Cortese Elvira, Rochelle Pierre La, Patel Freya, Koohi Nehzat, Kaski Diego
SENSE research unit, Department of Clinical and Movement Neurosciences, Institute of Neurology, University College London, London, UK.
Audiology Department, School of Speech-Language Pathology and Audiology, Faculty of Medicine, Universidad de Valparaiso, Valparaíso, Chile.
Sci Rep. 2025 Jul 14;15(1):25403. doi: 10.1038/s41598-025-11007-9.
Accurate diagnosis of acute vertigo (AV) in emergency settings is crucial due to varied underlying causes. Challenges include differentiating non-life-threatening conditions, like vestibular migraine, from severe issues, such as stroke. The "TiTrATE - STANDING Adapted" algorithm was created to help non-specialist emergency physicians diagnose posterior circulation strokes in AV patients, overcoming the limitations of current practices that require specialized knowledge and equipment. This study involved a prospective validation and retrospective analysis of 67 patients at the National Hospital for Neurology and Neurosurgery and University College London Hospital. Patients underwent objective oculomotor assessments through video oculography and pure tone audiometry, conducted by an experienced audiologist in the acute stage. The accuracy of the "TiTrATE - STANDING Adapted" algorithm was compared to final diagnoses made by specialists, which included a comprehensive review of medical histories, objective test results, and imaging studies. The "TiTrATE - STANDING Adapted" algorithm demonstrated a sensitivity of 90%, with low specificity (57.9%), resulting in a high rate of false positives (24 out of 67) and a global accuracy of 62.7%. Conditions such as vestibular migraine and chronic vascular issues (e.g., orthostatic hypotension) were often misclassified, impacting the overall specificity. Integrating TiTrATE, HINTS Plus, and STANDING into a single diagnostic algorithm for acute vertigo in the ED could enhance accuracy and streamline decision-making. However, the combined model must perform at least as well as its individual components. Key improvements needed before implementation include adding vestibular migraine criteria, refining stroke exclusion guidelines, and ongoing validation to boost diagnostic precision and patient outcomes.
由于急性眩晕(AV)的潜在病因多种多样,因此在急诊环境中准确诊断至关重要。面临的挑战包括区分非危及生命的情况,如前庭性偏头痛,与严重问题,如中风。创建“TiTrATE - 站立适应版”算法是为了帮助非专科急诊医生诊断AV患者的后循环中风,克服当前需要专业知识和设备的实践的局限性。本研究对国立神经病学与神经外科医院以及伦敦大学学院医院的67例患者进行了前瞻性验证和回顾性分析。患者在急性期由经验丰富的听力学家通过视频眼震图和纯音听力测定进行客观眼动评估。将“TiTrATE - 站立适应版”算法的准确性与专家做出的最终诊断进行比较,专家诊断包括对病史、客观检查结果和影像学研究的全面审查。“TiTrATE - 站立适应版”算法的敏感性为90%,特异性较低(57.9%),导致假阳性率较高(67例中有24例),总体准确率为62.7%。前庭性偏头痛和慢性血管问题(如体位性低血压)等情况经常被误分类,影响了总体特异性。将TiTrATE、HINTS Plus和站立测试整合到急诊急性眩晕的单一诊断算法中,可以提高准确性并简化决策过程。然而,组合模型的表现必须至少与其各个组成部分一样好。实施前需要进行的关键改进包括增加前庭性偏头痛标准、完善中风排除指南,以及持续验证以提高诊断精度和患者治疗效果。