Djorojevic Mirjana, Roldán Concepción, Botella Miguel, Alemán Inmaculada
Department of Legal Medicine, Toxicology and Physical Anthropology, Faculty of Medicine, University of Granada, 11 Madrid Av., Granada, 18012, Spain.
Department of Biostatistics, Faculty of Medicine, University of Granada, 11 Madrid Av., Granada, 18012, Spain.
Int J Legal Med. 2016 Jan;130(1):245-51. doi: 10.1007/s00414-015-1201-7. Epub 2015 May 8.
The current study was undertaken to test the validity and reproducibility of the Purkait triangle method and some alternative proposals for sex prediction from the proximal femur in the adult population of Spain. To that end, sexual dimorphism of the maximum femoral head diameter and the minimum femoral neck diameter were also evaluated. The study was conducted on 186 femora (109 males and 77 females) taken from the San José collection of identified individuals (Southern Spain). Discriminant function analyses (DFA) employing the jackknife procedure for cross-validations were considered. Overall, more than 94% of individuals of both sexes were correctly classified. The most dimorphic single variable from the triangle method was the intertrochanteric apex distance (BC) that reached 85.5% accuracy, falling below those obtained for the femoral head and femoral neck diameter, respectively, (89.8 and 91.9%). Combining BC with the neck diameter, the predictive ability increased to 92.5%; when femoral head diameter was added to the latter two, the classification success rate improved further up to 94.6% (94.1% after cross-validation). We conclude that the classification success rates of the Purkait's method remained considerably below any of those obtained with the models proposed in the present study which proved to be a much better and more reliable choice both as single predictors and in combination with other variables.
本研究旨在检验Purkait三角法以及一些关于西班牙成年人群近端股骨性别预测的替代方案的有效性和可重复性。为此,还评估了股骨头最大直径和股骨颈最小直径的性别二态性。该研究对取自西班牙南部圣何塞已识别个体样本库的186根股骨(109例男性和77例女性)进行。采用留一法交叉验证的判别函数分析(DFA)。总体而言,超过94%的男女个体被正确分类。三角法中最具二态性的单一变量是转子间顶点距离(BC),其准确率达到85.5%,分别低于股骨头和股骨颈直径的准确率(89.8%和91.9%)。将BC与颈直径相结合,预测能力提高到92.5%;当在后两者基础上加入股骨头直径时,分类成功率进一步提高到94.6%(交叉验证后为94.1%)。我们得出结论,Purkait方法的分类成功率远低于本研究提出的模型所获得的任何成功率,本研究提出的模型无论是作为单一预测指标还是与其他变量结合使用,都被证明是更好、更可靠的选择。