Ojha Pawan T, Nagendra Shashank, Ansari Afroz, Kadam Nikhil Dhananjay, Mathur Ajay, Gopinathan Neeraja, Ojha Nishu, Patel Hardik, Bansode Akshay, Kalel Orpah, Morwani Kishan P, Jagtap Digvijay, Kumar Sumant, Vij Vinod
Department of Neurology, Fortis Hiranandani Hospital, Vashi, Navi Mumbai, Maharashtra, India.
Department of Neurology, Grant Medical College and JJ Hospital, Mumbai, Maharashtra, India.
Ann Indian Acad Neurol. 2022 May-Jun;25(3):464-472. doi: 10.4103/aian.aian_662_21. Epub 2022 Apr 6.
Most of the existing qualitative facial nerve grading systems are very subjective while the quantitative grading systems are more complex, require longer data input time and specific software. There is a need for having a scoring system with graphic criteria to improve the subjectivity, reliability and convenience. We aimed to develop and validate such a reliable graphic scale for use in Bell's palsy.
Face videos of patients with unilateral facial paralysis were recorded using smartphones and analyzed for six items including five voluntary facial movements apart from complications of facial palsy (synkinesis, hyperkinesis, and contracture). 15 videos were used for pilot study, 75 for the development of scale and 110 for its validation. Each video was rated on two separate occasions by 3 independent raters, a score of 0-4 was assigned to each item using the graphic scoring criteria, and a composite score was obtained (range 0-24). Five disease severity categories: normal (score 0), mild (score 1-6), moderate (score 7-12), severe (score: 13-18) and profound facial weakness (score: 19-24).
The proposed scale and its component items had high inter-rater and intra-rater reliability (Kappa >0.7). Good correlation (Pearson co-efficient >0.7) was seen among the voluntary movements. The proposed scale is a valid tool to score motor deficits and complications of facial palsy.
The proposed scale is a valid and reliable graphic scale to describe facial motor dysfunction and its secondary defects.
现有的大多数定性面神经分级系统主观性很强,而定性分级系统则更为复杂,需要更长的数据输入时间和特定软件。需要一个具有图形标准的评分系统来提高主观性、可靠性和便利性。我们旨在开发并验证这样一种可靠的图形量表,用于贝尔面瘫。
使用智能手机记录单侧面瘫患者的面部视频,并分析六个项目,包括除面瘫并发症(联动、运动亢进和挛缩)之外的五种随意面部运动。15个视频用于预试验,75个用于量表开发,110个用于验证。每个视频由3名独立评分者在两个不同场合进行评分,使用图形评分标准为每个项目分配0至4分,并获得一个综合评分(范围为0至24)。五种疾病严重程度类别:正常(评分0)、轻度(评分1至6)、中度(评分7至12)、重度(评分13至18)和极重度面部无力(评分19至24)。
所提出的量表及其组成项目具有较高的评分者间和评分者内信度(Kappa>0.7)。在随意运动之间观察到良好的相关性(皮尔逊相关系数>0.7)。所提出的量表是评估面瘫运动功能缺损和并发症的有效工具。
所提出的量表是描述面部运动功能障碍及其继发缺陷的有效且可靠的图形量表。