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Early Diagnosis and Differential Diagnosis of Cerebral Palsy

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Cerebral Palsy

Abstract

Cerebral palsy (CP) is a multi-aetiological term, including residua of early brain damage as well as certain nonprogressive genetic conditions. However, progressive diseases such as brain tumours, neurometabolic and neurodegenerative disorders have to be excluded. When the perinatal history is severe and acquired brain damage has been documented, the early diagnosis of cerebral palsy is easy. On the other hand, with an unsuspicious history, the diagnosis of CP usually requires prolonged observation based on adequate developmental tests and neurological examinations.

An early diagnosis and treatment of CP are usually believed to lead to an improved outcome; however for several reasons, this has never been proven with adequate research methods. This chapter gives a short overview on the most important conditions and syndromes that have to be differentiated from CP including some references for further reading.

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References

  1. Herskind A, Greisen G, Nielsen JB. Early identification and intervention in cerebral palsy. Dev Med Child Neurol. 2015;57:29–36.

    Article  PubMed  Google Scholar 

  2. Granild-Jensen JB, Rackauskaite G, Flachs EM, Uldall P. Predictors for early diagnosis of cerebral palsy from national registry data. Dev Med Child Neurol. 2015;57:931–5.

    Article  PubMed  Google Scholar 

  3. Pappas A, Korzeniewski SJ. Long-term cognitive outcomes of birth asphyxia and the contribution of identified perinatal asphyxia to cerebral palsy. Clin Perinatol. 2016;43:559–72.

    Article  PubMed  Google Scholar 

  4. Dubowitz LM, Cowan F, Rutherford M, et al. Neonatal neurology, past present and future. A window on the brain. Brain Dev. 1995;17(Suppl):22–30.

    Article  PubMed  Google Scholar 

  5. Romeo DM, Ricci D, Brogna C, Mercuri E. Use of the Hammersmith Infant Neurological Examination in infants with cerebral palsy: a critical review of the literature. Dev Med Child Neurol. 2016;58:240–5.

    Article  PubMed  Google Scholar 

  6. Pizzardi A, Romeo DM, Cioni M, et al. Infant neurological examination from 3 to 12 months: predictive value of the single items. Neuropediatrics. 2008;39:344–6.

    Article  CAS  PubMed  Google Scholar 

  7. Heineman KR, Bos AF, Hadders-Algra M. The infant motor profile: a standardized and qualitative method to assess motor behaviour in infancy. Dev Med Child Neurol. 2008;50:275–82.

    Article  PubMed  Google Scholar 

  8. Prechtl HFR. State of the art of the new functional assessment of the young nervous system. An early predictor of cerebral palsy. Early Hum Dev. 1997;50:1–11.

    Article  CAS  PubMed  Google Scholar 

  9. Ramin SM, Gilstrap LM III. Other factors/conditions associated with cerebral palsy. Sem Perinatol. 2000;24:196–9.

    Article  CAS  Google Scholar 

  10. Apgar V. The newborn (Apgar) scoring system. Reflections and advice. Pediatr Clin N Am. 1966;13:645–50.

    Article  CAS  Google Scholar 

  11. Amess P, McFerran C, Khan Y, et al. Early prediction of neurological outcome by term neurological examination and cranial ultrasound in very preterm infants. Acta Paediatr. 2009;98:448–53.

    Article  CAS  PubMed  Google Scholar 

  12. Kuban KC, Allred EN, O’Shea TM, et al. Cranial ultrasound lesions in the NICU predict cerebral palsy at age 2 years in children born at extremely low gestational age. J Child Neurol. 2009;24:63–72.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Leijser LM, Vein AA, Liauw L, et al. Prediction of short-term neurological outcome in full-term neonates with hypoxic-ischaemic encephalopathy based on combined use of electroencephalogram and neuro-imaging. Neuropediatrics. 2007;38:219–27.

    Article  CAS  PubMed  Google Scholar 

  14. Murakami A, Morimoto M, Yamade K, et al. Fiber-tracking techniques can predict the degree of neurologic impairment for periventricular leukomalacia. Pediatrics. 2008;122:500–6.

    Article  PubMed  Google Scholar 

  15. Panteliadis CP, Hagel C, Karch D, Heinemann K. Cerebral palsy: a lifelong challenge asks for early intervention. Open Neurol J. 2015;9:45–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kuban KC, Allred EN, O’Shea M, et al. An algorithm for identifying and classifying cerebral palsy in young children. J Pediatr. 2008;153:466–72.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Boennemann CG, Wang CH, Quijano-Roy S, et al. Diagnostic approach to the congenital muscular dystrophies. Neuromuscul Disord. 2014;24:289–11.

    Article  Google Scholar 

  18. Korzeniewski SJ, Birbeck G, DeLano MC, et al. A systematic review of neuroimaging for cerebral palsy. J Child Neurol. 2008;23:216–27.

    Article  PubMed  Google Scholar 

  19. Bax M, Tydeman C, Flodmark O. Clinical and MRI correlates of cerebral palsy: the European cerebral palsy study. JAMA. 2006;296:1602–8.

