101. Patella height measurements in patients with patellofemoral instability: the power to predict patella height indices.
- Author
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Picken S, Summers H, and Al-Dadah O
- Subjects
- Humans, Radiography, Magnetic Resonance Imaging methods, Knee Joint, Patella diagnostic imaging, Patellofemoral Joint diagnostic imaging
- Abstract
Introduction: Numerous indices for patella height measurement are described in the literature; however, there is not a universally accepted 'gold standard'. Choice of indices varies depending on personal preference and previous experience, making it difficult to compare results between studies. The aims of this study were to assess the correlation between different patella height indices and generate statistically derived formulae that can be used to predict the value of one patella height ratio when another is known., Materials and Methods: Patients with patellofemoral instability were radiologically evaluated using both X-ray and Magnetic Resonance Imaging (MRI) of the knee. Two observers measured six validated patella height indices at two separate time intervals. All measurements were aggregated together and a mean average for each patella height ratio was calculated. These results were then statistically analysed using Pearson product-moment correlation and linear regression tests., Results: Forty-four patients were included in the study. A statistically significant correlation was found between the majority of patella height ratios. On X-ray, the strongest correlation (r = 0.92, p < 0.001) and regression (R
2 = 0.85, p < 0.001) coefficients were between the Blackburne-Peel and Caton-Dechamps ratios, with the formula; CD = 0.20 + (0.95xBP). On MRI, the strongest correlation (r = - 0.84, p < 0.001) and regression (R2 = 0.71, p < 0.001) coefficients were between the Patellophyseal index and Patellotrochlear index, with the formula; PP = 1.02-(1.10xPT)., Conclusion: The formulae produced in this study can predict the value of one patella height ratio when the results of another are known. This could facilitate systematic reviews and meta-analyses by allowing the pooling together of data from many studies., (© 2024. Crown.)- Published
- 2024
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