Konno Shinichi, Hayashino Yasuaki, Fukuhara Shunichi, Kikuchi Shinichi, Kaneda Kiyoshi, Seichi Atsushi, Chiba Kazuhiro, Satomi Kazuhiko, Nagata Kensei, Kawai Shinya
Department of Orthopaedic Surgery, Fukuhsima Medical University, Hikarigaoka 1, Fukushima, 960-1295, Japan.
Eur Spine J. 2007 Nov;16(11):1951-7. doi: 10.1007/s00586-007-0402-2. Epub 2007 Jun 5.
No clinical diagnostic support tool can help identify patients with LSS. Simple diagnostic tool may improve the accuracy of the diagnosis of LSS. The aim of this study was to develop a simple clinical diagnostic tool that may help physicians to diagnose LSS in patients with lower leg symptoms. Patients with pain or numbness of the lower legs were prospectively enrolled. The diagnosis of LSS by experienced orthopedic specialists was the outcome measure. Multivariable logistic regression analysis identified factors that predicted LSS; a simple clinical prediction rule was developed by assigning a risk score to each item based on the estimated beta-coefficients. From December 2002 to December 2004, 104 orthopedic physicians from 22 clinics and 50 hospitals evaluated 468 patients. Two items of physical examination, three items of patients' symptom, and five items of physical examination were included in the final scoring system as a result of multiple logistic regression analysis. The sum of the risk scores for each patient ranged from -2 to 16. The Hosmer-Lemeshow statistic was 11.30 (P = 0.1851); the area under the ROC curve was 0.918. The clinical diagnostic support tool had a sensitivity of 92.8% and a specificity of 72.0%. The prevalence of LSS was 6.3% in the bottom quartile of the risk score (-2 to 5) and 99.0% in the top quartile (12 to 16). We developed a simple clinical diagnostic support tool to identify patients with LSS. Further studies are needed to validate this tool in primary care settings.
没有临床诊断支持工具能够帮助识别腰椎管狭窄症患者。简单的诊断工具可能会提高腰椎管狭窄症诊断的准确性。本研究的目的是开发一种简单的临床诊断工具,以帮助医生诊断有小腿症状的患者。前瞻性纳入有小腿疼痛或麻木的患者。由经验丰富的骨科专家做出的腰椎管狭窄症诊断为观察指标。多变量逻辑回归分析确定了预测腰椎管狭窄症的因素;通过根据估计的β系数为每个项目赋予风险评分,制定了一个简单的临床预测规则。2002年12月至2004年12月,来自22个诊所和50家医院的104名骨科医生对468例患者进行了评估。经过多变量逻辑回归分析,最终评分系统纳入了两项体格检查项目、三项患者症状项目和五项体格检查项目。每位患者的风险评分总和为-2至16。Hosmer-Lemeshow统计量为11.30(P = 0.1851);ROC曲线下面积为0.918。该临床诊断支持工具的敏感性为92.8%,特异性为72.0%。在风险评分最低四分位数(-2至5)中,腰椎管狭窄症的患病率为6.3%,在最高四分位数(12至16)中为99.0%。我们开发了一种简单的临床诊断支持工具来识别腰椎管狭窄症患者。需要进一步研究以在初级保健环境中验证该工具。