Literature DB >> 23574478

A systematic review of tests to predict cerebral palsy in young children.

Margot Bosanquet1, Lisa Copeland, Robert Ware, Roslyn Boyd.   

Abstract

AIM: This systematic review evaluates the accuracy of predictive assessments and investigations used to assist in the diagnosis of cerebral palsy (CP) in preschool-age children (<5 y).
METHOD: Six databases were searched for studies that included a diagnosis of CP validated after 2 years of age. The validity of the studies meeting the criteria was evaluated using the Standards for Reporting Diagnostic Accuracy criteria. Where possible, results were pooled and a meta-analysis was undertaken.
RESULTS: Nineteen out of 351 studies met the full inclusion criteria, including studies of general movements assessment (GMA), cranial ultrasound, brain magnetic resonance imaging (MRI), and neurological examination. All studies assessed high-risk populations including preterm (gestational range 23-41 wks) and low-birthweight infants (range 500-4350 g). Summary estimates of sensitivity and specificity of GMA were 98% (95% confidence interval [CI] 74-100%) and 91% (95% CI 83-93%) respectively; of cranial ultrasound 74% (95% CI 63-83%) and 92% (95% CI 81-96%) respectively; and of neurological examination 88% (95% CI 55-97%) and 87% (95% CI 57-97%) respectively. MRI performed at term corrected age (in preterm infants) appeared to be a strong predictor of CP, with sensitivity ranging in individual studies from 86 to 100% and specificity ranging from 89 to 97% There was inadequate evidence for the use of other predictive tools.
SUMMARY: This review found that the assessment with the best evidence and strength for predictive accuracy is the GMA. MRI has a good predictive value when performed at term-corrected age. Cranial ultrasound is as specific as MRI and has the advantage of being readily available at the bedside. Studies to date have focused on high-risk infants. The accuracy of these tests in low-risk infants remains unclear and requires further research. © The Authors. Developmental Medicine & Child Neurology
© 2013 Mac Keith Press.

Entities:  

Mesh:

Year:  2013        PMID: 23574478     DOI: 10.1111/dmcn.12140

Source DB:  PubMed          Journal:  Dev Med Child Neurol        ISSN: 0012-1622            Impact factor:   5.449


  89 in total

1.  Combined predictors of neurodevelopment in very low birth weight preterm infants.

Authors:  Pilar Medina-Alva; Kevin R Duque; Alonso Zea-Vera; Sicilia Bellomo; César Cárcamo; Daniel Guillen-Pinto; Maria Rivas; Alfredo Tori; Jaime Zegarra; Luis Cam; Anne Castañeda; Aasith Villavicencio; Theresa J Ochoa
Journal:  Early Hum Dev       Date:  2019-02-08       Impact factor: 2.079

2.  Computer-based video analysis identifies infants with absence of fidgety movements.

Authors:  Ragnhild Støen; Nils Thomas Songstad; Inger Elisabeth Silberg; Toril Fjørtoft; Alexander Refsum Jensenius; Lars Adde
Journal:  Pediatr Res       Date:  2017-07-26       Impact factor: 3.756

Review 3.  Speech and language interventions for infants aged 0 to 2 years at high risk for cerebral palsy: a systematic review.

Authors:  Olena Chorna; Ellyn Hamm; Caitlin Cummings; Ashley Fetters; Nathalie L Maitre
Journal:  Dev Med Child Neurol       Date:  2016-11-29       Impact factor: 5.449

4.  Early Detection of Cerebral Palsy Using Sensorimotor Tract Biomarkers in Very Preterm Infants.

Authors:  Nehal A Parikh; Alexa Hershey; Mekibib Altaye
Journal:  Pediatr Neurol       Date:  2019-05-09       Impact factor: 3.372

5.  A critical period of corticomuscular and EMG-EMG coherence detection in healthy infants aged 9-25 weeks.

Authors:  Anina Ritterband-Rosenbaum; Anna Herskind; Xi Li; Maria Willerslev-Olsen; Mikkel Damgaard Olsen; Simon Francis Farmer; Jens Bo Nielsen
Journal:  J Physiol       Date:  2017-02-15       Impact factor: 5.182

6.  Validation of an MRI Brain Injury and Growth Scoring System in Very Preterm Infants Scanned at 29- to 35-Week Postmenstrual Age.

Authors:  J M George; S Fiori; J Fripp; K Pannek; J Bursle; R X Moldrich; A Guzzetta; A Coulthard; R S Ware; S E Rose; P B Colditz; R N Boyd
Journal:  AJNR Am J Neuroradiol       Date:  2017-05-18       Impact factor: 3.825

Review 7.  Detection and assessment of brain injury in the growth-restricted fetus and neonate.

Authors:  Atul Malhotra; Michael Ditchfield; Michael C Fahey; Margie Castillo-Melendez; Beth J Allison; Graeme R Polglase; Euan M Wallace; Ryan Hodges; Graham Jenkin; Suzanne L Miller
Journal:  Pediatr Res       Date:  2017-05-17       Impact factor: 3.756

8.  Computer Vision to Automatically Assess Infant Neuromotor Risk.

Authors:  Claire Chambers; Nidhi Seethapathi; Rachit Saluja; Helen Loeb; Samuel R Pierce; Daniel K Bogen; Laura Prosser; Michelle J Johnson; Konrad P Kording
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2020-11-06       Impact factor: 3.802

9.  Network Implementation of Guideline for Early Detection Decreases Age at Cerebral Palsy Diagnosis.

Authors:  Nathalie L Maitre; Vera J Burton; Andrea F Duncan; Sai Iyer; Betsy Ostrander; Sarah Winter; Lauren Ayala; Stephanie Burkhardt; Gwendolyn Gerner; Ruth Getachew; Kelsey Jiang; Laurie Lesher; Carrie M Perez; Melissa Moore-Clingenpeel; Rebecca Lam; Dennis J Lewandowski; Rachel Byrne
Journal:  Pediatrics       Date:  2020-04-08       Impact factor: 7.124

Review 10.  [Developmental neurology - networked medicine and new perspectives].

Authors:  U Tacke; H Weigand-Brunnhölzl; A Hilgendorff; R M Giese; A W Flemmer; H König; B Warken-Madelung; M Arens; N Hesse; A S Schroeder
Journal:  Nervenarzt       Date:  2017-12       Impact factor: 1.214

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