79 Concordance Between Theorized Cognitive Profiles, Medical Risk Factors, and Clinical Diagnoses Within Preschool-Aged Children

Abstract

Objective:

Early childhood is recognized as a critical window of rapid cognitive development. Unfortunately, many risk factors for atypical cognitive development may occur during this period, including genetic syndromes, congenital neuroanatomical malformations, pre- or perinatal injury, and neurological and medical disorders. The impact of these risk factors on cognitive functioning may not always map onto patterns typically observed in adults. Limited literature exists on the presentation of cognitive profiles within clinical populations in the preschool developmental period. The present study aimed to evaluate whether discrete a priori cognitive profiles consistent with common neurobehavioral syndromes emerge and are distinguishable on testing in early childhood in a mixed clinical sample. We also aimed to determine if there was a consistent association between known medical risk factors and resultant cognitive profiles.

Participants and Methods:

Participants included 163 children aged 1-5 years (M=48.5 months, SD=12.8 months) referred for neuropsychological evaluation. The sample was predominantly male (67.5%) and White (72.9%), followed by other/mixed race (11.6%), Black (9.7%), and Latino/Hispanic (5.8%). Cognitive abilities assessed included broad intellectual abilities, verbal abilities, nonverbal abilities, attention, and executive functioning. Continuous test scores were transformed into categorical ranges of performance, with scores classified as “above average,” “average,” “below average,” or “extremely low” to allow for profile classification. Theoretical clinical profiles consistent with common neurobehavioral syndromes were determined a priori by consensus among three authors (JK, AH, LM). Chi square tests of independence were conducted to compare membership across neurobehavioral diagnostic groups, clinical profile groups, and medical groups.

Results:

Based on cognitive data, 55.2% of the sample (n=90) was classified as Global Developmental Delay/Intellectual Disability, 19.6% (GDD/ID; n=32) was classified as

Language Disorder, and 18.4% (n=30) was classified as Typical Cognitive Development. 4.3% (n=7) of the sample was classified as Attention-Deficit/Hyperactivity Disorder (ADHD), and 2.5% (n=4) was classified as Nondominant Hemisphere Dysfunction. As hypothesized, cognitive profile group membership was consistent with diagnostic impressions, as actual clinical diagnoses of Language Disorder, ADHD, GDD/ID, or a classification of typical cognitive development were significantly associated with theorized cognitive profile based on test performance alone (x² (1,20) = 147.29, p < .001). Cognitive profile group membership was also significantly associated with referral source (1,28) = 62.88, p < .001) and the presence of a neurological disorder (1,4) = 14.64, p =.006).

Conclusions:

Findings support the presence of specific theorized cognitive profiles in preschoolers in a mixed clinical sample. Specifically, GDD/ID, Language Disorder, and typical cognitive development are discrete and consistently distinguishable cognitive profiles in this age range. Early life neurological risk factors are also significantly related to cognitive profile membership, suggesting that these factors may be useful in predicting cognitive development even in very young children. Future work is needed to examine the consistency of these profiles over time and their predictive value in estimating subsequent development, and the possibility of discriminating unique cognitive profiles for specific medical conditions in preschoolers.