计算机化决策支持以最佳地引导患者通过痴呆症的诊断途径
Aniek M van Gils1,2, Antti Tolonen3, Argonde C van Harten4,5
1Alzheimer Center Amsterdam and Department of Neurology, VU University Medical Center, Amsterdam UMC, De Boelelaan 1118, Amsterdam, 1081 HZ, The Netherlands. a.vangils@amsterdamumc.nl.
Alzheimer's research & therapy
|November 26, 2024
概括
数据驱动的方法有效指导痴呆症诊断和治疗资格. 这种逐步测试优化了诊断途径,提高了准确性,减少了记忆诊所患者不必要的测试.
科学领域:
- 神经学 神经学
- 生物标志物 生物标志物
- 诊断工具 诊断工具 诊断工具
背景情况:
- 痴呆症患病率的增加需要有效的诊断策略.
- 新兴的疾病修饰疗法 (DMT) 需要精确的患者选择.
- 记忆诊所需要优化综合征,病因和DMT资格诊断的途径.
研究的目的:
- 开发和验证一种数据驱动的,循序渐进的痴呆症诊断方法.
- 在三个临床场景中评估这种方法的效率和准确性.
- 引导临床医生在记忆诊所中选择具有附加值的测试.
主要方法:
- 利用了来自两个记忆诊所队列 (ADC,PredictND) 的数据,其中包括504名痴呆患者,191名MCI和188名对照.
- 采用数字认知查 (cCOG),神经心理评估 (NP),MRI和CSF生物标志物在一个连续的测试策略.
- 临床决策支持系统 (CDSS) 生成疾病状态指数 (DSI),以指导诊断确定性和确认诊断.
主要成果:
- cCOG预先查减少了42%的综合征诊断NP需求 (准确率为0.71).
- 逐步的病因诊断达到80%的准确性,需要77%的MRI和37%的CSF病例.
- 对于DMT的资格,逐步测试确定了90%的潜在符合条件的AD痴呆症患者,其中60%进行了CSF测试.
结论:
- 数据驱动的诊断途径在不同的临床场景中是准确和高效的.
- 一个CDSS工具可以帮助临床医生优化测试选择的附加值.
- 有效的诊断途径对于保持痴呆症护理的可访问性和可负担性至关重要,特别是在新的DMT方面.
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