Poongkunran Mugilan, Ulep Robin D, Stuntz Gage A, Mitchell Sara, Gaines Kenneth J, Vidal Gabriel, Chehebar Daniel, Iwuchukwu Ifeanyi O, McGrade Harold, Mohammed Alaa E, Zweifler Richard M
Ochsner Neuroscience Institute, Ochsner Health, New Orleans, LA, United States.
Ochsner Clinical School, New Orleans, LA, United States.
Front Neurol. 2023 Jun 2;14:1141059. doi: 10.3389/fneur.2023.1141059. eCollection 2023.
Telestroke has grown significantly since its implementation. Despite growing utilization, there is a paucity of data regarding the diagnostic accuracy of telestroke to distinguish between stroke and its mimics. We aimed to evaluate diagnostic accuracy of telestroke consultations and explore the characteristics of misdiagnosed patients with a focus on stroke mimics.
We conducted a retrospective study of all the consultations in our Ochsner Health's TeleStroke program seen between April 2015 and April 2016. Consultations were classified into one of three diagnostic categories: stroke/transient ischemic attack, mimic, and uncertain. Initial telestroke diagnosis was compared with the final diagnosis post review of all emergency department and hospital data. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-) for diagnosis of stroke/TIA versus mimic were calculated. Area under receiver-operating characteristic curve (AUC) analysis to predict true stroke was performed. Bivariate analysis based on the diagnostic categories examined association with sex, age, NIHSS, stroke risk factors, tPA given, bleeding after tPA, symptom onset to last known normal, symptom onset to consult, timing in the day, and consult duration. Logistic regression was performed as indicated by bivariate analysis.
Eight hundred and seventy-four telestroke evaluations were included in our analysis. Accurate diagnosis through teleneurological consultation was seen in 85% of which 532 were strokes (true positives) and 170 were mimics (true negatives). Sensitivity, specificity, PPV, NPV were 97.8, 82.5, 93.7 and 93.4%, respectively. LR+ and LR- were 5.6 and 0.03. AUC (95% CI) was 0.9016 (0.8749-0.9283). Stroke mimics were more common with younger age and female gender and in those with less vascular risk factors. LR revealed OR (95% CI) of misdiagnosis for female gender of 1.9 (1.3-2.9). Lower age and lower NIHSS score were other predictors of misdiagnosis.
We report high diagnostic accuracy of the Ochsner Telestroke Program in discriminating stroke/TIA and stroke mimics, with slight tendency towards over diagnosis of stroke. Female gender, younger age and lower NIHSS score were associated with misdiagnosis.
远程卒中自实施以来显著发展。尽管其应用日益广泛，但关于远程卒中区分卒中及其模仿病症的诊断准确性的数据却很匮乏。我们旨在评估远程卒中会诊的诊断准确性，并以卒中模仿病症为重点探讨误诊患者的特征。
我们对2015年4月至2016年4月期间在奥克施纳健康中心远程卒中项目中进行的所有会诊进行了回顾性研究。会诊被分为三种诊断类别之一：卒中/短暂性脑缺血发作、模仿病症和不确定。将最初的远程卒中诊断与所有急诊科和医院数据复查后的最终诊断进行比较。计算了诊断卒中/短暂性脑缺血发作与模仿病症的敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）、阳性似然比（LR+）和阴性似然比（LR-）。进行了预测真正卒中的受试者工作特征曲线（AUC）下面积分析。基于诊断类别进行的双变量分析检查了与性别、年龄、美国国立卫生研究院卒中量表（NIHSS）、卒中危险因素、给予组织型纤溶酶原激活剂（tPA）、tPA后出血、症状发作至最后已知正常时间、症状发作至会诊时间、一天中的时段以及会诊持续时间的关联。根据双变量分析结果进行了逻辑回归。
我们的分析纳入了874次远程卒中评估。通过远程神经学会诊的准确诊断率为85%，其中532例为卒中（真阳性），170例为模仿病症（真阴性）。敏感性、特异性、PPV、NPV分别为97.8%、82.5%、93.7%和93.4%。LR+和LR-分别为5.6和0.03。AUC（95%可信区间）为0.9016（0.8749至0.9283）。卒中模仿病症在年龄较小、女性以及血管危险因素较少的患者中更为常见。LR显示女性误诊的比值比（OR，95%可信区间）为1.9（1.3至2.9）。年龄较小和NIHSS评分较低是误诊的其他预测因素。
我们报告奥克施纳远程卒中项目在区分卒中/短暂性脑缺血发作和卒中模仿病症方面具有较高的诊断准确性，不过存在轻微的卒中过度诊断倾向。女性、年龄较小和NIHSS评分较低与误诊相关。
