 mmHg (HR, 0.95; 95% CI, 0.88-1.03; P-value for interaction = 0.051). In both groups, omecamtiv mecarbil did not change SBP values over time and did not increase the risk of adverse events, when compared with placebo. CONCLUSION: In GALACTIC-HF, risk reduction of heart failure outcomes with omecamtiv mecarbil compared with placebo was large and significant in patients with low SBP. Omecamtiv mecarbil did not affect SBP and was well tolerated independent of SBP values.

Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.