Encephalometric features of cranial structure in patients with achondroplasia, and statistical methods of expert diagnostics

Klimov O.V. Gaidyshev I.P.

Journal: Гений ортопедии @geniy-ortopedii

Section: Оригинальные статьи

Article in issue: 1, 2014.

Free access

Purpose. To reveal the diagnostically significant and statistically reliable anthropometric features of cranial structure in patients with achondroplasia. To study the possibility of using the methods of mathematical statistics based on the results for differential diagnostics versus skeletal dysplasiae of other types by the head anthropometric characteristics. Materials and Methods. The photos of 25 patients with achondroplasia, and 15 patients with hypochondroplasia treated at RISC RTO in the period of 2007-2012 studied, as well as those of 25 normal subjects who were included in the control (reference) group. All the subjects were Caucasians. Two statistical methods realized in «AtteStat» special program used for mathematical analyzing the data in order to study the possibility of differential computed diagnosing the diseases. Standard encephalometric points which can be rather clearly presented on human head, the photo including, were selected for the study. Results. The data of anthropometric features of the head structure in patients with achondroplasia have been obtained for the first time. The cephalometric indexes obtained based on performed measurings among which the most diagnostically significant values revealed by the methods of mathematical statistics. Conclusion. The analysis of the values revealed by the method of multiple logistic regression made it possible to obtain a parametric value reflecting the probability of the disease presence in a particular patient with a given set of anthropometric characteristics.

achondroplasia \ limb lengthening \ systemic skeletal diseases \ diagnostics \ statistical analysis \ cephalometric indexes \ the method of multiple logistic regression

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Short address: https://sciup.org/142121734

IDS: 142121734   |   UDC: 611.714/.716-071.3:616.71-007.157:519.2