Search

Hunter syndrome, or mucopolysaccharidosis (MPS) II, is a rare lysosomal disorder characterized by progressive, multi-system disease. As most symptoms cannot be reversed once established, early detection and treatment prior to the onset of clinical symptoms are critical. However, it is difficult to identify affected individuals early in disease, and therefore the long-term outcomes of initiating treatment during this optimal time period are incompletely described. We report long-term clinical outcomes of treatment when initiated prior to obvious clinical signs by comparing the courses of two siblings with neuronopathic Hunter syndrome (c.1504 T > G[p.W502G]), one who was diagnosed due to clinical disease (Sibling-O, age 3.7 years) and the other who was diagnosed before disease was evident (Sibling-Y, age 12 months), due to his older sibling's findings. The brothers began enzyme replacement therapy within a month of diagnosis. Around the age of 5 years, Sibling-O had a cognitive measurement score in the impaired range of

Abstract Background Mucopolysaccharidosis II (MPS II) is a rare lysosomal storage disease characterized by cognitive impairment in most patients. This post hoc analysis evaluated changes in cognitive function, adaptive behavior and functional outcomes in patients with neuronopathic MPS II over time. Fifty-five children with MPS II were enrolled in a 24-month observational study (NCT01822184). The Differential Ability Scales, second edition (DAS-II; early years battery for ages 2 years 6 months to 6 years 11 months, school age battery for ages 7 years to 17 years 11 months), Vineland Adaptive Behavior Scales, second edition (VABS-II) and the Hunter Syndrome-Functional Outcomes for Clinical Understanding Scale (HS-FOCUS) were performed at baseline and 3-month intervals over 2 years. A subgroup of 38 children with a DAS-II General Conceptual Ability (GCA) score of 55–85 (below average–very low abilities) at any time during the study were included in this analysis. Results Mean (standard deviation [SD]) early years DAS-II GCA score decreased from 73.4 (15.7, n = 22) at baseline to 62.7 (34.9, n = 6) at month 24. For the six patients with early years GCA assessments at baseline and month 24, mean (SD) GCA scores decreased from 72.3 (21.3) at baseline to 62.7 (34.9) at month 24. School age GCA scores were stable over 2 years: mean (SD) 72.4 (11.8, n = 10) at baseline; 74.3 (12.3, n = 8) at month 24. Mean (SD) VABS-II Adaptive Behavior Composite (ABC) scores were stable throughout the study (baseline, 81.8 [11.8, n = 36]; month 24, 81.0 [10.2, n = 13]). Some associations between items and domains of HS-FOCUS (p

Background: Mucopolysaccharidosis II (MPS II) is a rare lysosomal storage disease characterized by cognitive impairment in most patients. This post hoc analysis evaluated changes in cognitive function, adaptive behavior and functional outcomes in patients with neuronopathic MPS II over time. Fifty-five children with MPS II were enrolled in a 24-month observational study (NCT01822184). The Differential Ability Scales, second edition (DAS-II; early years battery for ages 2 years 6 months to 6 years 11 months, school age battery for ages 7 years to 17 years 11 months), Vineland Adaptive Behavior Scales, second edition (VABS-II) and the Hunter Syndrome-Functional Outcomes for Clinical Understanding Scale (HS-FOCUS) were performed at baseline and 3-month intervals over 2 years. A subgroup of 38 children with a DAS-II General Conceptual Ability (GCA) score of 55-85 (below average-very low abilities) at any time during the study were included in this analysis.Results: Mean (standard deviation [SD]) early years DAS-II GCA score decreased from 73.4 (15.7, n = 22) at baseline to 62.7 (34.9, n = 6) at month 24. For the six patients with early years GCA assessments at baseline and month 24, mean (SD) GCA scores decreased from 72.3 (21.3) at baseline to 62.7 (34.9) at month 24. School age GCA scores were stable over 2 years: mean (SD) 72.4 (11.8, n = 10) at baseline; 74.3 (12.3, n = 8) at month 24. Mean (SD) VABS-II Adaptive Behavior Composite (ABC) scores were stable throughout the study (baseline, 81.8 [11.8, n = 36]; month 24, 81.0 [10.2, n = 13]). Some associations between items and domains of HS-FOCUS (p < 0.05) and DAS-II GCA and VABS-II ABC scores were shown, but there was no clear pattern of changes in HS-FOCUS over 2 years.Conclusions: The DAS-II measured changes in cognitive function over 2 years in younger patients with MPS II, whereas cognitive function in older patients remained stable. Further research is required to confirm the content validity of the DAS-II in different patient populations with MPS II. The VABS-II and HS-FOCUS were not sensitive tools for measuring behavioral and functional changes over 2 years. These findings may inform selection of appropriate cognitive and behavioral assessment tools for future studies. [ABSTRACT FROM AUTHOR]

