Akçay Burçin, Çolak Tuğba Kuru, Apti Adnan, Çolak İlker, Kızıltaş Önder
Department of Physiotherapy and Rehabilitation, Faculty of Healthy Sciences, Bandırma Onyedi Eylül University, Balıkesir, Turkey.
Department of Physiotherapy and Rehabilitation, Faculty of Health Sciences, Marmara University, Istanbul, Turkey.
S Afr J Physiother. 2021 Nov 2;77(2):1568. doi: 10.4102/sajp.v77i2.1568. eCollection 2021.
In pattern-specific scoliosis exercises and bracing, the corrective treatment plan differs according to different curve patterns. There are a limited number of studies investigating the reliability of the commonly used classifications systems.
To test the reliability of the augmented Lehnert-Schroth (ALS) classification and the Rigo classification.
X-rays and posterior photographs of 45 patients with scoliosis were sent by the first author to three clinicians twice at 1-week intervals. The clinicians classified images according to the ALS and Rigo classifications, and the data were analysed using SPSS V-16. Intraclass correlation coefficients (ICCs) and standard error measurement (SEM) were calculated to evaluate the inter- and intra-observer reliability.
The inter-observer ICC values were 0.552 (ALS), 0.452 (Rigo) for X-ray images and 0.494 (ALS), 0.518 (Rigo) for the photographs. The average intra-observer ICC value was 0.720 (ALS), 0.581 (Rigo) for the X-ray images and 0.726 (ALS) and 0.467 (Rigo) for the photographs.
The results of our study indicate moderate inter-observer reliability for X-ray images using the ALS classification and clinical photographs using the Rigo classification. Intra-observer reliability was moderate to good for X-ray images and clinical photographs using the ALS classification and poor to moderate for X-ray and clinical photographs using the Rigo classification.
Pattern classifications assist in creating a plan and indication of correction in specific scoliosis physiotherapy and pattern-specific brace applications and surgical treatment. More sub-types are needed to address the individual patterns of curvature. The optimisation of curve classification will likely reduce failures in diagnosis and treatment.
在特定模式的脊柱侧弯运动疗法和支具治疗中，矫正治疗方案因不同的侧弯模式而异。对常用分类系统可靠性进行研究的数量有限。
检验增强型Lehnert-Schroth（ALS）分类法和Rigo分类法的可靠性。
第一作者将45例脊柱侧弯患者的X线片和后前位照片每隔1周分两次发给3位临床医生。临床医生根据ALS和Rigo分类法对图像进行分类，数据使用SPSS V-16进行分析。计算组内相关系数（ICC）和标准误测量值（SEM）以评估观察者间和观察者内的可靠性。
对于X线图像，观察者间ICC值分别为0.552（ALS）、0.452（Rigo）；对于照片，观察者间ICC值分别为0.494（ALS）、0.518（Rigo）。对于X线图像，观察者内平均ICC值分别为0.720（ALS）、0.581（Rigo）；对于照片，观察者内平均ICC值分别为0.726（ALS）、0.467（Rigo）。
我们的研究结果表明，使用ALS分类法的X线图像和使用Rigo分类法的临床照片的观察者间可靠性为中等。使用ALS分类法的X线图像和临床照片的观察者内可靠性为中等至良好，而使用Rigo分类法的X线图像和临床照片的观察者内可靠性为差至中等。
模式分类有助于制定特定脊柱侧弯物理治疗、特定模式支具应用和手术治疗的矫正计划及指征。需要更多的子类型来处理个体的弯曲模式。优化曲线分类可能会减少诊断和治疗的失败。
