Department of Neurology, Massachusetts General Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States.
Department of Pediatrics, Massachusetts General Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States.
Clin Neurophysiol. 2024 Nov;167:51-60. doi: 10.1016/j.clinph.2024.08.017. Epub 2024 Sep 5.
Early identification of infants at risk of cerebral palsy (CP) enables interventions to optimize outcomes. Central sleep spindles reflect thalamocortical sensorimotor circuit function. We hypothesized that abnormal infant central spindle activity would predict later contralateral CP.
We trained and validated an automated detector to measure spindle rate, duration, and percentage from central electroencephalogram (EEG) channels in high-risk infants (n = 35) and age-matched controls (n = 42). Neonatal magnetic resonance imaging (MRI) findings, infant motor exam, and CP outcomes were obtained from chart review. Using univariable and multivariable logistic regression models, we examined whether spindle activity, MRI abnormalities, and/or motor exam predicted future contralateral CP.
The detector had excellent performance (F1 = 0.50). Spindle rate (p = 0.005, p = 0.0004), duration (p < 0.001, p < 0.001), and percentage (p < 0.001, p < 0.001) were decreased in hemispheres corresponding to future CP compared to those without. In this cohort, PLIC abnormality (p = 0.004) and any MRI abnormality (p = 0.004) also predicted subsequent CP. After controlling for MRI findings, spindle features remained significant predictors and improved model fit (p < 0.001, all tests). Using both spindle duration and MRI findings had highest accuracy to classify hemispheres corresponding to future CP (F1 = 0.98, AUC 0.999).
Decreased central spindle activity improves the prediction of future CP in high-risk infants beyond early MRI or clinical exam alone.
Decreased central spindle activity provides an early biomarker for CP.
早期识别脑瘫（CP）高危婴儿可进行干预以优化结局。中央睡眠纺锤波反映丘脑-皮质感觉运动回路功能。我们假设异常婴儿中央纺锤波活动将预测随后出现对侧 CP。
我们训练和验证了一种自动检测方法，以从高危婴儿（n=35）和年龄匹配的对照组（n=42）的中央脑电图（EEG）通道中测量纺锤波频率、持续时间和百分比。从图表回顾中获得新生儿磁共振成像（MRI）结果、婴儿运动检查和 CP 结局。我们使用单变量和多变量逻辑回归模型，检查纺锤波活动、MRI 异常和/或运动检查是否预测未来对侧 CP。
该检测器具有出色的性能（F1=0.50）。与未来无 CP 的半球相比，纺锤波频率（p=0.005，p=0.0004）、持续时间（p<0.001，p<0.001）和百分比（p<0.001，p<0.001）降低。在该队列中，PLIC 异常（p=0.004）和任何 MRI 异常（p=0.004）也预测了随后的 CP。在控制 MRI 发现后，纺锤波特征仍然是重要的预测指标，并改善了模型拟合（p<0.001，所有检验）。使用纺锤波持续时间和 MRI 发现具有最高的准确性来分类未来 CP 的半球（F1=0.98，AUC 0.999）。
与单独使用早期 MRI 或临床检查相比，中央纺锤波活动减少可提高高危婴儿未来 CP 的预测能力。
中央纺锤波活动减少为 CP 提供了早期生物标志物。
