The reliability of goniometric measurement of frontal knee alignment in standing in people with knee osteoarthritis: A pilot study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objectives Goniometry is a low-cost, high-access measure of frontal knee alignment in people with knee osteoarthritis (KOA). Previous literature has demonstrated the clinical relevance of measuring knee alignment; however, the reliability and associated measurement error of goniometer methods have not been adequately investigated. We sought to evaluate the reliability and measurement error of goniometric measurement of frontal alignment of the knee in standing individuals with KOA. Methods An intra- and inter-rater reliability study design was conducted. Twenty-six individuals with KOA based on clinical and radiological diagnosis criteria were recruited at a tertiary hospital health service. Frontal knee alignment was measured by two examiners (Examiner A, an experienced physiotherapist, and Examiner B, a final-year pre-registration physiotherapy student). Each examiner independently recorded two measures. Reliability, measurement error, and limits of agreement were evaluated using Intraclass Correlation Coefficients (ICCs; 3, k), standard error of measurement (SEM), and Bland–Altman plots, respectively. Results Excellent intra- (ICC = 0.99) and inter-rater reliability (ICC = 0.96) were demonstrated. Inter-rater SEM was 1.20°, while intra-rater SEM ranged between 0.58 and 0.59° for each examiner (MDC95 Examiner A: 1.64°, MDC95 Examiner B: 1.61°). Bland–Altman plots revealed LOA95 of, at worst, 5.8° between examiners and 2.4° for individual raters. Conclusion This study demonstrated excellent reliability (intra- and inter-rater) of goniometric frontal knee alignment measurement in people with KOA. However, to ensure high levels of reliability, measurement methods of alignment need to be standardized between practitioners so that clinical decisions can be confidently made based on this measure.
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4408241380