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    Age prediction formulae from radiographic assessment of skeletal maturation at the knee in an Irish population.

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    Authors
    O'Connor, Jean E
    Coyle, Joseph
    Bogue, Conor
    Spence, Liam D
    Last, Jason
    Affiliation
    UCD School of Medicine and Medical Science, Health Sciences Centre, University College Dublin, Belfield, Dublin 4, Ireland. Electronic address: jean.oconnor@ucd.ie.
    Issue Date
    2014-01
    Keywords
    BONE DENSITY
    Local subject classification
    KNEE
    
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    Citation
    Age prediction formulae from radiographic assessment of skeletal maturation at the knee in an Irish population. 2014, 234:188.e1-8 Forensic Sci. Int.
    Journal
    Forensic science international
    URI
    http://hdl.handle.net/10147/325958
    DOI
    10.1016/j.forsciint.2013.10.032
    PubMed ID
    24262807
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S0379073813004775
    Abstract
    Age estimation in living subjects is primarily achieved through assessment of a hand-wrist radiograph and comparison with a standard reference atlas. Recently, maturation of other regions of the skeleton has also been assessed in an attempt to refine the age estimates. The current study presents a method to predict bone age directly from the knee in a modern Irish sample. Ten maturity indicators (A-J) at the knee were examined from radiographs of 221 subjects (137 males; 84 females). Each indicator was assigned a maturity score. Scores for indicators A-G, H-J and A-J, respectively, were totalled to provide a cumulative maturity score for change in morphology of the epiphyses (AG), epiphyseal union (HJ) and the combination of both (AJ). Linear regression equations to predict age from the maturity scores (AG, HJ, AJ) were constructed for males and females. For males, equation-AJ demonstrated the greatest predictive capability (R(2)=0.775) while for females equation-HJ had the strongest capacity for prediction (R(2)=0.815). When equation-AJ for males and equation-HJ for females were applied to the current sample, the predicted age of 90% of subjects was within ±1.5 years of actual age for male subjects and within +2.0 to -1.9 years of actual age for female subjects. The regression formulae and associated charts represent the most contemporary method of age prediction currently available for an Irish population, and provide a further technique which can contribute to a multifactorial approach to age estimation in non-adults.
    Item Type
    Article
    Language
    en
    ISSN
    1872-6283
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.forsciint.2013.10.032
    Scopus Count
    Collections
    Cork University Hospital

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