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Dapagliflozin across the range of ejection fraction in patients with heart failure: a patient-level, pooled meta-analysis of DAPA-HF and DELIVER

Whether the sodium–glucose cotransporter 2 inhibitor dapagliflozin reduces the risk of a range of morbidity and mortality outcomes in patients with heart failure regardless of ejection fraction is unknown. A patient-level pooled meta-analysis of two …

Comments on 'Sample size formula for a win ratio endpoint' by RX Yu and J. Ganju

We compared two recently published formulas for the sample size calculation based on the win ratio and the win odds tests. Both are general formulas that can incorporate unbalanced randomization and ties. In the case of no ties and both formulas …

Design and Analysis of Studies Based on Hierarchical Composite Endpoints: Insights from the DARE-19 Trial

DARE-19 was a randomised, double-blind, placebo-controlled trial of patients hospitalised with COVID-19 and with at least one cardiometabolic risk factor (ie, hypertension, type 2 diabetes, atherosclerotic cardiovascular disease, heart failure, and chronic kidney disease). Patients were randomly assigned 1:1 to dapagliflozin (10 mg daily orally) or matched placebo for 30 days.

Dapagliflozin and Kidney Outcomes in Hospitalized Patients with COVID-19 Infection

DARE-19 was a randomised, double-blind, placebo-controlled trial of patients hospitalised with COVID-19 and with at least one cardiometabolic risk factor (ie, hypertension, type 2 diabetes, atherosclerotic cardiovascular disease, heart failure, and chronic kidney disease). Patients were randomly assigned 1:1 to dapagliflozin (10 mg daily orally) or matched placebo for 30 days.

Power and sample size calculation for the win odds test: application to an ordinal endpoint in COVID-19 trials

The win odds is a distribution-free method of comparing locations of distributions of two independent random variables. Introduced as a method for analyzing hierarchical composite endpoints, it is well suited to be used in the analysis of ordinal scale endpoints in COVID-19 clinical trials. For a single outcome, we provide power and sample size calculation formulas for the win odds test. We also provide an implementation of the win odds analysis method for a single ordinal outcome in a commonly used statistical software to make the win odds analysis fully reproducible.

Dapagliflozin in patients with cardiometabolic risk factors hospitalised with COVID-19 (DARE-19)

DARE-19 was a randomised, double-blind, placebo-controlled trial of patients hospitalised with COVID-19 and with at least one cardiometabolic risk factor (ie, hypertension, type 2 diabetes, atherosclerotic cardiovascular disease, heart failure, and chronic kidney disease). Patients were randomly assigned 1:1 to dapagliflozin (10 mg daily orally) or matched placebo for 30 days.

Dapagliflozin and Recurrent Heart Failure Hospitalizations in Heart Failure With Reduced Ejection Fraction: An Analysis of DAPA-HF

Dapagliflozin reduced the risk of total (first and repeat) HF hospitalizations and cardiovascular death. Time-to-first event analysis underestimated the benefit of dapagliflozin in HF and reduced ejection fraction.

Effects of dapagliflozin on prevention of major clinical events and recovery in patients with respiratory failure because of COVID‐19: Design and rationale for the DARE‐19 study

DARE-19 will evaluate whether dapagliflozin can prevent COVID-19-related complications and all-cause mortality, or improve clinical recovery, and assess the safety profile of dapagliflozin in this patient population. Currently, DARE-19 is the first large randomized controlled trial investigating use of sodium-glucose cotransporter 2 inhibitors in patients with COVID-19.

Adjusted win ratio with stratification: Calculation methods and interpretation

The win ratio is a general method of comparing locations of distributions of two independent, ordinal random variables, and it can be estimated without distributional assumptions. In this paper we provide a unified theory of win ratio estimation in the presence of stratification and adjustment by a numeric variable.