Jouffroy P, Sebaaly A, Aubert T, Riouallon G
Service de chirurgie orthopédique et traumatologique, Centre hospitalier Paris Saint Joseph, 185 rue Raymond Losserand, 75014 Paris, France.
Service de chirurgie orthopédique et traumatologique, Centre hospitalier Paris Saint Joseph, 185 rue Raymond Losserand, 75014 Paris, France.
Orthop Traumatol Surg Res. 2017 May;103(3):325-329. doi: 10.1016/j.otsr.2016.10.020. Epub 2016 Dec 23.
Acetabular fractures remain challenging to diagnose, particularly when they are complex. An accurate diagnosis is nevertheless crucial to select the best surgical strategy. None of the training methods described to date relies on the Letournel classification with a detailed analysis of each abnormality seen by computed tomography (CT). We therefore prospectively assessed a CT-based diagnostic method by (1) determining the rate of correct diagnoses by orthopaedic surgeons before and after training in the method, (2) comparing the times needed to read the CT images before and after training, (3) and assessing the repeatability of the method.
Training in the CT-based diagnostic method significantly increases the rate of correct diagnoses.
The CT-based diagnostic method involves analysing eight anatomical landmarks in the anterior, posterior, and no man's land zones. From our institutional database (450 cases between 2007 and 2016), we selected 35 acetabular fractures that replicated the overall distribution of fracture types. The images were reviewed by 10 inexperienced and 3 experienced readers before and after they received training in the CT-based diagnostic method. The rates of correct diagnoses and times needed to read the images were compared. Finally, an additional reading was performed to allow an assessment of reproducibility.
After training, the rate of correct diagnoses by the unexperienced readers improved by 16.64% for all fractures combined (from 212/350, 60.5% [37-83%] to 270/350, 77.14% [63-86%]; P=0.001) and by 25.9% for associated fractures (from 90/180, 50% [11-89%] to 114/140, 75.6% [61-90%]; P=0.003). Mean time required by the inexperienced readers to interpret the 35 sets of images decreased after training, from 66.1 to 47.6min (i.e., a 1.22-minute decrease per patient, P=0.001). None of the study variables changed significantly after training of the experienced readers (P>0.05). Reproducibility among the inexperienced readers was 0.78.
Analysing the eight anatomical landmarks located in the anterior, posterior, and no man's land zones is a simple and reproducible method for diagnosing all fracture patterns defined by the Letournel classification.
Level III, non-randomised prospective case-control diagnostic study.
髋臼骨折的诊断仍然具有挑战性,尤其是复杂骨折。然而,准确的诊断对于选择最佳手术策略至关重要。迄今为止所描述的训练方法均未依赖于基于计算机断层扫描(CT)所见的每种异常进行详细分析的Letournel分类法。因此,我们前瞻性地评估了一种基于CT的诊断方法,具体包括:(1)确定骨科医生在接受该方法培训前后的正确诊断率;(2)比较培训前后读取CT图像所需的时间;(3)评估该方法的可重复性。
基于CT的诊断方法培训能显著提高正确诊断率。
基于CT的诊断方法包括分析前柱、后柱及中立区的八个解剖标志。从我们的机构数据库(2007年至2016年间的450例病例)中,我们选择了35例髋臼骨折,这些骨折复制了骨折类型的总体分布。10名经验不足的读者和3名经验丰富的读者在接受基于CT的诊断方法培训前后对这些图像进行了评估。比较了正确诊断率和读取图像所需的时间。最后,进行了额外的评估以评估可重复性。
培训后,经验不足的读者对所有骨折的正确诊断率提高了16.64%(从212/350,60.5%[37-83%]提高到270/350,77.14%[63-86%];P=0.001),对合并骨折的正确诊断率提高了25.9%(从90/180,50%[11-89%]提高到114/140,75.6%[61-90%];P=0.003)。经验不足的读者解读35组图像所需的平均时间在培训后减少,从66.1分钟降至47.6分钟(即每位患者减少1.22分钟,P=0.001)。经验丰富的读者在接受培训后,所有研究变量均无显著变化(P>0.05)。经验不足的读者之间的可重复性为0.78。
分析前柱、后柱及中立区的八个解剖标志是一种简单且可重复的方法,可用于诊断Letournel分类法定义的所有骨折类型。
III级,非随机前瞻性病例对照诊断研究。