How Helpful Is aEEG? Context and User Experience Matter.
How Helpful Is aEEG? Context and User Experience Matter.
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DOI：
10.1055/s-0040-1721711
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发表时间：
2022-07
影响因子：
2
通讯作者：
Wusthoff, Courtney J.
中科院分区：
文献类型：
--
作者：
Sandoval Karamian, Amanda G.;Wusthoff, Courtney J.
目的 本研究的目的是模拟振幅积分脑电图（aEEG）在常见临床情况下诊断癫痫发作的效用。 研究设计 使用报告的新生儿癫痫发作流行率和 aEEG 敏感性和特异性、似然比 (LR) 和测试后概率来计算 aEEG 在三种典型临床情况下诊断癫痫发作的效用。 结果 患病率数据支持新生儿缺氧缺血性脑病 (HIE) 新生儿癫痫发作的预测概率为 0.4，细菌性脑膜炎为 0.27，极早产儿为 0.05。据报道，专家 aEEG 解释对癫痫发作的敏感性为 85%，特异性为 90%，阳性似然比 (LR+) 为 8.7，阴性似然比 (LR−) 为 0.17。报告的敏感性为 65%，特异性为 70%，中间解释得出 LR+ 2.17 和 LR− 0.5。报告的敏感性为 40%，而缺乏经验的解释的敏感性为 50%，LR+ 0.8 和 LR− 1.2。这些将预测试转移到后测试概率的能力高度依赖于用户的专业知识。对于 HIE，当 aEEG 经专家解释为癫痫发作呈阳性时，测试前癫痫发作概率为 0.4，测试后概率为 0.85；当 aEEG 为阴性时，癫痫发作概率降至 0.1。相比之下，在没有经验的用户水平上，aEEG 解释为癫痫发作阴性或阳性，在测试前和测试后概率之间没有获得有用的信息。类似地，在脑膜炎或极度早产的模型中，从 aEEG 获得的增量信息根据解释者的经验变化很大。 结论 aEEG 在癫痫发作率较高的情况下使用时，以及当解释具有专家用户报告的敏感性和特异性时，对于筛查新生儿癫痫发作最有用。相比之下，当应用于癫痫发作率较低的情况或解释准确性较低时，aEEG 在提供有意义的临床信息方面可能变得微不足道。适当的患者选择和高质量的解释对于 aEEG 在新生儿癫痫发作检测中的应用至关重要。 要点 aEEG 在新生儿癫痫筛查中的实用性依赖于患者选择和质量解释。 aEEG 的实用性最高，癫痫发作率高且有专家解释。由于癫痫发作率较低或解释准确性较低，aEEG 的效用可以忽略不计。
Objective The aim of the study is to model amplitude-integrated electroencephalography (aEEG) utility to diagnose seizures in common clinical scenarios. Study Design Using reported neonatal seizure prevalence and aEEG sensitivities and specificities, likelihood ratios (LRs) and post-test probabilities were calculated to quantify aEEG utility to diagnose seizures in three typical clinical scenarios. Results Prevalence data supported pretest probabilities for neonatal seizures of 0.4 in neonatal hypoxic ischemic encephalopathy (HIE), 0.27 in bacterial meningitis, and 0.05 in extreme prematurity. Reported sensitivity of 85% and specificity of 90% for seizures with expert aEEG interpretation yielded a positive likelihood ratio (LR+) of 8.7 and a negative likelihood ratio (LR−) of 0.17. Reported sensitivity of 65% and specificity of 70% with intermediate interpretation yielded LR+ 2.17 and LR− 0.5. Reported sensitivity of 40% and sensitivity of 50% with inexperienced interpretation gave LR+ 0.8 and LR− 1.2. These translate the ability to move pretest to post-test probability highly dependent on user expertise. For HIE, a pretest probability of seizure of 0.4 moves to a post-test probability of 0.85 when aEEG is positive for seizures by expert interpretation, and down to 0.1 when aEEG is negative. In contrast, no useful information was gained between pretest and post-test probability by aEEG interpreted as negative or positive for seizure at the inexperienced user level. Similarly, in the models of meningitis or extreme prematurity, incremental information gained from aEEG ranged widely based on interpreter experience. Conclusion aEEG is most useful to screen for neonatal seizures when used in conditions with high seizure prevalence, and when interpretation has a sensitivity and specificity as reported for expert users. In contrast, aEEG can become negligible in providing meaningful clinical information when applied in conditions having lower seizure prevalence or when interpretation has low accuracy. Appropriate patient selection and high quality interpretation are essential for aEEG utility in neonatal seizure detection. Key Points aEEG utility for neonatal seizure screening relies on patient selection and quality interpretation. Utility of aEEG is highest with high seizure prevalence and expert interpretation. Utility of aEEG can be negligible with lower seizure prevalence or low accuracy interpretation.
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DOI：
10.1136/fn.89.1.f37
发表时间：
2004-01-01
影响因子：
4.4
作者：
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发表时间：
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影响因子：
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