Maxillofacial Surgery Unit, Emergency Department, ASST-GOM Niguarda, Niguarda Hospital, Piazza Ospedale Maggiore 3, 20162, Milan, Italy.
Department of Medical Physics, ASST-Monza, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, 20900, Monza, Italy.
J Craniomaxillofac Surg. 2019 Sep;47(9):1456-1463. doi: 10.1016/j.jcms.2019.07.005. Epub 2019 Jul 5.
Comprehensive facial injury (CFI) score is a powerful and extremely simple scale used to grade the clinical severity of all facial injuries, and is expressed in terms of the overall surgical time needed for definitive treatment. Its statistical validation was previously reported in 2019. The aim of this study was to investigate further the link with duration of surgery, applying the score to a larger sample of patients, and to evaluate the relationship between CFI score and other extremely relevant dependent variables: length of stay (LOS) in high care units (HCU) and in intensive care units (ICU). 1406 patients with diagnosis of at least one facial bone fracture, and treated by the same team in two highly specialized trauma centers, were studied. For each patient a specific CFI score is assigned and overall surgical time, length of stay, and presence of associated injuries were recorded. Data were divided into six clusters according to CFI score: (1) 0-5, (2) 6-10, (3) 11-15, (4) 16-20, (5) 21-25, and (6) >25. Regressions between CFI clusters and duration of surgery (minutes), LOS in ICU (days), and in HCU (days) were established. In addition, the presence of associated head and/or somatovisceral injuries was analyzed and related to CFI score. Statistical analysis confirmed linear regression existing between each CFI cluster and overall surgical time (p < 0.00001), with improved significance of the results using median values of surgical duration for each cluster (p = 0.0001). It also demonstrated the existence of linear regression between all CFI clusters and LOS in HCU (p = 0.0001) and between CFI clusters 3-6 and median values of LOS in ICU (p = 0.0001). Finally, associated injuries were observed to be more frequent in high CFI score clusters, occurring in around 90% of patients with a CFI score >25 (p < 0.00001). Association of head and facial injuries play a major role in high LOS in ICU values, whereas coexistence of facial, head and somatovisceral involvement increases LOS in ICU to over twice that for single association. Surgical time and length of stay are outcomes traditionally used to assess the statistical significance of many new proposed trauma score. The strong correlation demonstrated between CFI score and each of these variables confirms its value and reliability. CFI score is proven to be an ideal, simple, informative, and reproducible tool for measuring severity of facial injuries and their clinical impact. It allows correlation with associated head and somatovisceral injuries, focusing attention on the interesting field of reciprocal influences in simultaneous, multidistrectual involvement. None of the previously proposed facial injury severity scales have offered such informative and statistically significant features.
全面面部损伤 (CFI) 评分是一种强大且极其简单的量表,用于评估所有面部损伤的临床严重程度,并以明确治疗所需的整体手术时间来表示。其统计验证已于 2019 年报告。本研究的目的是进一步研究与手术时间的关系,将该评分应用于更大的患者样本,并评估 CFI 评分与其他极其相关的因变量之间的关系:高护理单元 (HCU) 和重症监护病房 (ICU) 的住院时间 (LOS)。研究了在两个高度专业化的创伤中心由同一团队治疗的至少有一个面部骨折诊断的 1406 名患者。为每位患者分配特定的 CFI 评分,并记录总体手术时间、住院时间和伴随损伤的情况。根据 CFI 评分将数据分为六个聚类:(1) 0-5,(2) 6-10,(3) 11-15,(4) 16-20,(5) 21-25,和 (6) >25。建立了 CFI 聚类与手术时间(分钟)、ICU 住院时间(天)和 HCU 住院时间(天)之间的回归关系。此外,还分析了伴随的头部和/或躯体内脏损伤的存在情况,并将其与 CFI 评分相关联。统计分析证实,每个 CFI 聚类与整体手术时间之间存在线性回归关系(p<0.00001),使用每个聚类的手术持续时间中位数时,结果的显著性得到改善(p=0.0001)。它还表明,所有 CFI 聚类与 HCU 住院时间(p=0.0001)和 CFI 聚类 3-6 与 ICU 住院时间中位数(p=0.0001)之间存在线性回归关系。最后,观察到高 CFI 评分聚类中更频繁地发生伴随的头部和面部损伤,约 90%的 CFI 评分>25 的患者发生这种情况(p<0.00001)。头部和面部损伤的关联在 ICU 中 LOS 值较高的情况下起着重要作用,而面部、头部和躯体内脏同时受累的共存使 ICU 中的 LOS 增加到两倍以上。手术时间和住院时间是传统上用于评估许多新提出的创伤评分统计意义的结果。CFI 评分与这些变量中的每一个之间的强烈相关性证实了其价值和可靠性。CFI 评分被证明是一种理想的、简单的、信息丰富的、可重复的工具,用于衡量面部损伤的严重程度及其临床影响。它允许与伴随的头部和躯体内脏损伤相关联,将注意力集中在同时多区域受累的相互影响这一有趣领域。以前提出的任何面部损伤严重程度评分都没有提供如此信息丰富和具有统计学意义的特征。