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颞肌和颧骨的形态测量作为下颌骨骨折患者基于医院的临床结局的新预测指标。

Morphomic measurement of the temporalis muscle and zygomatic bone as novel predictors of hospital-based clinical outcomes in patients with mandible fracture.

作者信息

Lisiecki Jeffrey, Zhang Peng, Wang Lu, Rinkinen Jacob, De La Rosa Sara, Enchakalody Binu, Brownley Robert Cameron, Wang Stewart C, Buchman Steven R, Levi Benjamin

机构信息

From the *Section of Plastic Surgery, Department of Surgery, and †Department of Biostatistics, University of Michigan, Ann Arbor, MI; and ‡International Center for Automotive Medicine, University of Michigan, Ann Arbor, MI.

出版信息

J Craniofac Surg. 2013 Sep;24(5):1577-81. doi: 10.1097/SCS.0b013e3182a12e02.

DOI:10.1097/SCS.0b013e3182a12e02
PMID:24036730
Abstract

INTRODUCTION

Patients with mandibular fracture often have comorbidities and concomitant injuries making the decision for when and how to operate a challenge. Physicians describe "temporalis wasting" as a finding that indicates frailty; however, this is a subjective finding without quantitative values. In this study, we demonstrate that decreased morphomic values of the temporalis muscle and zygomatic bone are an objective measure of frailty associated with increased injury-induced morbidity as well as negative impact on overall hospital-based clinical outcomes in patients with mandible fracture.

METHODS

Computed tomographic (CT) scans from all patients with a diagnosis of a mandible fracture in the University of Michigan trauma registry and with a hospital admission were collected from the years 2004 to 2011. Automated, high-throughput CT analysis was used to reconstruct the anatomy and quantify morphomic values (temporalis volume, area and thickness, and zygomatic thickness) in these patients using MATLAB v13.0 (MathWorks Inc, Natick, MA, USA). Subsequently, a subset of 16 individuals with a Glasgow Coma Scale of 14 or 15 was analyzed to control for brain injury. Clinical data were obtained, and the association between morphomic measurements and clinical outcomes was evaluated using Pearson correlation for unadjusted analysis and multiple regression for adjusted analysis.

RESULTS

The mean age of patients in the study was 47.1 years. Unadjusted analysis using Pearson correlation revealed that decreases in zygomatic bone thickness correlated strongly with increases in hospital, intensive care unit, and ventilator days (P < 0.0001, P = 0.0003, and P = 0.0017, respectively). Furthermore, we found that decreases in temporalis mean thickness correlated with increases in hospital and ventilator days (P = 0.0264 and P = 0.0306, respectively). Similarly, decreases in temporalis local mean thickness are significantly correlated with increases in hospital and ventilator days (P = 0.0232 and P = 0.0472, respectively).

CONCLUSIONS

Decreased thicknesses of the zygomatic bone and temporalis muscle are significantly correlated with higher hospital, ventilator, and intensive care unit days in patients with mandibular fracture receiving reconstructive operations. This morphomic methodology provides an accurate, quantitative means to evaluate craniofacial trauma patient frailty, injury, and outcomes using routinely obtained CT scans. In the future, we plan to apply this approach to determine preoperative risk stratification and assist in surgical planning.

摘要

引言

下颌骨骨折患者常伴有合并症和其他损伤,这使得决定何时以及如何进行手术成为一项挑战。医生将“颞肌萎缩”描述为一种表明身体虚弱的体征;然而,这是一种主观体征,没有量化值。在本研究中,我们证明颞肌和颧骨的形态学测量值降低是身体虚弱的客观指标,与损伤所致发病率增加相关,并且对下颌骨骨折患者的整体医院临床结局有负面影响。

方法

收集了2004年至2011年密歇根大学创伤登记处诊断为下颌骨骨折且入院治疗的所有患者的计算机断层扫描(CT)图像。使用MATLAB v13.0(美国马萨诸塞州纳蒂克市MathWorks公司)对这些患者进行自动、高通量CT分析,以重建解剖结构并量化形态学测量值(颞肌体积、面积和厚度,以及颧骨厚度)。随后,对格拉斯哥昏迷量表评分为14或15分的16名患者进行亚组分析,以控制脑损伤因素。获取临床数据,并使用Pearson相关性进行未校正分析,使用多元回归进行校正分析,以评估形态学测量值与临床结局之间的关联。

结果

研究中患者的平均年龄为47.1岁。使用Pearson相关性进行的未校正分析显示,颧骨厚度降低与住院天数、重症监护病房天数和呼吸机使用天数增加密切相关(分别为P < 0.0001、P = 0.0003和P = 0.0017)。此外,我们发现颞肌平均厚度降低与住院天数和呼吸机使用天数增加相关(分别为P = 0.0264和P = 0.0306)。同样,颞肌局部平均厚度降低与住院天数和呼吸机使用天数增加显著相关(分别为P = 0.0232和P = 0.0472)。

结论

在接受重建手术的下颌骨骨折患者中,颧骨和颞肌厚度降低与住院天数、呼吸机使用天数和重症监护病房天数增加显著相关。这种形态学方法提供了一种准确、定量的手段,可利用常规获取的CT扫描来评估颅面创伤患者的身体虚弱程度、损伤情况和结局。未来,我们计划应用这种方法来确定术前风险分层并协助手术规划。

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