UNASSIGNED: Patients with distal radius fractures treated with a VLP within the ICUC database, an international collaborative and publicly available dataset, were identified. The primary outcome was volar rim loss of reduction on follow-up imaging, defined as a change in radiographic alignment from intra-operative fluoroscopy, teardrop angle less than 50°, or loss of normal radiocarpal alignment. Secondary outcomes were final range of motion (ROM) of the affected extremity. Radiographic Soong classification was used to grade plate position. Descriptive statistics were used to assess variables\' distributions. A Random Forest supervised machine learning algorithm was used to classify variable importance for predicting the primary outcome. Traditional descriptive statistics were used to compare patient, fracture, and treatment characteristics with volar rim loss of reduction. Volar rim loss of reduction and final ROM in degrees and as compared with contralateral unaffected limb were also assessed.
UNASSIGNED: Fifty patients with volarly displaced, intra-articular distal radius fractures treated with a VLP were identified. Six patients were observed to have a volar rim loss of reduction, but none required reoperation. Volar ulnar fragment size, Soong grade 0, and postfixation axial plate position in relation to the sigmoid notch were significantly associated (P < .05) with volar rim loss of reduction. All cases of volar rim loss of reduction occurred when VUF was 10.8 mm or less.
UNASSIGNED: The size of the VUF was the most important variable for predicting volar rim loss of reduction followed by postfixation plate position in an axial position to the sigmoid notch and the number of volar fragments in the Random Forest machine learning algorithm. There were no significant differences in ROM between patients with volar ulnar escape and those without.
■使用ICUC数据库中的VLP治疗的桡骨远端骨折患者,一个国际合作和公开可用的数据集,已确定。主要结果是随访成像时掌侧边缘减少,定义为术中透视检查的射线照相对准变化,泪滴角小于50°,或失去正常的桡骨对齐。次要结果是受影响肢体的最终运动范围(ROM)。射线照相宋代分类用于对板位置进行分级。描述性统计用于评估变量的分布。使用随机森林监督机器学习算法对变量重要性进行分类以预测主要结果。传统的描述性统计用于比较患者,骨折,和治疗特点与掌侧边缘损失减少。还评估了与对侧未受影响的肢体相比的掌侧边缘减少和最终ROM的程度。
■50名四肢移位的患者,确定了用VLP治疗的桡骨远端关节内骨折.观察到6例患者掌侧边缘减少,但没有人需要再次操作。尺骨尺骨尺骨碎片大小,Soong等级为0,固定后的轴向钢板位置与乙状结肠切迹的关系显着相关(P<0.05)与掌侧边缘减少减少有关。当VUF为10.8mm或更小时,所有掌侧边缘减少的情况都发生了。
■在随机森林机器学习算法中,VUF的大小是预测掌侧边缘减少的最重要变量,然后是轴向位置的固定后钢板位置和掌侧碎片的数量。掌侧尺骨逃逸患者与无尺骨逃逸患者之间的ROM没有显着差异。