根据EEG和临床特征,在儿童期脑炎后的早期预测
Xiaojuan Sun1, Jinhua Zhao1, Chunyun Guo1
1Department of Pediatrics, The Second Affiliated Hospital of Nantong University, Nantong First People's Hospital, Nantong, Jiangsu, China.
Emergency medicine international
|July 24, 2023
概括
这项研究开发了一种模型,使用血红蛋白,发作频率和EEG模式来预测脑炎后的儿童. 这种早期预测有助于及时干预患有脑后风险的儿童.
科学领域:
- 儿科神经学 儿科神经学
- 临床神经生理学 临床神经生理学
背景情况:
- 儿童脑炎可能导致长期的神经系统后果,包括.
- 早期识别患有脑后风险的儿童对于及时管理和改善结果至关重要.
研究的目的:
- 建立和验证儿童脑炎后的早期预测模型.
- 确定主要的临床和脑电图 (EEG) 预测PE的特征.
主要方法:
- 分析了255名患有脑炎的儿童队列.
- 患者被分为训练和验证组.
- 后勤回归分析确定了PE的风险因素,构成了预测模型的基础.
主要成果:
- 血红蛋白水平,急性脑炎期间的频率和脑脑电图缓慢/快波频率是PE的显著预测因素.
- 开发的预测模型表现出良好的诊断性能,训练组的AUC为0.835,验证组的AUC为0.712.
结论:
- 周围血液中的血红蛋白,急性发作频率和特定的EEG模式是脑后的有价值预测因素.
- 已建立的模型提供了一个有前途的工具,用于早期PE风险评估在儿童脑炎后.
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