Novel Screening Tool for Adolescent Idiopathic Scoliosis: A Reliability Study

• Published in: Journal of manipulative and physiological therapeutics 2022-06, Vol.45 (5), p.358-364
• Main Authors: Engel, Roger, McAviney, Jeb, Graham, Petra L., Anderson, Peter J., Brown, Benjamin T.
• Format: Article
• Language: English
• Subjects: Adolescent; Child; Diagnostic Techniques and Procedures; Female; Humans; Kyphosis; Male; Mass Screening; Reproducibility of Results; Risk Factors; Scoliosis; Scoliosis - diagnosis; Software
• ISSN: 0161-4754; 1532-6586; 1532-6586
• DOI: 10.1016/j.jmpt.2022.08.001

The aim of this study was to assess the agreement between a web-based scoliosis screening tool and a standard screening procedure. Sixty participants were selected (median age, 12 years; 75% were women) and separated into 2 groups: those with unknown spinal curvature status and those with confirmed scoliosis. Each participant was assessed by 2 blinded assessors, with one measuring the angle of trunk rotation using a scoliometer and the second using a web-based screening application. The app provided a relative risk score for having scoliosis based on a weighted algorithm. Those with an angle of trunk rotation ≥7° or risk score >2 were deemed as being at risk for having scoliosis. There was fair agreement (kappa = 0.34; 95% confidence interval [CI], 0.14-0.55; P < .001) between the app and the scoliometer among the unconfirmed cases. The McNemar test indicated a difference in the proportion of positive tests (P = .001), whereby the screening app produced a significantly higher number of positive tests (15/53 = 28.3%) compared to the standard screening procedure (4/53 = 7.5%) for unconfirmed cases. Among the confirmed cases, the app correctly identified 5 out of 7 (sensitivity: 71%; 95% CI, 29%-96%) participants, whereas the scoliometer correctly identified 6 out of 7 (sensitivity: 86%; 95% CI, 42%-100%) participants. These findings indicate fair agreement between the app and the scoliometer, though it was not possible to precisely estimate the sensitivity of the app in this study.