Ruolo del test da sforzo cardiopolmonare nei pazienti affetti da cardiomiopatia ipertrofica in età pediatrica

Background Decreased exercise capacity, and reduction in peak oxygen uptake are present in most patients affected by hypertrophic cardiomyopathy (HCM) . In addition an abnormal blood pressure response during a maximal exercise test was seen to be associated with high risk for sudden cardiac death in adult patients affected by HCM. Therefore exercise test (CPET) has become an important part of the evaluation of the HCM patients, but data on its role in patients with HCM in the pediatric age are quite limited. Methods and results Between 2004 and 2010, using CPET and echocardiography, we studied 68 children (mean age 13.9 ± 2 years) with HCM. The exercise test was completed by all the patients without adverse complications. The mean value of achieved VO2 max was 31.4 ± 8.3 mL/Kg/min which corresponded to 77.5 ± 16.9 % of predicted range. 51 patients (75%) reached a subnormal value of VO2max. On univariate analysis the achieved VO2 as percentage of predicted and the peak exercise systolic blood pressure (BP) Z score were inversely associated with max left ventricle (LV) wall thickness, with E/Ea ratio, and directly related with Ea and Sa wave velocities No association was found with the LV outflow tract gradient. During a mean follow up of 2.16 ± 1.7 years 9 patients reached the defined clinical end point of death, transplantation, implanted cardioverter defibrillator (ICD) shock, ICD implantation for secondary prevention or myectomy. Patients with peak VO2 < 52% or with peak systolic BP Z score < -5.8 had lower event free survival at follow up. Conclusions Exercise capacity is decreased in patients with HCM in pediatric age and global ventricular function seems being the most important determinant of exercise capacity in these patients. CPET seems to play an important role in prognostic stratification of children affected by HCM.

Bioengineering of exercise: biomechanical and metabolic aspects

The field of research of this dissertation concerns the bioengineering of exercise, in particular the relationship between biomechanical and metabolic knowledge. This relationship can allow to evaluate exercise in many different circumstances: optimizing athlete performance, understanding and helping compensation in prosthetic patients and prescribing exercise with high caloric consumption and minimal joint loading to obese subjects. Furthermore, it can have technical application in fitness and rehabilitation machine design, predicting energy consumption and joint loads for the subjects who will use the machine. The aim of this dissertation was to further understand how mechanical work and metabolic energy cost are related during movement using interpretative models. Musculoskeletal models, when including muscle energy expenditure description, can be useful to address this issue, allowing to evaluate human movement in terms of both mechanical and metabolic energy expenditure. A whole body muscle-skeletal model that could describe both biomechanical and metabolic aspects during movement was identified in literature and then was applied and validated using an EMG-driven approach. The advantage of using EMG driven approach was to avoid the use of arbitrary defined optimization functions to solve the indeterminate problem of muscle activations. A sensitivity analysis was conducted in order to know how much changes in model parameters could affect model outputs: the results showed that changing parameters in between physiological ranges did not influence model outputs largely. In order to evaluate its predicting capacity, the musculoskeletal model was applied to experimental data: first the model was applied in a simple exercise (unilateral leg press exercise) and then in a more complete exercise (elliptical exercise). In these studies, energy consumption predicted by the model resulted to be close to energy consumption estimated by indirect calorimetry for different intensity levels at low frequencies of movement. The use of muscle skeletal models for predicting energy consumption resulted to be promising and the use of EMG driven approach permitted to avoid the introduction of optimization functions. Even though many aspects of this approach have still to be investigated and these results are preliminary, the conclusions of this dissertation suggest that musculoskeletal modelling can be a useful tool for addressing issues about efficiency of movement in healthy and pathologic subjects.