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Full-Text Articles in Physical Sciences and Mathematics
Heart Failure In Humans Reduces Contractile Force In Myocardium From Both Ventricles, Cheavar A. Blair, Elizabeth A Brundage, Katherine L. Thompson, Arnold J. Stromberg, Maya Guglin, Brandon J Biesiadecki, Kenneth S. Campbell
Heart Failure In Humans Reduces Contractile Force In Myocardium From Both Ventricles, Cheavar A. Blair, Elizabeth A Brundage, Katherine L. Thompson, Arnold J. Stromberg, Maya Guglin, Brandon J Biesiadecki, Kenneth S. Campbell
Statistics Faculty Publications
This study measured how heart failure affects the contractile properties of the human myocardium from the left and right ventricles. The data showed that maximum force and maximum power were reduced by approximately 30% in multicellular preparations from both ventricles, possibly because of ventricular remodeling (e.g., cellular disarray and/or excess fibrosis). Heart failure increased the calcium (Ca2+) sensitivity of contraction in both ventricles, but the effect was bigger in right ventricular samples. The changes in Ca2+ sensitivity were associated with ventricle-specific changes in the phosphorylation of troponin I, which indicated that adrenergic stimulation might induce different effects …
Sample Size Calculation And Blinded Recalculation For Analysis Of Covariance Models With Multiple Random Covariates, Georg Zimmermann, Meinhard Kieser, Arne C. Bathke
Sample Size Calculation And Blinded Recalculation For Analysis Of Covariance Models With Multiple Random Covariates, Georg Zimmermann, Meinhard Kieser, Arne C. Bathke
Statistics Faculty Publications
When testing for superiority in a parallel-group setting with a continuous outcome, adjusting for covariates is usually recommended. For this purpose, the analysis of covariance is frequently used, and recently several exact and approximate sample size calculation procedures have been proposed. However, in case of multiple covariates, the planning might pose some practical challenges and pitfalls. Therefore, we propose a method, which allows for blinded re-estimation of the sample size during the course of the trial. Simulations confirm that the proposed method provides reliable results in many practically relevant situations, and applicability is illustrated by a real-life data example.