Müller-Barna Peter, Leinweber Christina, Pfaffenrath Julia, Schütt-Becker Nina, von Martial Rascha, Greck Susanne, Hubert Nikolai, Rambold Holger, Haberl Roman, Hubert Gordian Jan
Department of Neurology, TEMPiS Telestroke Center, München Klinik, Academic Teaching Hospital of the Ludwig-Maximilians-University, Munich, Germany.
Department of Neurology, InnKlinikum Altötting, Altötting, Germany.
Front Neurol. 2022 Mar 2;13:766685. doi: 10.3389/fneur.2022.766685. eCollection 2022.
Acute dizziness, vertigo, and imbalance are frequent and difficult to interpret symptoms in the emergency department (ED). Primary care hospitals often lack the expertise to identify stroke or TIA as underlying causes. A telemedical approach based on telestroke networks may offer adequate diagnostics and treatment.
The aim of this study is to evaluate the accuracy of a novel ED algorithm in differentiating between peripheral and central vestibular causes.
Within the Telemedical Project for Integrative Stroke Care (TEMPiS), a telemedical application including a videooculography (VOG) system was introduced in 2018 in 19 primary care spoke hospitals. An ED triage algorithm was established for all patients with acute dizziness, vertigo, or imbalance of unknown cause (ADVIUC) as a leading complaint. In three predefined months, all ADVIUC cases were prospectively registered and discharge letters analyzed. Accuracy of the ED triage algorithm in differentiation between central and peripheral vestibular cases was analyzed by comparison of ED diagnoses to final discharge diagnoses. The rate of missed strokes was calculated in relation to all cases with a suitable brain imaging. Acceptance of teleconsultants and physicians in spoke hospitals was assessed by surveys.
A total number of 388 ADVIUC cases were collected, with a median of 12 cases per months and hospital (IQR 8-14.5). The most frequent hospital discharge diagnoses are vestibular neuritis (22%), stroke/TIA (18%), benign paroxysmal positioning vertigo (18%), and dizziness due to internal medicine causes (15%). Detection of a central vestibular cause by the ED triage algorithm has a high sensitivity (98.6%), albeit poor specificity (45.9%). One stroke out of 32 verified by brain scan was missed (3.1%). User satisfaction, helpfulness of the project, improvement of care, personal competence, and satisfaction about handling of the VOG systems were rated consistently positive.
The concept shows good acceptance for a telemedical and network-based approach to manage ADVIUC cases in the ED of primary care hospitals. Identification of stroke cases is accurate, while specificity needs further improvement. The concept could be a major step toward a broadly available state of the art diagnostics and therapy for patients with ADVIUC in primary care hospitals.
急性头晕、眩晕和平衡失调是急诊科常见且难以解读的症状。基层医院往往缺乏识别中风或短暂性脑缺血发作(TIA)作为潜在病因的专业知识。基于远程卒中网络的远程医疗方法可能提供充分的诊断和治疗。
本研究旨在评估一种新型急诊科算法区分外周性和中枢性前庭病因的准确性。
在综合卒中护理远程医疗项目(TEMPiS)中,2018年在19家基层分中心医院引入了一种包括视频眼震图(VOG)系统的远程医疗应用。针对所有以急性头晕、眩晕或不明原因的平衡失调(ADVIUC)为主诉的患者建立了急诊科分诊算法。在三个预定义的月份中,对所有ADVIUC病例进行前瞻性登记并分析出院小结。通过将急诊科诊断与最终出院诊断进行比较,分析急诊科分诊算法区分中枢性和外周性前庭病例的准确性。计算与所有进行了合适脑部成像的病例相关的漏诊中风率。通过调查评估分中心医院远程会诊医生和医生的接受度。
共收集了388例ADVIUC病例,每家医院每月中位数为12例(四分位间距8 - 14.5)。最常见的医院出院诊断是前庭神经炎(22%)、中风/TIA(18%)、良性阵发性位置性眩晕(18%)和内科病因导致的头晕(15%)。急诊科分诊算法检测中枢性前庭病因具有较高的敏感性(98.6%),但特异性较差(45.9%)。在32例经脑部扫描证实的中风病例中有1例漏诊(3.1%)。用户满意度、项目的帮助程度、护理改善情况、个人能力以及对VOG系统操作的满意度评分均持续呈阳性。
该概念对于基层医院急诊科采用远程医疗和基于网络的方法管理ADVIUC病例显示出良好的接受度。中风病例的识别准确,但特异性需要进一步提高。该概念可能是朝着为基层医院ADVIUC患者广泛提供先进诊断和治疗迈出的重要一步。