- 期刊
- OpenAccess
Sex Prediction Assessment via Mandibular Canine Index and Logistic Regression in Pakistani Population: A Digital Model Study
摘要
The prime aim of the study was to establish sex prediction assessment via mandibular canine index (MCI) and logistic regression in Pakistani population thorough a digital model study. The selected sample consisted of 128 subjects with the ages ranged from 18 to 24 years. The mesiodistal and buccolingual tooth size were measured via scanned digital dental models. Male's measured canine width and MCI is larger than female. SMCI anticipated erroneously 48% male and 51% female. Sex assessment via binary logistic regression (BLR) for inclusion of two (MD 43 and LICW) variables showed the overall percentage of prediction were 66.4%, and 64.1% and 68.8% for male and female respectively. BLR for inclusion of more tooth size (MD and BL widths of maxillary and mandibular right side) variables. The overall percentages of prediction were 75.4%, with 80% and 71% for male and female respectively. The Rao index is not a reliable way for the sex identification in Pakistani population. BLR sex prediction models is applicable for Pakistani population.
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