Title of article :
Approach to Patients with Neurometabolic Diseases Who Show Characteristic Signs and Symptoms
Author/Authors :
KARIMZADEH, Parvaneh Department of Pediatric Neurology - Pediatric Neurology Research Center - Research Institute for Children’s Health - Shahid Beheshti University of Medical Sciences, Tehran, Iran. , GHOFRANI, Mohammad Department of Pediatric Neurology - Pediatric Neurology Research Center - Research Institute for Children’s Health - Shahid Beheshti University of Medical Sciences, Tehran, Iran , NASIRI, Shahram Department of Paediatric Neurology - Abuzar children’s medical center - Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Abstract :
Neurometabolic disorders are hereditary conditions mainly affect
the function of the brain and the nervous system. The prevalence of
these disorders is 1 in 1,000 live births. Such disorders, at different
ages, could manifest as sepsis, hypoglycemia, and other neurologic
disorders. Having similar manifestations leads to delayed diagnosis
of neurometabolic disorders. A number of neurometabolic disorders
have known treatments; however, to prevent long-term complications
the key factors are early diagnosis and treatment. Although a large
number of neurometabolic diseases have no treatment or cure, the
correct and on-time diagnosis before death is important for parents
to have plans for prenatal diagnosis. Different diagnostic procedures
could be offered to parents, enzymatic procedures, and determining
metabolites in plasma, urine, and CSF, and molecular genetic
diagnosis. Molecular genetic diagnostic procedures are expensive
and could not be offered to all parents. Therefore, we aimed to
design algorithms to diagnose neurometabolic disorders according to
some frequent and characteristic signs and symptoms. By designing
these algorithms and using them properly, we could offer diagnostic
enzymatic panels. These enzymatic panels are inexpensive; thereby
reducing the financial burden on the parents. Also, having an early
diagnosis according to these panels could lead to offering more
accurate and less expensive molecular genetic tests.
Keywords :
Neurometabolic disorders , children , enzymatic panels , algorithms , diagnosis
Journal title :
Iranian Journal of Child Neurology (IJCN)