The reliability of the augmented Lehnert-Schroth and Rigo classification in scoliosis management.

IF 1 Q4 REHABILITATION South African Journal of Physiotherapy Pub Date : 2021-11-02 eCollection Date: 2021-01-01 DOI:10.4102/sajp.v77i2.1568
Burçin Akçay, Tuğba Kuru Çolak, Adnan Apti, İlker Çolak, Önder Kızıltaş
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引用次数: 3

Abstract

Background: 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.

Objective: To test the reliability of the augmented Lehnert-Schroth (ALS) classification and the Rigo classification.

Methods: 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.

Results: 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.

Conclusions: 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.

Clinical implications: 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.

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增强Lehnert-Schroth和Rigo分类在脊柱侧凸治疗中的可靠性。
背景:在特定模式的脊柱侧凸练习和支具中,根据不同的曲线模式,矫正治疗方案有所不同。调查常用分类系统可靠性的研究数量有限。目的:检验增强Lehnert-Schroth (ALS)分类法和Rigo分类法的可靠性。方法:由第一作者将45例脊柱侧凸患者的x光片和后侧照每隔1周发给3位临床医生两次。临床医生根据ALS和Rigo分类对图像进行分类,并用SPSS V-16软件对数据进行分析。计算类内相关系数(ICCs)和标准误差测量(SEM)来评估观察者之间和观察者内部的可靠性。结果:x线图像的观察者间ICC值分别为0.552 (ALS)和0.452 (Rigo),照片的观察者间ICC值分别为0.494 (ALS)和0.518 (Rigo)。x射线图像的平均观察者内ICC值为0.720 (ALS)、0.581 (Rigo),照片的平均观察者内ICC值为0.726 (ALS)、0.467 (Rigo)。结论:我们的研究结果表明,使用ALS分类的x线图像和使用Rigo分类的临床照片具有中等的观察者间可靠性。使用ALS分类的x线图像和临床照片的观察者内信度为中等至良好,使用Rigo分类的x线图像和临床照片的观察者内信度为差至中等。临床意义:模式分类有助于在特定脊柱侧凸物理治疗和特定模式支架应用和手术治疗中制定计划和矫正指征。需要更多的子类型来处理单个的曲率模式。曲线分类的优化将有可能减少诊断和治疗的失败。
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来源期刊
CiteScore
1.70
自引率
9.10%
发文量
35
审稿时长
30 weeks
期刊最新文献
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