Intelligence assessment is an integral part of a comprehensive autism evaluation. Many past studies have described a cognitive profile of autistic individuals characterized by higher nonverbal than verbal IQ scores. The diagnostic utility of this profile, however, remains unknown. We leveraged receiver operating characteristic methods to determine the sensitivity, specificity, and area under the curve (AUC) of three different IQ profiles in a large sample of children who have an autism spectrum disorder diagnosis (N = 1,228, Simons Simplex Collection) who completed the Differential Ability Scales—Second Edition (DAS‐II), School Age compared to the normative sample provided by the DAS‐II publisher (N = 2,200). The frequently discussed nonverbal > verbal IQ profile performed near chance at distinguishing ASD from normative individuals (AUC: 0.54, 95% CI [0.52–0.56]), and performed significantly worse for females than males (AUC: females: 0.46 [0.41–0.52]; males: 0.55 [0.53–0.58]). All cognitive profiles showed AUC < 0.56. We conclude that while significant differences between verbal and nonverbal IQ scores exist at the group level, these differences are small in an absolute sense and not meaningful at an individual level. We do not recommend using cognitive profiles to aid in autism diagnostic decision‐making. Lay Summary Some researchers and clinicians have reported an "autistic cognitive profile" of higher nonverbal intelligence than verbal intelligence. In an analysis of over 1,000 autistic children, we found that the group's average nonverbal intelligence is usually higher than their verbal intelligence. However, this pattern should not be used by clinicians to make an individual diagnosis of autism because our results show it is not helpful nor accurate. [ABSTRACT FROM AUTHOR]

The present study examined the factor structure of the Differential Ability Scales--Second Edition (DAS-II) core subtests from the standardization sample via confirmatory factor analysis (CFA) using methods (bifactor modeling and variance partitioning) and procedures (robust model estimation due to nonnormal subtest score distributions) recommended but not included in the DAS-II Introductory and Technical Handbook. CFAs were conducted with the three DAS-II standardization sample age groups (lower early years [age = 2:6-3:5 years], upper early years [age = 3:6-6:11 years], school age [7:0-17:11 years]) using standardization sample raw data provided by NCS Pearson, Inc. Although most DAS-II core subtests were properly associated with the theoretically proposed group factors, both the higher order and bifactor models indicated that the g factor accounted for large portions of total and common variance, whereas the group factors (Verbal, Nonverbal, Spatial) accounted for small portions of total and common variance. The DAS-II core battery provides strong measurement of general intelligence, and clinical interpretation should be primarily, if not exclusively, at that level. [ABSTRACT FROM AUTHOR]

When the Differential Ability Scales–Second Edition (DAS-II) was developed, the instrument's content, structure, and theoretical orientation were amended. Despite these changes, the Technical Handbook did not report results from exploratory factor analytic investigations, and confirmatory factor analyses were implemented using selected subtests across the normative age groups from the total battery. To address these omissions, the present study investigated the theoretical structure of the DAS-II using principal axis factoring followed by the Schmid–Leiman procedure with participants from the 5- to 8-year-old age range to determine the degree to which the DAS-II theoretical structure proposed in the Technical Handbook could be replicated. Unlike other age ranges investigated where at most 14 subtests were administered, the entire DAS-II battery was normed on participants aged 5 to 8 years, making it well suited to test the full instrument's alignment with theory. Results suggested a six-factor solution that was essentially consistent with the Cattell–Horn–Carroll (CHC)-based theoretical structure suggested by the test publisher and simple structure was attained. The only exception involved two subtests (Picture Similarities and Early Number Concepts) that did not saliently load on a group factor. Implications for clinical practice are discussed. [ABSTRACT FROM AUTHOR]

The present study examined the factor structure of the Differential Ability Scales-Second Edition (DAS-II; Elliott, 2007a) standardization sample using exploratory factor analyses, multiple factor extraction criteria, and hierarchical exploratory factor analyses (Schmid & Leiman, 1957) not included in the DAS-II Introductory and Technical Handbook (Elliott, 2007b). Exploratory factor analyses with multiple factor extraction criteria and hierarchical analyses with the Schmid and Leiman (1957) procedure were conducted with the 3 DAS-II standardization samples (Lower Early Years [Ages 2:6-3:5], Upper Early Years [Ages 3:6-6:11], School-Age [Ages 7:0-17:11]). All factor extraction criteria suggested 1 factor despite the author and publisher recommended and promoted 2 (Ages 2:6-3:5) or 3 (Ages 3:6-6:11, Ages 7:0-17:11) factors. Results indicated that most DAS-II subtests were properly associated with the theoretically proposed first-order factors. Hierarchical exploratory analyses with the Schmid and Leiman procedure, however, found that the hierarchical g factor accounted for large portions of total and common variance, while the 2 or 3 first-order factors accounted for small portions of total and common variance. It was concluded that the DAS-II provides strong measurement of general intelligence but clinical interpretation should be primarily at that level. (PsycINFO Database Record [ABSTRACT FROM AUTHOR]

