1. Predicting Metacarpal Anatomic Lengths via Adjacent Metacarpals
- Author
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Asher Lichtig, MD, Alfonso Mejia, MD, Marc Lipman, MD, Feddy P. Jacome, BS, and Farid Amirouche, PhD
- Subjects
Biomechanics ,Fracture ,Length ,Metacarpal ,Prediction ,Surgery ,RD1-811 - Abstract
Purpose: The purpose of this study is to generate validated prediction rules for metacarpal lengths that can be applied without the need for computation tools to assist with restoration of anatomic length after fracture and utilizes only ipsilateral metacarpals. Methods: The anatomic lengths of all hand bones in 50 hands (25 men, 25 women) were used along with linear regression subset analysis to determine which metacarpals are the most predictive of each other. The most predictive metacarpals were then used to generate simple addition and subtraction prediction rules via simplifying the linear equation generated with linear regression analysis. Those rules were then applied to subsequent test cases, and percent accuracy within various cutoffs were analyzed and compared to the accuracy when using the contralateral side. Results: The prediction rules were generated and were found to be identical for both men and women. When applied to the test cases, the estimated metacarpal lengths were within 3 mm of the actual value in 97.5% of the cases for women and 90% of the cases for men compared to 95% when using the contralateral side. Conclusion: The simple additional and subtraction rules generated in this analysis were as good as or superior to using the contralateral side in all cases for women and were as good as or superior to using the contralateral side in for metacarpals 3–5 for men. Clinical Relevance: Using these simple estimating rules may be superior to using the contralateral side in most cases and provides a secondary method for determining anatomic lengths when contralateral radiographs are not available or when contralateral radiographs were obtained in different enough conditions such that the lengths may not be representative of the hand of interest.
- Published
- 2024
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