    Article  CAS  PubMed  Google Scholar 

  20. Ashwal S, Russman BS, Blasco PA, et al. Practice parameter: diagnostic assessment of the child with cerebral palsy. Neurology. 2004;62:851–63.

    Article  CAS  PubMed  Google Scholar 

  21. Huntsman R, Lemire E, Norton J, et al. The differential diagnosis of spastic diplegia. Arch Dis Child. 2015;100:500–4.

    Article  PubMed  Google Scholar 

  22. North KN, Wang CH, Clarke N, et al. Approach to the diagnosis of congenital myopathies. Neuromuscul Disord. 2014;24:97–116.

    Article  PubMed  Google Scholar 

  23. Park S-J, Jung EH, Ryu R-S, et al. The clinical application of array CGH for the detection of chromosomal defects in 20,126 unselected newborns. Mol Cytogenet. 2013;6:21. http://www.molecularcytogenetics.org/content/6/1/21

    Article  PubMed  PubMed Central  Google Scholar 

  24. Volpe JJ. Brain injury in premature infants a complex amalgam of destructive and developmental disturbances. Lancet Neurol. 2009;8:110–28.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Tarsy D, Simon DK. Dystonia. N Engl J Med. 2006;355:818–29.

    Article  CAS  PubMed  Google Scholar 

  26. van Egmont ME, Kuiper A, Eggink H, et al. Dystonia in children and adolescents: a systematic review and a new diagnostic algorithm. J Neurol Neurosurg Psychiatry. 2015;86:774–81.

    Article  Google Scholar 

  27. Segawa M, Nomura Y, Nishiyama N. Autosomal dominant guanosine triphosphate cyclohydrolase I deficiency (Segawa disease). Ann Neurol. 2003;54:S32–45.

    Article  CAS  PubMed  Google Scholar 

  28. Kurian MA, Gissen P, Smith M, et al. The monoamine neurotransmitter disorders: an expanding range of neurological syndromes. Lancet Neurol. 2011;10:721–33.

    Article  CAS  PubMed  Google Scholar 

  29. Finsterer J, Löscher W, Quasthoff S, et al. Hereditary spastic paraplegias with autosomal dominant, recessive, X-linked, or maternal trait of inheritance. J Neurol Sci. 2012;318:1–18.

    Article  PubMed  Google Scholar 

  30. de Bot ST, van de Warrenburg BPC, Kremer HPH, et al. Child neurology. Hereditary spastic paraplegia in children. Neurology. 2010;75:e75.

    Article  PubMed  Google Scholar 

  31. Boycott KM, Bonnemann C, Herz J, et al. Mutations in VLDLR as a cause for autosomal recessive cerebellar ataxia with mental retardation (disequilibrium syndrome). J Child Neurol. 2009;24:1310–5.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Fogel BI, Perlman S. Clinical features and molecular genetics of autosomal recessive cerebellar ataxias. Lancet Neurol. 2007;6:245–57.

    Article  CAS  PubMed  Google Scholar 

  33. Sailer A, Houlden H. Recent advances in the genetics of cerebellar ataxias. Curr Neurol Neurosci Rep. 2012;12:227–36.

    Article  CAS  PubMed  Google Scholar 

  34. Kennedy AD, Miller MJ, Beebe K, et al. Metabolomic profiling of human urine as a screen for multiple inborn errors of metabolism. Genet Test Mol Biomarkers. 2016;20:485–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Korinthenberg R, Panteliadis CP, Hagel C, editors. Neuropädiatrie—evidenzbasierte Therapie. 2nd ed. Munich: Elsevier; 2014.

    Google Scholar 

  36. Tebani A, Abily-Donval L, Afonso C, et al. Clinical metabolomics: the new metabolic window for inborn errors of metabolism investigations in the post-genomic era. Int J Mol Sci. 2016;17(7):1167. https://doi.org/10.3390/ijms17071167.

    Article  PubMed Central  Google Scholar 

  37. Gordon N. Alexander disease. Eur J Pediatr Neurol. 2003;7:395–9.

    Article  Google Scholar 

  38. Kohlschütter A, Eichler F. Childhood leukodystrophies: a clinical perspective. Expert Rev Neurother. 2011;11:1485–96.

    Article  PubMed  Google Scholar 

  39. Ziereisen F, Dan B, Christiaens F, et al. Connatal Pelizaeus-Merzbacher disease in two girls. Pediatr Radiol. 2000;30:435–8.

    Article  CAS  PubMed  Google Scholar 

  40. Wang PJ, Hwu WL, Shen YZ. Epileptic seizures and electroencephalographic evolution in genetic leukodystrophies. J Clin Neurophysiol. 2001;18:25–32.

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Rudolf Korinthenberg .

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Korinthenberg, R., Panteliadis, C.P. (2018). Early Diagnosis and Differential Diagnosis of Cerebral Palsy. In: Panteliadis, C. (eds) Cerebral Palsy. Springer, Cham. https://doi.org/10.1007/978-3-319-67858-0_11

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  • DOI: https://doi.org/10.1007/978-3-319-67858-0_11

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  • Online ISBN: 978-3-319-67858-0

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