Detecting epilepsy‐related cognitive problems in clinically referred children with epilepsy: Is the WISC‐IV a useful tool?
Bibliographic record
Abstract
PURPOSE: The Wechsler Intelligence Scale for Children - Fourth Edition is the most widely used intelligence quotient (IQ) test in use today. However, despite numerous studies on IQ in childhood epilepsy, data exist almost exclusively from prior editions of the test, and no studies to date provide information on the sensitivity of specific WISC-IV scores (full-scale IQ [FSIQ], index, and subtest scores) to epilepsy-related cognitive impairments. The goal of this study was to determine the relative sensitivity of WISC-IV index and subscale scores in detecting cognitive problems in a group of clinically referred children with epilepsy compared to matched controls, and to define the relationship among WISC-IV scales, demographic factors, and epilepsy-related variables. METHODS: WISC-IV data for children with epilepsy and high seizure burden were obtained from the Alberta Children's Hospital (ACH) and the New York University Comprehensive Epilepsy Center (NYU), two tertiary care medical centers for pediatric epilepsy. All children were clinically referred and received a standard assessment including WISC-IV. Matched controls were obtained from the WISC-IV Canadian and American standardization samples. KEY FINDINGS: WISC-IV scores from 212 children were included: 106 children with epilepsy (46 girls, 60 boys; mean age 11.0 years, standard deviation [SD] 3.1; parental education 14.5 years, SD 2.8), and 106 controls matched for age, gender, ethnicity, and parental education. Of the children with epilepsy, 44 had a clearly lateralized focus on electroencephalography (EEG) involving either the right or left hemisphere (26 left, 18 right). FSIQ for the epilepsy group was significantly lower than for controls, and 36.8% of children had IQs compatible with intellectual disability (FSIQ < 70), versus <1% of controls. In children with epilepsy, Working Memory and Processing Speed Index scores were lower than those for Verbal Comprehension and Perceptual Reasoning (p < 0.01). At the subtest level, scores for children with epilepsy were highest on visual and verbal subtests measuring reasoning skills such as Matrix Reasoning, and lowest on Coding (mean 5.93, SD 3.6). In terms of percentage of children on each subtest with low scores (i.e., scores below 2 SDs from the expected normative mean of 10), the Coding subtest identified the most children (28.3%) with low scores, and the Similarities subtest identified the fewest (16%). Later age at onset and shorter epilepsy duration were both correlated with higher WISC-IV FSIQ and index scores (r correlation coefficient values ranging from 0.36 to 0.44, p < 0.0001), and number of current and previous antiepileptic drug trials were both inversely correlated with FSIQ and index scores (r -0.27 to -0.47, all p-values < 0.01). Neither the FSIQ nor the index scores were significantly related to seizure frequency. A similar pattern was found for subtest scores. No differences in FSIQ, index scores, or subtest scores were found between children with left- and right-hemisphere seizure foci, or between those with positive or negative magnetic resonance imaging (MRI) findings. SIGNIFICANCE: The WISC-IV is sensitive to epilepsy-related cognitive problems in clinically referred children with high seizure burden, particularly problems relating to expressive verbal, working memory, and processing speed difficulties. Compared to healthy children, these children have a very high rate of cognitive difficulties as assessed by the WISC-IV. The usefulness of the WISC-IV in detecting cognitive deficits in children with milder forms of epilepsy remains to be determined.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".