预测是从诊断开始的:估计第一次发作诊所发作复发风险
Suyi Ooi1, Chris Tailby2, Naoto Nagino3
1The Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, Heidelberg, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia; Department of Neurology, Austin Health, Heidelberg, Victoria, Australia.
Seizure
|October 8, 2024
概括
第一次发作诊所的诊断是准确的,但当前的预测工具用于第一次未引起的发作 (FUS) 后的发作复发需要更多的临床因素来提高性能.
科学领域:
- 神经学 神经学
- 临床预测建模临床预测建模
背景情况:
- 第一次发作诊所的目标是准确诊断和管理经历第一次发作的患者.
- 预测发作复发对于治疗决策和患者管理至关重要.
研究的目的:
- 评估在第一次发作诊所使用发作复发预测工具的可行性.
- 评估初始临床诊断的准确性和预测模型在第一次未引起的发作 (FUS) 后发作复发的性能.
主要方法:
- 在487名患者中评估了诊断准确性,随访时间超过6个月.
- 在181名FUS患者中,使用逻辑回归和与现有模型相比,评估了复发预测.
主要成果:
- 最初的诊断在69%的患者中持续存在;误诊发生在5%的患者中.
- 在FUS之后,12个月的发作复发率为41%.
- 开发的模型显示了适度的预测性能 (AUC 0.60),以夜间,焦点半学和发育障碍作为预测因素.
结论:
- 在第一发作诊所可以实现高诊断准确度,支持使用预测工具.
- 目前仅依赖临床因素的预测工具的性能有限.
- 未来的预测模型需要除了临床因素之外的额外数据来提高准确性.
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