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A Meta-Analytic Review for the Patella Sexual Dimorphism Assessment/Una Revision Meta-Analitica para la Evaluacion del Dimorfismo Sexual de la Patela
Sexual dimorphism is one of the most important ways to identify bone remains in mass disasters. Many of them have been used for this purpose; mainly skull, pelvis and long bones. However, only a few studies using the patella have been done and, to our knowledge, there are no assessments of previous...
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Published in: | International journal of morphology 2020-12, Vol.38 (4), p.933 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Sexual dimorphism is one of the most important ways to identify bone remains in mass disasters. Many of them have been used for this purpose; mainly skull, pelvis and long bones. However, only a few studies using the patella have been done and, to our knowledge, there are no assessments of previous results in the literature. Meta-analysis provides a useful strong tool to test, in a systematic way, the most relevant information about a given research field. The aim of this study is to apply the meta-analytic technique to assess the major studies concerning sexual dimorphism in the patella by measuring classical metric traits: maximum height and maximum width, with different techniques, such as caliper, radiography, tomography and magnetic resonance. The 17 papers found, involving a total sample size higher than 2600 patellae, showed a very high heterogeneity- around 93 % of I2 value, for height and width measurements when all the studies were analyzed together. Homogeneity increased when each study was classified according to the techniques used. In this case, a statistical difference appeared, among the several subgroups of techniques for the two measurements, suggesting the importance of the methodology used. Maximum height and maximum width were all showed to be statistically relevant in distinguishing both sexes. KEY WORDS: Patella; Sex; Dimorphism; Meta-analysis; Systematic review. |
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ISSN: | 0717-9367 |