Estimates of intelligence in young children with neurodevelopmental disorders are critical for making diagnoses, in characterizing symptoms of disorders, and in predicting future outcomes. The limitations of standardized testing for children with developmental delay or cognitive impairment are well known: Tests do not exist that provide developmentally appropriate material along with norms that extend to the lower reaches of ability. Two commonly used and interchanged instruments are the Mullen Scales of Early Learning (MSEL), a test of developmental level, and the Differential Ability Scales, second edition (DAS-II), a more traditional cognitive test. We evaluated the correspondence of contemporaneous MSEL and the DAS-II scores in a mixed sample of children aged 2–10 years with autism spectrum disorder (ASD), non-ASD developmental delays, and typically developing children across the full spectrum of cognitive ability. Consistent with published data on the original DAS and the MSEL, scores on the DAS-II and MSEL were highly correlated. However, curve estimation revealed large mean differences that varied as a function of the child’s cognitive ability level. We conclude that interchanging MSEL and DAS-II scores without regard to the discrepancy in scores may produce misleading results in both cross-sectional and longitudinal studies of children with and without ASD, and, thus, this practice should be implemented with caution. [ABSTRACT FROM PUBLISHER]

Intelligence assessment is an integral part of a comprehensive autism evaluation. Many past studies have described a cognitive profile of autistic individuals characterized by higher nonverbal than verbal IQ scores. The diagnostic utility of this profile, however, remains unknown. We leveraged receiver operating characteristic methods to determine the sensitivity, specificity, and area under the curve (AUC) of three different IQ profiles in a large sample of children who have an autism spectrum disorder diagnosis (N = 1,228, Simons Simplex Collection) who completed the Differential Ability Scales-Second Edition (DAS-II), School Age compared to the normative sample provided by the DAS-II publisher (N = 2,200). The frequently discussed nonverbal > verbal IQ profile performed near chance at distinguishing ASD from normative individuals (AUC: 0.54, 95% CI [0.52-0.56]), and performed significantly worse for females than males (AUC: females: 0.46 [0.41-0.52]; males: 0.55 [0.53-0.58]). All cognitive profiles showed AUC < 0.56. We conclude that while significant differences between verbal and nonverbal IQ scores exist at the group level, these differences are small in an absolute sense and not meaningful at an individual level. We do not recommend using cognitive profiles to aid in autism diagnostic decision-making. LAY SUMMARY: Some researchers and clinicians have reported an "autistic cognitive profile" of higher nonverbal intelligence than verbal intelligence. In an analysis of over 1,000 autistic children, we found that the group's average nonverbal intelligence is usually higher than their verbal intelligence. However, this pattern should not be used by clinicians to make an individual diagnosis of autism because our results show it is not helpful nor accurate., (© 2020 International Society for Autism Research, Wiley Periodicals LLC.)

Background: This study aimed to assess the sensitivity and specificity of the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III), Cognitive and Language scales at 24 months for predicting cognitive impairments in preterm children at 4 years., Methods: Children born <30 weeks' gestation completed the Bayley-III at 24 months and the Differential Ability Scale, Second Edition (DAS-II), at 4 years to assess cognitive functioning. Test norms and local term-born reference data were used to classify delay on the Bayley-III Cognitive and Language scales. Impairment on the DAS-II Global Conceptual Ability, Verbal, and Nonverbal Reasoning indices was classified relative to test norms. Scores < -1 SD relative to the mean were classified as mild/moderate delay or impairment, and scores < -2 SDs were classified as moderate delay or impairment., Results: A total of 105 children completed the Bayley-III and DAS-II. The sensitivity of mild/moderate cognitive delay on the Bayley-III for predicting impairment on DAS-II indices ranged from 29.4% to 38.5% and specificity ranged from 92.3% to 95.5%. The sensitivity of mild/moderate language delay on the Bayley-III for predicting impairment on DAS-II indices ranged from 40% to 46.7% and specificity ranged from 81.1% to 85.7%. The use of local reference data at 24 months to classify delay increased sensitivity but reduced specificity. Receiver operating curve analysis identified optimum cut-point scores for the Bayley-III that were more consistent with using local reference data than Bayley-III normative data., Conclusions: In our cohort of very preterm children, delay on the Bayley-III Cognitive and Language scales was not strongly predictive of future impairments. More children destined for later cognitive impairment were identified by using cut-points based on local reference data than Bayley-III norms., (Copyright © 2015 by the American Academy of Pediatrics.)