摘要
目的 建立腰骶三角(L5横突、S,上关节突、骶骨翼和髂骨翼组成的三角区)分型并根据分型指导L5S,内镜手术.方法 回顾性分析2016年1月至2018年10月于天津市天津医院就诊的腰腿痛患者647例,男315例、女332例,年龄(42.9±15.1)岁(范围19～74岁).基于腰椎正侧位X线片测量L5横突与骶骨翼距离(transverse process sacral distance,TSD)、横突间长度(inter transverse process length,ITL)、椎板间隙宽度(interlaminar width,ILW)、椎板间隙高度(interlami-nar height,ILH)、髂骶角(iliosaral angle,ISA)、髂嵴高度(iliac height,IH)、椎间隙高度(intervertebral space height,ISH)、椎间孔高度(intervertebral foramen height,IFH)、椎间孔宽度(intervertebral foramen width,IFW).采用 Spearman 相关性分析和分层聚类分析建立腰骶三角分型.对2020年1月至2022年12月于天津市天津医院接受L5S1内镜手术治疗的患者822例基于腰骶三角分型指导内镜手术并进行验证,男421例、女401例,年龄(45.1±16.7)岁(范围15～79岁).比较患者手术前后疼痛视觉模拟评分(visual analogue scale,VAS)和Oswestry功能障碍指数(Oswestry disability index,ODI),采用 Macnab标准评估手术疗效.结果 Spearman相关性分析结果显示IH与ISA(r=0.75,P＜0.001)、IFH与IFW(r=0.60,P＜0.001)、TSD与IFH(r=0.53,P＜0.001)、TSD 与 IFW(r=0.40,P＜0.001)均呈正相关.TSD 与 I H(r=-0.46,P＜0.001)、TSD 与 ISA(r=-0.42,P＜0.001)、IFW 与 ISA(r=-0.41,P＜0.001)、IFW与 IH(r=-0.50,P＜0.001)、IFH 与 IH(r=-0.42,P＜0.001)均呈负相关.根据Spearman相关性分析、分层聚类分析及受试者工作特征曲线将腰骶角分为三种类型:1型,L5横突与骶骨翼重叠;2型,0＜TSD≤7 mm;3型,TSD＞7 mm.基于腰骶三角分型指导822例患者L5S,内镜手术入路和方式,包括椎板间入路单轴内镜、椎间孔入路单轴内镜、椎间孔开窗入路可动式椎间盘镜和单侧双通道内镜,所有患者术后即刻、术后半年和末次随访的VAS评分和ODI均小于术前,差异有统计学意义(P＜0.05).末次随访时Macnab评分优278例、良475例、可69例,优良率91.6％(753/822),无一例出现腰椎失稳.结论 腰骶三角分型简单实用,可有效指导L5S1内镜手术.
Abstract
Objective To establish a lumbosacral triangle(composed of L5 transverse process,S1 superior articular pro-cess,sacral ala and iliac crest)classification and to guide L5S1 endoscopic surgery.Methods A total of 647 patients with low back pain who admitted to Tianjin Hospital from January 2016 to October 2018 were retrospectively analyzed,including 315 males and 332 females,aged 42.9±15.1 years(range,19-74 years).The L5 transverse process sacral distance(TSD),inter trans-verse process length(ITL),interlaminar width(ILW),interlaminar height(ILH),iliosacral angle(ISA),iliac crest height(IH),inter-vertebral space height(ISH),intervertebral foramen height(IFH),and intervertebral foramen width(IFW)were measured based on lumbar spine anterior-posterior and lateral radiographs.Spearman correlation analysis and hierarchical cluster analysis were used to establish the lumbosacral triangle classification.A total of 822 patients underwent endoscopic LsS1 surgery based on lumbosa-cral triangle classification guidance and verification in Tianjin Hospital from January 2020 to December 2022,including 421 males and 401 females,aged 45.1±16.7 years(range,15-79 years).The visual analogue scale(VAS)and Oswestry disability in-dex(ODI)were compared before and after surgery,and the Macnab criteria were used to assess surgical outcomes.Results Spearman correlation analysis showed positive correlations between IH and ISA(r=0.75,P＜0.001),IFH and IFW(r=0.60,P＜0.001),TSD and IFH(r=0.53,P＜0.001),and TSD and IFW(r=0.40,P＜0.001).There was a negative correlation between TSD and IH(r=-0.46,P＜0.001),TSD and ISA(r=-0.42,P＜0.001),IFW and ISA(r=-0.41,P＜0.001),IFW and IH(r=-0.50,P＜0.001),IFH and IH(r=-0.42,P＜0.001).According to Spearman correlation analysis,hierarchical cluster analysis and receiver op-erating characteristic curve,lumbosacral angle was divided into three types:Type 1,L5 transverse process overlapped with sacral alar;Type 2,0＜TSD≤7 mm;Type 3,TSD＞7 mm.Based on lumbosacral triangle classification,different endoscopic techniques were used at L5S1 in 822 patients,including interlaminar approach single-axis endoscopy,trans-foraminal approach single-axis en-doscopy,trans-foraminal fenestration approach mobile microendoscopy and unilateral biportal endoscopy,the VAS and ODI of all the patients decreased than those preoperative in immediate postoperative period,half a year postoperative period and the final fol-low up,and the difference was statistically significant(P＜0.05).At the last follow-up,the Macnab score was excellent in 278 cas-es,good in 475 cases,and fair in 69 cases,with an excellent and good rate of 91.6％(753/822).Conclusion Lumbosacral trian-gle classification is simple and practical,and can effectively guide LsS1 endoscopic surgery.
基金项目
天津市卫生健康委高层次人才工程(TJSHHYXXZ-D2-010)
NETL
NSTL
万方数据