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开发和验证用于预测脑麻儿童智力障碍的诺莫грам

Junying Yuan^1,2, Gailing Wang², Mengyue Li³

¹Henan Pediatric Clinical Research Center and Henan Key Laboratory of Child Brain Injury, Institute of Neuroscience and Third Affiliated Hospital and of Zhengzhou University, Zhengzhou 450052, China.

International journal of clinical and health psychology : IJCHP

|September 16, 2024

概括

这项研究开发了一种预测模型,以识别患有脑 (CP) 的儿童面临智力障碍 (ID) 高风险. 早期识别可以及时进行干预,以改善CP儿童的治疗结果.

科学领域:

儿科神经学儿科神经学
发育儿科发育儿科
临床遗传学临床遗传学

背景情况:

智力障碍 (ID) 经常与脑 (CP) 一起发生,这带来了重大挑战.
早期识别患有CP的儿童的ID对于及时干预和改善结果至关重要.

研究的目的:

开发和验证一个预测模型,用于评估被诊断为脑 (CP) 的儿童智力障碍 (ID) 的风险.

主要方法:

分析了885名患有CP的儿童的数据,其中377名被诊断为ID.
使用了最小绝对收缩和选择操作员 (LASSO) 回归,后勤回归和决策曲线分析 (DCA).
模型性能使用接收机操作特征 (ROC) 曲线和校准图表与启动验证进行评估.

主要成果:

一个预测性名录识别了关键的风险因素,包括早产,CP亚型,总运动功能分类系统 (GMFCS) 水平,MRI发现,和听力损失.
该模型表现出强大的预测能力,ROC曲线下的面积 (AUC) 为0.781 (95%CI:0.7504-0.8116).
通过校准图表,Hosmer-Lemeshow测试和DCA.证实了良好模型适合性和临床实用性.

结论:

开发的预测模型有效地识别了患有CP的儿童患有ID高风险,支持早期干预.
分层风险类别提供了精确的临床管理指南,以优化CP儿童的治疗结果.
在幼儿时期利用神经可塑性是改善CP儿童发育轨迹的关键.

关键词:

脑性麻脑性麻是一种疾病.是一种病.在GMFCS中,我们可以使用GMFCS.智力障碍智力障碍是一种智力障碍.这就是MRICS.预测模型的预测模型.

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