预测过渡到精神病的眼动特征:纵向变化和影响
Dan Zhang1, Lihua Xu1, Xu Liu1
1Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Schizophrenia bulletin
|January 20, 2024
概括
眼动模式可以预测临床高风险 (CHR) 个体的精神病转化. 这些异常的眼动 (EM) 在一年内看起来稳定,这表明使用眼睛追踪技术的早期检测有潜力.
科学领域:
- 神经科学是一个神经科学.
- 精神病学是一个精神病学.
- 计算精神病学是一种计算精神病学.
背景情况:
- 眼动 (EM) 特征对临床高风险 (CHR) 个体中精神病转换的预测价值的研究有限.
- 了解纵向EM轨迹对于早期发现精神病至关重要.
研究的目的:
- 调查机器学习模型的预测准确度,使用EM指数进行CHR转换.
- 在一年内检查CHR个体EM指数的纵向变化.
主要方法:
- 对140名CHR和98名健康对照进行了眼动评估 (固定稳定性,自由视力,平滑追逐).
- 考克斯回归和随机森林模型用于预测;线性混合效应模型 (LMMs) 分析了纵向变化.
主要成果:
- 转化为精神病的CHR个体表现出明显的EM模式 (长时间的固定,减小的冲动幅度,减少平滑的追逐速度增长).
- 一个随机森林模型在根据基线EM测量对转换器与非转换器进行分类时,获得了0.776的准确性.
- 一年后,在转换器中没有观察到这些EM指数的显著纵向变化.
结论:
- 异常的眼动可能在精神病发作之前发生,并在一年内保持稳定.
- 眼睛跟踪技术与预测建模相结合,对识别患有精神病高风险的CHR个体显示出有前途.
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