Department of Neurology, University of California Davis, Sacramento, CA 95817, USA.
Department of Public Health Sciences, University of California Davis, Davis, CA 95616, USA.
Epilepsy Behav. 2024 May;154:109742. doi: 10.1016/j.yebeh.2024.109742. Epub 2024 Mar 29.
Children with new-onset epilepsies often exhibit co-morbidities including cognitive dysfunction, which adversely affects academic performance. Application of unsupervised machine learning techniques has demonstrated the presence of discrete cognitive phenotypes at or near the time of diagnosis, but there is limited knowledge of their longitudinal trajectories. Here we investigate longitudinally the presence and progression of cognitive phenotypes and academic status in youth with new-onset seizures as sibling controls.
282 subjects (6-16 years) were recruited within 6 weeks of their first recognized seizure along with 167 unaffected siblings. Each child underwent a comprehensive neuropsychological assessment at baseline, 18 and 36 months later. Factor analysis of the neuropsychological tests revealed four underlying domains - language, processing speed, executive function, and verbal memory. Latent trajectory analysis of the mean factor scores over 36 months identified clusters with prototypical cognitive trajectories.
Three unique phenotypic groups with distinct cognitive trajectories over the 36-month period were identified: Resilient, Average, and Impaired phenotypes. The Resilient phenotype exhibited the highest neuropsychological factor scores and academic performance that were all similar to controls; while the Impaired phenotype showed the polar opposite with the worst performances across all test metrics. These findings remained significant and stable over 36 months. Multivariate logistic regression indicated that age of onset, EEG, neurological examination, and sociodemographic disadvantage were associated with phenotype classification.
This study demonstrates the presence of diverse latent cognitive trajectory phenotypes over 36 months in youth with new-onset seizures that are associated with a stable neuropsychological and academic performance longitudinally.
新诊断癫痫的儿童常伴有认知功能障碍等合并症，这会对学习成绩产生不利影响。无监督机器学习技术的应用已经证明，在诊断时或接近诊断时存在离散的认知表型，但对其纵向轨迹知之甚少。在这里，我们研究了新诊断癫痫患儿和无癫痫的同胞对照者在认知表型和学业状况方面的纵向变化。
在首次确诊癫痫后 6 周内，共招募了 282 名（6-16 岁）患者和 167 名未受影响的同胞。每个孩子在基线、18 个月和 36 个月后都接受了全面的神经心理学评估。神经心理学测试的因子分析揭示了四个潜在的领域：语言、处理速度、执行功能和言语记忆。36 个月内平均因子分数的潜在轨迹分析确定了具有典型认知轨迹的聚类。
在 36 个月的时间里，确定了三种具有不同认知轨迹的独特表型群体：有弹性、平均和受损表型。有弹性表型表现出最高的神经心理学因子得分和学业成绩，与对照组相似；而受损表型则相反，所有测试指标的表现都最差。这些发现在 36 个月内仍然显著且稳定。多变量逻辑回归表明，发病年龄、脑电图、神经系统检查和社会经济劣势与表型分类有关。
本研究表明，新诊断癫痫的青少年在 36 个月内存在多种潜在的认知轨迹表型，这些表型与稳定的神经心理学和学业表现相关。
