Author/Editor     Primožič, Jasmina
Title     Uporabnost okluzijskih indeksov pri triaži pacientov v zobozdravstveni ordinaciji
Type     monografija
Place     Ljubljana
Publisher     Univerza v Ljubljani, Mediciska fakulteta
Publication year     2006
Volume     str. 49
Language     slo
Abstract     Background. Triage of orthodontic patients is frequently left to the subjective judgement of specialists.To overcome this problem, many occlusal indices were developed in order to assess and classify malocclusion. Each of them has its advantages and disadvantages, but there is no universally accepted method for measuring malocclusion. Aim. The purpose of this study was to select the best suitable index for the Slovene population from the most widely used indices in Europe. The aim of the study was to compare the reliability, reproducibility and the time needed for evaluating malocclusion with the EFO index and the Index of Orthodontic Treatment Need (IOTN). Hypothesis. The EFO index and the IOTN do not differ in the assessment and classification of malocclusion. The intra-examiner agreement and the inter-examiner agreement for both the indices are perfect. Taking into account the number of morphological features that each method measures, we expect the EFO index to be more time-consuming than the IOTN. Methods. Study models of the permanent dentition of 100 patients (53 female, 47 male, mean age = 15,4), who were randomly selected from a population of people referred to the orthodontic centre, were evaluated with the EFO index and the IOTN. The association between the two indices in classifying malocclusion was tested using the classification with the EF index as the gold standard. To evaluate the intra- and inter-examiner agreement, the ICC (intra-class correlation coefficient) was used. To compare the differences in time consumption the paired two-tailed Student t-test was used. Results. There was a perfect agreement between the EFO and EF indices (ICC = 0,930) and a good agreement between the IOTN and the EF index. (ICC = 0,572). Abstract truncated at 2000 characters.