Massachusetts Eye & Ear Infirmary, Harvard Medical School, Boston.
JAMA Facial Plast Surg. 2019 Sep 1;21(5):387-392. doi: 10.1001/jamafacial.2019.0086.
Quantitative assessment of facial function is difficult, and historic grading scales such as House-Brackmann have well-recognized limitations. The electronic, clinician-graded facial function scale (eFACE) allows rapid regional analysis of static, dynamic, and synkinetic facial function in patients with unilateral facial palsy within the course of a clinical encounter, but it relies on clinician assessment. A newly developed, machine-learning algorithm (Emotrics) provides automated, objective facial measurements but lacks clinical input (ie, recognizing laterality of facial palsy or synkinesis).
To compare the sensitivity of a clinician-based tool (eFACE) to a well-established intervention for facial palsy (eyelid weight placement) with an automated facial-measurement algorithm (Emotrics).
DESIGN, SETTING, AND PARTICIPANTS: A retrospective review was conducted of the most recent 53 patients with unilateral facial palsy who received an eyelid weight at the Massachusetts Eye and Ear Infirmary Facial Nerve Center from 2014 to 2017. Preoperative and postoperative photographs were deidentified and randomized. The entire cohort was analyzed by 3 clinicians, as well as by the Emotrics program.
eFACE scores of the palpebral fissure at rest (0, wide; 100, balanced; 200, narrow), with gentle eyelid closure (0, incomplete; 100, complete), and with forceful eyelid closure (0, incomplete; 100, complete) before and after eyelid weight placement were compared with palpebral fissure measurements by Emotrics.
Of the 53 participants, 33 were women, and mean (SD) age was 44.7 (18) years. The mean (SD) eFACE scores and Emotrics measurements (in millimeters) before vs after eyelid weight placement of the palpebral fissure at rest (eFACE, 84.3 [15.9] vs 109.7 [21.4]; Emotrics, 10.3 [2.2] vs 9.1 [1.8]), with gentle eyelid closure (eFACE, 65.9 [28.0] vs 92.1 [15.4]; Emotrics, 4.4 [2.7] vs 1.3 [2.0]), and with forceful eyelid closure (eFACE, 75.1 [28.6] vs 97.0 [10.7]; Emotrics, 3.0 [3.1] vs 0.5 [1.3]) all significantly improved. Subgroup analysis of patients with expected recovery (eg, Bell palsy) (n = 40) demonstrated significant development of ocular synkinesis on eFACE (83.9 [22.7] vs 98.9 [4.4]) after weight placement, which could also explain the improvement in eyelid function. The scores of patients with no expected recovery (n = 13) improved in both eFACE and Emotrics analysis following eyelid weight placement, though results did not reach significance, likely limited by the small subgroup size.
The eFACE tool agrees well with automated, objective facial measurements using a machine-learning based algorithm such as Emotrics. The eFACE tool is sensitive to spontaneous recovery and surgical intervention, and may be used for rapid regional facial function assessment from a clinician's perspective following recovery and/or surgical intervention.
重要性:面部功能的定量评估较为困难,House-Brackmann 等传统分级量表具有明显的局限性。电子临床医生评分的面部功能量表(eFACE)可在临床就诊过程中快速对单侧面瘫患者的静态、动态和协同运动面部功能进行区域分析,但它依赖于临床医生的评估。一种新开发的、基于机器学习的算法(Emotrics)可提供自动、客观的面部测量,但缺乏临床输入(即识别面瘫的侧别或协同运动)。
目的:比较基于临床医生的工具(eFACE)与用于面瘫的既定干预措施(眼睑重量放置)与基于自动面部测量的算法(Emotrics)的敏感性。
设计、设置和参与者:对 2014 年至 2017 年在马萨诸塞州眼耳医院面神经中心接受眼睑重量放置的 53 例单侧面瘫患者的最新病例进行了回顾性分析。术前和术后照片被去标识和随机化。整个队列由 3 名临床医生以及 Emotrics 程序进行分析。
主要结局和测量:比较了眼睑重量放置前后 eFACE 评估的眼睑裂静止时(0,宽;100,平衡;200,窄)、眼睑轻度闭合时(0,不完全;100,完全)和眼睑强力闭合时(0,不完全;100,完全)的评分与 Emotrics 测量的眼睑裂测量值。
结果:在 53 名参与者中,有 33 名女性,平均(SD)年龄为 44.7(18)岁。眼睑裂静止时(eFACE,84.3[15.9] vs 109.7[21.4];Emotrics,10.3[2.2] vs 9.1[1.8])、眼睑轻度闭合时(eFACE,65.9[28.0] vs 92.1[15.4];Emotrics,4.4[2.7] vs 1.3[2.0])和眼睑强力闭合时(eFACE,75.1[28.6] vs 97.0[10.7];Emotrics,3.0[3.1] vs 0.5[1.3])的 eFACE 评分和 Emotrics 测量值在眼睑重量放置后均显著提高。对预计可恢复的患者(如贝尔面瘫)(n=40)进行亚组分析显示,眼睑重量放置后 eFACE 上出现眼动性协同运动(83.9[22.7] vs 98.9[4.4]),这也可以解释眼睑功能的改善。没有预期恢复的患者(n=13)在眼睑重量放置后,eFACE 和 Emotrics 分析中的评分均有所改善,但结果未达到统计学意义,这可能是由于亚组规模较小。
结论和相关性:eFACE 工具与基于机器学习的自动客观面部测量工具(如 Emotrics)吻合良好。eFACE 工具对自发性恢复和手术干预均敏感,可从临床医生的角度用于评估恢复后和/或手术干预后的面部功能的快速区域评估。
证据水平:4。