Cozma Liviu, Avasilichioaei Mioara, Dima Natalia, Popescu Bogdan Ovidiu
Department of Clinical Neurosciences, School of Medicine, "Carol Davila" University of Medicine and Pharmacy, 020021 Bucharest, Romania.
Department of Neurology, Colentina Clinical Hospital, 20125 Bucharest, Romania.
Brain Sci. 2021 May 25;11(6):695. doi: 10.3390/brainsci11060695.
Diagnosing atypical parkinsonism can be an error-exposed undertaking in the context of elaborate criteria coupled with time restraints on their comprehensive application. We conducted a retrospective, descriptive study of diagnostic accuracy among physicians at two tertiary neurology centers in Romania and developed an algorithmic tool for comparison purposes. As many as 90 patients qualified for inclusion in the study, with 77 patients actually complying with atypical parkinsonism criteria. Overall, physician-established diagnoses may be incorrect in about one-fourth of cases. The reasons for this finding span a wide range of possibilities, from terminology-related inaccuracies to criteria sophistication. A Boolean-logic algorithmic approach to diagnosis might decrease misdiagnosis rates. These findings prepare the ground for the future refinement of an algorithmic application to be fully validated in a prospective study for the benefit of patients and health professionals alike.
在复杂的诊断标准以及对这些标准全面应用存在时间限制的情况下，诊断非典型帕金森症可能是一项容易出错的工作。我们对罗马尼亚两家三级神经科中心的医生进行了一项关于诊断准确性的回顾性描述性研究，并开发了一种算法工具用于比较。多达90名患者符合纳入该研究的条件，其中77名患者实际符合非典型帕金森症标准。总体而言，医生做出的诊断在约四分之一的病例中可能是错误的。这一发现的原因有多种可能性，从与术语相关的不准确到标准的复杂性。采用布尔逻辑算法方法进行诊断可能会降低误诊率。这些发现为未来完善算法应用奠定了基础，以便在一项前瞻性研究中得到充分验证，从而造福患者和医疗专业人员。
