Publications

BACKGROUND

Guidelines provide class I recommendations for aortic valve intervention for patients with symptomatic severe aortic stenosis (AS) or reduced ejection fraction, but the cornerstone of management for asymptomatic patients has been watchful waiting. This is based on historical nonrandomized data, but randomized controlled trials (RCTs) have now been performed of early surgical aortic valve replacement (SAVR) for asymptomatic severe AS. We performed a meta-analysis of RCTs comparing early SAVR to watchful waiting for asymptomatic severe AS, focusing on individual end points of death and heart failure (HF) hospitalization.

METHODS

We systematically identified all RCTs comparing early SAVR to watchful waiting in patients with asymptomatic severe AS and synthesized the data in a random-effects meta-analysis. The prespecified primary end point was all-cause mortality.

RESULTS

Two trials randomizing 302 patients were included. Early SAVR lead to a 55% reduction in all-cause mortality (hazard ratio, 0.45; 95% confidence interval, 0.24-0.85; = .014). There was no heterogeneity (I = 0.0%). Early SAVR also lead to a 79% reduction in HF hospitalization (hazard ratio, 0.21; 95% confidence interval, 0.05-0.96; = .044).

CONCLUSIONS

In patients with severe asymptomatic AS and normal ejection fraction, early SAVR reduces death and HF hospitalization compared to initial conservative management. This challenges current treatment standards and has implications for the clinical care of these patients and for guidelines.

The breast is a dynamic organ whose response to physiological and pathophysiological conditions alters its disease susceptibility, yet the specific effects of these clinical variables on cell state remain poorly annotated. We present a unified, high-resolution breast atlas by integrating single-cell RNA-seq, mass cytometry, and cyclic immunofluorescence, encompassing a myriad of states. We define cell subtypes within the alveolar, hormone-sensing, and basal epithelial lineages, delineating associations of several subtypes with cancer risk factors, including age, parity, and BRCA2 germline mutation. Of particular interest is a subset of alveolar cells termed basal-luminal (BL) cells, which exhibit poor transcriptional lineage fidelity, accumulate with age, and carry a gene signature associated with basal-like breast cancer. We further utilize a medium-depletion approach to identify molecular factors regulating cell-subtype proportion in organoids. Together, these data are a rich resource to elucidate diverse mammary cell states.