Literature DB >> 26307381

Empirical Derivation and Validation of a Clinical Case Definition for Neuropsychological Impairment in Children and Adolescents.

Miriam H Beauchamp1, Brian L Brooks2, Nick Barrowman3, Mary Aglipay4, Michelle Keightley5, Peter Anderson6, Keith O Yeates7, Martin H Osmond8, Roger Zemek8.   

Abstract

Neuropsychological assessment aims to identify individual performance profiles in multiple domains of cognitive functioning; however, substantial variation exists in how deficits are defined and what cutoffs are used, and there is no universally accepted definition of neuropsychological impairment. The aim of this study was to derive and validate a clinical case definition rule to identify neuropsychological impairment in children and adolescents. An existing normative pediatric sample was used to calculate base rates of abnormal functioning on eight measures covering six domains of neuropsychological functioning. The dataset was analyzed by varying the range of cutoff levels [1, 1.5, and 2 standard deviations (SDs) below the mean] and number of indicators of impairment. The derived rule was evaluated by bootstrap, internal and external clinical validation (orthopedic and traumatic brain injury). Our neuropsychological impairment (NPI) rule was defined as "two or more test scores that fall 1.5 SDs below the mean." The rule identifies 5.1% of the total sample as impaired in the assessment battery and consistently targets between 3 and 7% of the population as impaired even when age, domains, and number of tests are varied. The NPI rate increases in groups known to exhibit cognitive deficits. The NPI rule provides a psychometrically derived method for interpreting performance across multiple tests and may be used in children 6-18 years. The rule may be useful to clinicians and scientists who wish to establish whether specific individuals or clinical populations present within expected norms versus impaired function across a battery of neuropsychological tests.

Entities:  

Keywords:  Assessment; Brain injury; Cognition; Neuropsychology; Pediatric; Performance

Mesh:

Year:  2015        PMID: 26307381     DOI: 10.1017/S1355617715000636

Source DB:  PubMed          Journal:  J Int Neuropsychol Soc        ISSN: 1355-6177            Impact factor:   2.892


  5 in total

1.  Long-term neuropsychological follow-up of young children with medulloblastoma treated with sequential high-dose chemotherapy and irradiation sparing approach.

Authors:  Taryn B Fay-McClymont; Danielle M Ploetz; Don Mabbott; Karin Walsh; Amy Smith; Susan N Chi; Elizabeth Wells; Jennifer Madden; Ashley Margol; Jonathan Finlay; Mark W Kieran; Douglas Strother; Girish Dhall; Roger J Packer; Nicholas K Foreman; E Bouffet; Lucie Lafay-Cousin
Journal:  J Neurooncol       Date:  2017-04-12       Impact factor: 4.130

2.  Optimizing Neurocritical Care Follow-Up Through the Integration of Neuropsychology.

Authors:  Jonathan N Dodd; Trevor A Hall; Kristin Guilliams; Réjean M Guerriero; Amanda Wagner; Sara Malone; Cydni N Williams; Mary E Hartman; Juan Piantino
Journal:  Pediatr Neurol       Date:  2018-09-18       Impact factor: 3.372

3.  Key Stakeholder Priorities for the Review and Update of the Australian Guide to Diagnosis of Fetal Alcohol Spectrum Disorder: A Qualitative Descriptive Study.

Authors:  Nicole Hayes; Lisa K Akison; Sarah Goldsbury; Nicole Hewlett; Elizabeth J Elliott; Amy Finlay-Jones; Dianne C Shanley; Kerryn Bagley; Andi Crawford; Haydn Till; Alison Crichton; Rowena Friend; Karen M Moritz; Raewyn Mutch; Sophie Harrington; Andrew Webster; Natasha Reid
Journal:  Int J Environ Res Public Health       Date:  2022-05-10       Impact factor: 4.614

4.  Neuropsychological Impairment, Brain Injury Symptoms, and Health-Related Quality of Life After Pediatric TBI in Oslo.

Authors:  Ingvil Laberg Holthe; Hilde Margrete Dahl; Nina Rohrer-Baumgartner; Sandra Eichler; Marthe Fjellheim Elseth; Øyvor Holthe; Torhild Berntsen; Keith Owen Yeates; Nada Andelic; Marianne Løvstad
Journal:  Front Neurol       Date:  2022-01-28       Impact factor: 4.003

5.  Structural-covariance networks identify topology-based cortical-thickness changes in children with persistent executive function impairments after traumatic brain injury.

Authors:  Daniel J King; Stefano Seri; Cathy Catroppa; Vicki A Anderson; Amanda G Wood
Journal:  Neuroimage       Date:  2021-09-23       Impact factor: 6.556

  5 in total

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