摘要
背景:青少年特发性脊柱侧凸是目前临床上影响青少年身体外观的常见病,但通过Logistic回归方程来分析固定后冠状面失平衡目前尚缺乏报道。目的:探讨LenkeⅡ型青少年特发性脊柱侧凸患者固定后冠状面失平衡的原因。方法:对新疆医科大学第一附属医院脊柱外科2001年1月至2012年11月收治的141例LenkeⅡ型青少年特发性脊柱侧凸患者进行多个变量的单因素比较和多因素Logistic回归分析,筛选导致青少年特发性脊柱侧凸患者固定后发生冠状面失平衡的危险因素,并构建预测模型。结果与结论:141例患者中有30例出现固定后冠状面失平衡,占全部受试患者的21.28%。对于LenkeⅡ型特发性脊柱侧弯畸形患者,固定前顶椎3-4级Nash-More椎体旋转、4-5级Risser征、主弯矫正率/柔韧性>1、下胸弯Cobb角>70°等易引起固定后冠状面失平衡。多因素Logistic回归分析提示椎体旋转、Risser征、主弯矫正率/柔韧性、下胸弯Cobb角等是LenkeⅡ型青少年特发性脊柱侧凸患者固定后发生冠状面失平衡的独立危险因素。预测模型为Y=1/[1+exp(-1.182X1+1.228X2+1.671X3-0.71X4+0.407)]。
BACKGROUND: Adolescent idiopathic scoliosis is a common disease that can affect physical appearance of adolescents in the clinic at present. However, there are lacks of studies on coronal plane imbalance after fixation using Logistic regression equation at present. OBJECTIVE: To investigate the reasons for coronal plane imbalance after fixation in patients with Lenke type II adolescent idiopathic scoliosis. METHODS: 141 cases of Lenke type II adolescent idiopathic scoliosis admitted by Department of Spina~ Surgery of the First Affiliated Hospital of Xinjiang Medical University in China from January 2001 to November 2012 were chosen as subjects. Multivariate single factor and multiple-factor Logistic regression were performed. Risk factors for the coronal plane imbalance after fixation in adolescent idiopathic scoliosis patients were screened, and predictive models were established. RESULTS AND CONCLUSION: Coronal plane imbalance occurred in 30 of the 141 patients, accounting for 21.28%. For Lenke type II adolescent idiopathic scoliosis patients, preoperative apical vertebral Nash-More rotation level 3-4, Risser grade 4-5, major curve correction rate/flexibility 〉 1, lower thoracic Cobb angle 〉 70~ were vulnerable to postoperative coronal plane imbalance. Multivariate logistic regression showed that vertebral rotation, Risser grade, major curve correction rate/flexibility, lower thoracic Cobb angle were independent risk factors for postoperative coronal plane imbalance in Lenke type II adolescent idiopathic scoliosis patients. The predictive model was Y=I/[1 +exp(-l. 182X1+1.228X2+1.671 X3-0.71 )(4+0.407)].
出处
《中国组织工程研究》
CAS
CSCD
2014年第9期1362-1367,共6页
Chinese Journal of Tissue Engineering Research