THE EFFECTS OF THREE DIFFERENT REAR KNEE ANGLES ON KINEMATICS IN THE SPRINT START

The purpose of this study was to investigate the rear knee angle range in the set position that allows sprinters to reach greater propulsion on the rear block during the sprint start. Eleven university-track team sprinters performed the sprint start using three rear knee angle conditions: 90°, 115° and 135°. A motion capture system consisting of 8 digital cameras (250 Hz) was used to record kinematic parameters at the starting block phase and the acceleration phase. The following variables were considered: horizontal velocity of the centre of mass (COM), COM height, block time, pushing time on the rear block, percentage of pushing time on the rear block, force impulse, push-off angle and length of the first two strides. The main results show that first, horizontal block velocity is significantly greater at 90° vs 115° and 135° rear knee angle (p<0.05 and p<0.001 respectively) at block clearance and the first two strides; second, during the pushing phase, the percentage of pushing time of the rear leg is significantly greater at 90° vs 135° rear knee angle (p<0.01). No significant difference was found for block time among the conditions. These results indicate that block velocity is the main kinematic parameter affected by rear knee angle during the starting block phase and acceleration phase. Furthermore, the 90° rear knee angle allows for a better push-off of the rear leg than larger angles at the set position. The findings of this study provide some direction and useful practical advice in defining an efficient rear leg biomechanical configuration at the set position.     

Some Properties of Block Matrices of Models Based on Hierarchical and Crossed Classifications

Proofs of several theorems on some properties of block matrices of linear statistical models based on hierarchical and crossed classifications are given. These properties are useful to deduce the estimator of vector of missing data in the case of any hierarchical classification and cross classification with the interaction of the highest order.     

Alternating wide complex tachycardia after surgical aortic valve replacement

A 51-year-old male developed recurrent episodes of palpitations and pre-syncope after surgical aortic valve replacement. Electrocardiograms after surgery revealed a wide complex tachycardia with alternating left bundle branch and right bundle branch block morphologies. An electrophysiology study (EPS) demonstrated typical bundle branch reentry ventricular tachycardia (BBRVT) treated successfully with right bundle ablation. We demonstrate the key diagnostic features of BBRVT on EPS, describe the circuit of BBRVT with explanation of the HV pseudointerval, and highlight the association of BBRVT and valve replacement.     

Refractory heart failure with LBBB - Pause before CRT

In this report, we describe complete disappearance of LBBB with normalization of LV function in two patients with cardiac sarcoidosis (CS) after immunosuppressive therapy. Both of these patients were ideal Class IA candidates for CRT (Complete LBBB, QRS ≥ 150 ms, EF < 30%). If CS is identified early, immunosuppressive treatment can lead to not only improvement of left ventricular function but also disappearance of the left bundle branch block. Timely diagnosis and management of CS obviated the need of CRT in these patients. It may be reasonable to evaluate all non-ischemic cardiomyopathies for underlying reversible causes prior to CRT implantation.     

Sample size considerations for stepped wedge designs with subclusters

The stepped wedge cluster randomized trial (SW-CRT) is an increasingly popular design for evaluating health service delivery or policy interventions. An essential consideration of this design is the need to account for both within-period and between-period correlations in sample size calculations. Especially when embedded in health care delivery systems, many SW-CRTs may have subclusters nested in clusters, within which outcomes are collected longitudinally. However, existing sample size methods that account for between-period correlations have not allowed for multiple levels of clustering. We present computationally efficient sample size procedures that properly differentiate within-period and between-period intracluster correlation coefficients in SW-CRTs in the presence of subclusters. We introduce an extended block exchangeable correlation matrix to characterize the complex dependencies of outcomes within clusters. For Gaussian outcomes, we derive a closed-form sample size expression that depends on the correlation structure only through two eigenvalues of the extended block exchangeable correlation structure. For non-Gaussian outcomes, we present a generic sample size algorithm based on linearization and elucidate simplifications under canonical link functions. For example, we show that the approximate sample size formula under a logistic linear mixed model depends on three eigenvalues of the extended block exchangeable correlation matrix. We provide an extension to accommodate unequal cluster sizes and validate the proposed methods via simulations. Finally, we illustrate our methods in two real SW-CRTs with subclusters.     

Selection Problems in Balanced Block Designs

If we have independent random variables the solution of BECHHOFER's selection problem in special cases is easily applied because we can use tables of a standardized multivariate normal distribution. The aim of this note is to show how such tables are also applicable in a case of correlated random variables like the estimates of treatment effects in BIB and BCB. Formulae for a choice of minimal sample sizes are also given.