The reliability of the augmented Lehnert-Schroth and Rigo classification in scoliosis management
South African Journal of Physiotherapy
| Field | Value | |
| Title | The reliability of the augmented Lehnert-Schroth and Rigo classification in scoliosis management | |
| Creator | Akçay, Burçin Kuru Çolak, Tuğba Apti, Adnan Çolak, İlker Kızıltaş, Önder | |
| Description | 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. | |
| Publisher | AOSIS | |
| Date | 2021-11-02 | |
| Identifier | 10.4102/sajp.v77i2.1568 | |
| Source | South African Journal of Physiotherapy; Vol 77, No 2 (2021); 5 pages 2410-8219 0379-6175 | |
| Language | eng | |
| Relation |
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https://sajp.co.za/index.php/sajp/article/view/1568/2632
https://sajp.co.za/index.php/sajp/article/view/1568/2633
https://sajp.co.za/index.php/sajp/article/view/1568/2634
https://sajp.co.za/index.php/sajp/article/view/1568/2635
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