Cervical vertebral maturation method-effect of clinical experience on the reproducibility
Journal Title: International Journal of Oral Health Dentistry - Year 2016, Vol 2, Issue 4
Abstract
Objectives: To assess interobserver an intraobserver reproducibility of the cervical vertebrae maturation method (CVMM) among three panels of judges with different levels of orthodontic experience (OE). Sample: Samples were collected from subjects from the Department of Orthodontics, who wanted to undergo fixed orthodontic therapy. Materials and Methods: Twenty good quality individual lateral cephalograms of patients seeking orthodontic treatment, with complete visualization of cervical vertebrae 1 through 4, were selected for our sample. Age ranging from 11 to 25 years of both the sexes. Thirty clinicians, divided according to their orthodontic experience into three groups (junior group, JU, OE up to 1 year; postgraduate group, PG, 2 OE up to 3years ;specialist group, SP, OE up to 7 years) evaluated the cephalograms in two sessions (T1 and T2) at 3 weeks apart. Results: The statistical assessment of inter-observer agreement at two time points (T1 and T2). ***P-value<0.001 (Statistically Highly Significant). 1. The Kendall’s W coefficient for each group varied from 0.597 to 0.982 at T1 and varied from 0.779 to 0.975 at T2. 2. The inter-observer agreement was highest for Specialist followed by Post-graduates and it was lowest for the Juniors (P-value<0.001 for all) in both the time intervals. — The statistical assessment of intra-observer agreement. — ***P-value<0.001 (Statistically Highly Significant). 1. The Cohen’s kappa coefficient for each group varied from 0.154 to 0.965 for all observers. 2. The intra-observer agreement was highest for Post-graduates followed by Specialists and it was lowest for the Juniors (P-value<0.001 for all). Conclusion: The group with the highest level of OE had the best performance. Hence, high level of orthodontic experience does increase the reproducibility of the CVMM
Authors and Affiliations
Almas Khanum, Ajit Kalia, Gaurav Gupta, Sonali Khandekar, Wasu Patil
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