Progressive Muscular Dystrophies (PMDs) are a heterogeneous family of neuromuscular diseases. Although they are considered as a rare diseases group, their severity and relatively high prevalence make them a suitable target for that kind of scientific research whose target is to give to the community a better quality of life. With this in mind, it is reasonable to think that a reliable predictive model is needed. Alas, since both PMDs subtypes prevalence and incidence among general population do not show significant statistical variations, it is not possible to base a predictive model on these data. However, the aim of this paper is to elaborate a novel approach in order to crack the code of PMDs unpredictability.

GSL Journal of Public Health and Epidemiology

D Frumento
2019-01-01

Abstract

Progressive Muscular Dystrophies (PMDs) are a heterogeneous family of neuromuscular diseases. Although they are considered as a rare diseases group, their severity and relatively high prevalence make them a suitable target for that kind of scientific research whose target is to give to the community a better quality of life. With this in mind, it is reasonable to think that a reliable predictive model is needed. Alas, since both PMDs subtypes prevalence and incidence among general population do not show significant statistical variations, it is not possible to base a predictive model on these data. However, the aim of this paper is to elaborate a novel approach in order to crack the code of PMDs unpredictability.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/955947
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