Physical Exercise Combined with Antihypertensive Drug Therapy on Left Ventricular Hypertrophy: Systematic Review and Meta-Analysis.

INTRODUCTION: Physical exercise and antihypertensive drugs contribute to reduce or prevent hypertensive heart disease (HHD). The effect on blood pressure (BP) of both combined therapy is well documented, but not for the left ventricular (LV) function. AIM: A systematic review and meta-analysis was conducted for LV biomarkers analysis regarding to HHD on subjects treated with antihypertensive drugs combined with physical exercise practice. METHODS: The search was conducted on the Pubmed, Bireme, Lilacs, Central (Cochrane) and Science direct databases, comprising undetermined period of time, including randomized studies comparing trained and sedentary subjects, both treated with antihypertensive drugs. We analyzed the influence of combined therapy on echocardiogram parameters and BP. A significance level of 5% and 95% CI was considered for all outcomes. RESULTS: Five studies (N = 1738) were included in meta-analysis. Combined therapy decreased significantly LV mass (CI - 21.63 to - 1.81, N = 783) and heart rate (HR; CI - 4.23 to - 1.59, N = 1738), compared to antihypertensive drugs alone. There was a trend to decrease LV mass index (LVMI; CI - 5.57 to 0.71, N = 1674), systolic BP (CI - 2.47 to 1.23, N = 1674) and diastolic BP (CI - 2.16 to 0.28, N = 1674), a trend to increase of ejection fraction (EF; 95% CI - 0.50 to 2.12, N = 783) and LV end-diastolic diameter (CI - 0.85 to 0.92, N = 847) was similar. CONCLUSION: The antihypertensive therapy combined with physical exercise practice can reduce LV mass and HR. Therefore, combined therapy prescription should be considered for prevention and treatment of LV hypertrophy of hypertensive subjects.

An alternative method for assessing the equivalence among treatments in survival analysis / Um método alternativo para avaliar a equivalência entre tratamentos em análise de sobrevivência

This work aims to evaluate the use of parametric models instead of a nonparametric procedure to adjust survival curves related to different treatments, and to verify the equivalence among treatments by the multivariate method of cluster analysis. The dataset used to validate the method was obtained from a laboratory experiment with cutting ants. Eight colonies of cutting ants were used, each one receiving different treatments. The exponential, Weibull, log-normal, and logistic models were adjusted for each treatment, along with the usual Kaplan-Meier adjustment. The logistic model used was the best option for evaluating the survival of the ants. Therefore, this model was adjusted for each treatment. The estimates of the parameters of each adjusted model were clustered using Ward's method of multivariate technique of cluster analysis. Finally, heuristic techniques for choosing the number of clusters were applied in order to define the sets of equivalent treatments. For the dataset used, the proposed method was less laborious and as efficient as the logrank for the comparison of many survival curves.

Este trabalho tem como objetivo avaliar o uso de modelos paramétricos, ao invés do usual procedimento não paramétrico, no ajuste de curvas de sobrevivência em relação a diferentes tratamentos e ainda verificar a equivalência entre esses tratamentos através da técnica multivariada de análise de agrupamento. O conjunto de dados usado para validar o método foi obtido através de um experimento de laboratório com formigas cortadeiras. Oito colônias de formigas cortadeiras foram usadas, cada uma recebendo um tratamento diferente. Os modelos exponencial, Weibull, log-normal e logístico foram ajustados para cada tratamento além do usual ajustamento de Kaplan-Meier. O modelo logístico foi o mais aceitável para avaliar a sobrevivência das formigas. Portanto, esse modelo foi ajustado para cada tratamento. As estimativas dos parâmetros de cada modelo ajustado foram agrupadas utilizando o método de Ward da técnica multivariada de análise de agrupamento. Para o conjunto de dados usado, o método proposto foi menos trabalhoso e tão eficiente quanto o teste logrank para a comparação das várias curvas de sobrevivência.