Department of Neurology, Mayo Clinic, Jacksonville, Florida.
Department of Neurology, Yale University, New Haven, Connecticut.
JAMA Neurol. 2020 May 1;77(5):593-600. doi: 10.1001/jamaneurol.2019.4785.
Misdiagnosis of epilepsy is common. Video electroencephalogram provides a definitive diagnosis but is impractical for many patients referred for evaluation of epilepsy.
To evaluate the accuracy of outpatient smartphone videos in epilepsy.
DESIGN, SETTING, AND PARTICIPANTS: This prospective, masked, diagnostic accuracy study (the OSmartViE study) took place between August 31, 2015, and August 31, 2018, at 8 academic epilepsy centers in the United States and included a convenience sample of 44 nonconsecutive outpatients who volunteered a smartphone video during evaluation and subsequently underwent video electroencephalogram monitoring. Three epileptologists uploaded videos for physicians from the 8 epilepsy centers to review.
Measures of performance (accuracy, sensitivity, specificity, positive predictive value, and negative predictive value) for smartphone video-based diagnosis by experts and trainees (the index test) were compared with those for history and physical examination and video electroencephalogram monitoring (the reference standard).
Forty-four eligible epilepsy clinic outpatients (31 women [70.5%]; mean [range] age, 45.1 [20-82] years) submitted smartphone videos (530 total physician reviews). Final video electroencephalogram diagnoses included 11 epileptic seizures, 30 psychogenic nonepileptic attacks, and 3 physiologic nonepileptic events. Expert interpretation of a smartphone video was accurate in predicting a video electroencephalogram monitoring diagnosis of epileptic seizures 89.1% (95% CI, 84.2%-92.9%) of the time, with a specificity of 93.3% (95% CI, 88.3%-96.6%). Resident responses were less accurate for all metrics involving epileptic seizures and psychogenic nonepileptic attacks, despite greater confidence. Motor signs during events increased accuracy. One-fourth of the smartphone videos were correctly diagnosed by 100% of the reviewing physicians, composed solely of psychogenic attacks. When histories and physical examination results were combined with smartphone videos, correct diagnoses rose from 78.6% to 95.2%. The odds of receiving a correct diagnosis were 5.45 times greater using smartphone video alongside patient history and physical examination results than with history and physical examination alone (95% CI, 1.01-54.3; P = .02).
Outpatient smartphone video review by experts has predictive and additive value for diagnosing epileptic seizures. Smartphone videos may reliably aid psychogenic nonepileptic attacks diagnosis for some people.
癫痫的误诊很常见。视频脑电图可以提供明确的诊断，但对于许多接受癫痫评估的患者来说，其实用性并不高。
评估智能手机视频在癫痫中的诊断准确性。
设计、地点和参与者：这是一项前瞻性、盲法、诊断准确性研究（OSmartViE 研究），于 2015 年 8 月 31 日至 2018 年 8 月 31 日在美国 8 个学术癫痫中心进行，纳入了 44 名连续就诊的非癫痫患者，这些患者在评估期间自愿提供智能手机视频，随后接受视频脑电图监测。3 名癫痫专家将视频上传至 8 个癫痫中心的医生处进行查看。
由专家和实习生进行的基于智能手机视频的诊断（索引测试）的性能（准确性、敏感度、特异性、阳性预测值和阴性预测值）与病史和体检以及视频脑电图监测（参考标准）的性能进行比较。
44 名符合条件的癫痫门诊患者（31 名女性[70.5%]；平均[范围]年龄 45.1[20-82]岁）提交了智能手机视频（共进行了 530 次医生审查）。最终的视频脑电图诊断包括 11 例癫痫发作、30 例心因性非癫痫性发作和 3 例生理性非癫痫性事件。专家对智能手机视频的解释在预测视频脑电图监测的癫痫发作诊断方面准确率为 89.1%（95%CI，84.2%-92.9%），特异性为 93.3%（95%CI，88.3%-96.6%）。尽管专家更有信心，但住院医生对所有涉及癫痫发作和心因性非癫痫性发作的指标的反应准确性都较低。事件中出现的运动体征提高了准确性。有四分之一的智能手机视频仅由心因性发作就能被 100%的审查医生正确诊断。当病史和体检结果与智能手机视频相结合时，正确诊断率从 78.6%上升到 95.2%。与单独使用病史和体检相比，使用智能手机视频结合患者病史和体检结果进行诊断的正确诊断可能性高 5.45 倍（95%CI，1.01-54.3；P = .02）。
专家对门诊智能手机视频的审查对诊断癫痫发作具有预测和附加价值。智能手机视频可能可以可靠地辅助某些人的心因性非癫痫性发作诊断。
