Objective: The purpose of this study was to examine the risks associated with learning disabilities (LDs) in a large sample of children born extremely preterm. We predicted higher than expected rates of LD, particularly in math, and children with LD in math, reading, or both would have lower intelligence quotients (IQs) and specific patterns of neuropsychological deficits.
Methods: We evaluated academic achievement, rates of LD, and their neuropsychological correlates in the Extremely Low Gestational Age Newborns (ELGANs) Study cohort of 10-year-old children born at 23 to 27 weeks gestational age. Primary analyses focused on children without intellectual disability (verbal IQ > 70 and nonverbal IQ > 70; N = 668). Low achievement was defined as a standard score ≤85 on the reading or math measures.
Results: The risk of low math achievement scores (27%) was 1.5 times higher than the risk of low reading achievement scores (17%). Children were classified as having LD based on low achievement criteria in reading only (RD, 6.4% of sample), math only (MD, 16.2%), both reading and math (RD/MD, 8.3%), or no reading or math disabilities (No LD, 69.1%). Although all 3 LD groups had multiple neuropsychological weaknesses compared with the No LD group, the RD and MD groups had different patterns of neuropsychological impairment.
Conclusion: These children from the ELGAN cohort had higher than expected rates of LD, particularly in mathematics, even after taking socioeconomic status into consideration. These results indicate specific cognitive weaknesses that differ between extremely preterm children with RD and MD.
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*Department of Psychiatry and Center for Human Development, University of California, San Diego, La Jolla, CA;
†Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA;
‡Department of Pediatrics, Case Western Reserve University and Rainbow Babies & Children's Hospital, University Hospitals Case Medical Center, Cleveland, OH;
§Department of Neurology, Harvard Medical School, Boston, MA;
‖Neuroepidemiology Unit, Department of Neurology, Boston Children's Hospital, Boston, MA;
¶Department of Biostatistics, Boston University School of Public Health, Boston, MA;
**Department of Pediatrics, University of North Carolina, Chapel Hill, NC;
††Department of Pediatrics, Division of Pediatric Neurology, Boston University Medical Center, Boston, MA.
Address for reprints: Natacha Akshoomoff, PhD, Department of Psychiatry, 9500 Gilman Dr, La Jolla, CA 92093-0115; e-mail: email@example.com.
Supported by grants from the National Institutes of Health (5U01NS040069, 2R01NS040069, 5P30HD018655, and 1UG3OD023348–1); N. Akshoomoff was supported by grants from the National Institutes of Health (5R01HD075765, 5R24HD075489, and 5R01HD061414).
Disclosure: The authors declare no conflict of interest.
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Received March , 2017
Accepted May , 2017