Prediction of the mesiodistal widths of maxillary permanent canines and premolars. |
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| Authors: | R N Staley J F Hoag |
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| Affiliation: | 1. Institute of Traditional Chinese Medicine and Natural Products, Jinan University, Guangzhou, China;2. Food and Nutritional Sciences Programme, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong Special Administrative Region, China;3. School of Life Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong Special Administrative Region, China;1. Department of Dental Technology, College of Applied Medical Sciences, King Khalid University, Saudi Arabia;2. Department of Oral Medical & Radiology, Sri Rajiv Gandhi College of Dental Sciences and Hospital, India;3. Department of Biomedical and Surgical and Biomedical Sciences, Catania University, 95123, Catania, Italy;4. Multidisciplinary Department of Medical-Surgical and Odontostomatological Specialties, University of Campania “Luigi Vanvitelli”, 80121, Naples, Italy;1. Medical Student, Yale School of Medicine, New Haven, CT;2. Medical Student, Yale School of Medicine, New Haven, CT;3. Craniofacial Fellow, Yale Plastic Surgery, New Haven, CT;4. Chief, Oral Maxillofacial Surgery, Director of Craniofacial Surgery, Yale Plastic Surgery, New Haven, CT |
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| Abstract: | Multiple regression equations for prediction of the mesiodistal widths of the maxillary canines and premolars were developed for the right and left sides of the arches of males and females. The equations were developed from longitudinal data taken from ninety-two Caucasian children (forty-six boys and forty-six girls) who participated in the Iowa Growth Study. The multiple regression equations, when compared with three currently used methods of prediction, were the best predictors. The newly developed equations and other prediction methods currently in use were tested on longitudinal data taken from a sample of forty-three Caucasian orthodontic patients (sixteen males and twenty-seven females). Again, the multiple regression equations had the best performance. |
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