2018
DOI: 10.3233/jnd-180304
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Treatment Algorithm for Infants Diagnosed with Spinal Muscular Atrophy through Newborn Screening

Abstract: Background:Spinal muscular atrophy (SMA) is an autosomal recessive disease characterized by the degeneration of alpha motor neurons in the spinal cord, leading to muscular atrophy. SMA is caused by deletions or mutations in the survival motor neuron 1 gene (SMN1). In humans, a nearly identical copy gene, SMN2, is present. Because SMN2 has been shown to decrease disease severity in a dose-dependent manner, SMN2 copy number is predictive of disease severity.Objective:To develop a treatment algorithm for SMA-posi… Show more

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Cited by 155 publications
(156 citation statements)
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“…Currently, the initial attempt to solve this dilemma was to find consensus on the opinion of experts assessed via the Delphi questionnaire [16]. Unfortunately, the expert group did not find a definite answer to the question of which children should be treated.…”
Section: Discussionmentioning
confidence: 99%
See 3 more Smart Citations
“…Currently, the initial attempt to solve this dilemma was to find consensus on the opinion of experts assessed via the Delphi questionnaire [16]. Unfortunately, the expert group did not find a definite answer to the question of which children should be treated.…”
Section: Discussionmentioning
confidence: 99%
“…MLPA was repeated again in 2020 with an improved MPLA-test. The patients were advised according to the treatment algorithm published by the American SMA NBS Multidisciplinary Working Group [16].…”
Section: Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…Additional NBS efforts for SMA are ongoing globally and are supported by the general population in several countries [17-19 , 38 , 39] . A treatment algorithm based on SMN2 copy number for SMA positive infants identified though NBS was recently developed by a group of SMA experts [40] . The recommendation was for infants with two or three SMN2 copies to receive immediate treatment following confirmatory testing.…”
Section: Discussionmentioning
confidence: 99%