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Prediction of osteoporosis using dental radiographs and age in females

AIMS AND OBJECTIVES: To evaluate the role of dental radiograph as a screening tool for diagnosis of osteoporosis in females. MATERIALS AND METHODS: In the present study, 50 women between the age group of 40-60 were recruited, and patients with systemic disorder and taking calcium supplements, and wo...

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Autores principales: Vijay, Guduba, Chitroda, Parita K., Katti, Girish, Shahbaz, Syed, Baba, Irfan, Bhuvaneshwari
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481743/
https://www.ncbi.nlm.nih.gov/pubmed/26167057
http://dx.doi.org/10.4103/0976-7800.158952
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author Vijay, Guduba
Chitroda, Parita K.
Katti, Girish
Shahbaz, Syed
Baba, Irfan
Bhuvaneshwari,
author_facet Vijay, Guduba
Chitroda, Parita K.
Katti, Girish
Shahbaz, Syed
Baba, Irfan
Bhuvaneshwari,
author_sort Vijay, Guduba
collection PubMed
description AIMS AND OBJECTIVES: To evaluate the role of dental radiograph as a screening tool for diagnosis of osteoporosis in females. MATERIALS AND METHODS: In the present study, 50 women between the age group of 40-60 were recruited, and patients with systemic disorder and taking calcium supplements, and women who are not willing for investigation were excluded. Their detailed medical history was obtained and dental radiographs were made, bone mineral density was measured at left radial bone using ultrasound. The radiographs were subjected to image analysis method using manual tracing of gonial angle, antegonial angle, antegonial depth, antegonial index, mental index and mandibular cortical index. Statistical discrimination analysis was applied to predict the presence of osteoporosis. With use of these indices, the sensitivity and specificity of orthopantomograph (OPG) radiograph to assess age-related changes in bone were compared. Radiomorphometric indices (RMI) were also scrutinized to depict the sensitivity and specificity of each index in the prediction of osteoporosis. RESULTS: Study results showed no significant differences between bone mineral density (BMD) and radiomorphometric analysis in the diagnoses of osteoporotic females. Out of 29, diagnosed as osteoporotic by radiograph 23 were confirmed by BMD and six were diagnosed as osteopenic. Among the six indices used, AGA and AGD showed more reproducible results. CONCLUSION: With our study results, we come to an arrival that OPG radiographs show overall sensitivity of 0.75 or 75% and specificity of 0.81 or 81% in the diagnosis of osteoporosis, and that anti gonial angle (AGA) and anti gonial depth (AGD) are the most reliable indices. Hence, we conclude that panoramic-based RMI can be used as an ancillary method in the diagnosis of osteoporosis.
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spelling pubmed-44817432015-07-12 Prediction of osteoporosis using dental radiographs and age in females Vijay, Guduba Chitroda, Parita K. Katti, Girish Shahbaz, Syed Baba, Irfan Bhuvaneshwari, J Midlife Health Original Article AIMS AND OBJECTIVES: To evaluate the role of dental radiograph as a screening tool for diagnosis of osteoporosis in females. MATERIALS AND METHODS: In the present study, 50 women between the age group of 40-60 were recruited, and patients with systemic disorder and taking calcium supplements, and women who are not willing for investigation were excluded. Their detailed medical history was obtained and dental radiographs were made, bone mineral density was measured at left radial bone using ultrasound. The radiographs were subjected to image analysis method using manual tracing of gonial angle, antegonial angle, antegonial depth, antegonial index, mental index and mandibular cortical index. Statistical discrimination analysis was applied to predict the presence of osteoporosis. With use of these indices, the sensitivity and specificity of orthopantomograph (OPG) radiograph to assess age-related changes in bone were compared. Radiomorphometric indices (RMI) were also scrutinized to depict the sensitivity and specificity of each index in the prediction of osteoporosis. RESULTS: Study results showed no significant differences between bone mineral density (BMD) and radiomorphometric analysis in the diagnoses of osteoporotic females. Out of 29, diagnosed as osteoporotic by radiograph 23 were confirmed by BMD and six were diagnosed as osteopenic. Among the six indices used, AGA and AGD showed more reproducible results. CONCLUSION: With our study results, we come to an arrival that OPG radiographs show overall sensitivity of 0.75 or 75% and specificity of 0.81 or 81% in the diagnosis of osteoporosis, and that anti gonial angle (AGA) and anti gonial depth (AGD) are the most reliable indices. Hence, we conclude that panoramic-based RMI can be used as an ancillary method in the diagnosis of osteoporosis. Medknow Publications & Media Pvt Ltd 2015 /pmc/articles/PMC4481743/ /pubmed/26167057 http://dx.doi.org/10.4103/0976-7800.158952 Text en Copyright: © Journal of Mid-life Health http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Original Article
Vijay, Guduba
Chitroda, Parita K.
Katti, Girish
Shahbaz, Syed
Baba, Irfan
Bhuvaneshwari,
Prediction of osteoporosis using dental radiographs and age in females
title Prediction of osteoporosis using dental radiographs and age in females
title_full Prediction of osteoporosis using dental radiographs and age in females
title_fullStr Prediction of osteoporosis using dental radiographs and age in females
title_full_unstemmed Prediction of osteoporosis using dental radiographs and age in females
title_short Prediction of osteoporosis using dental radiographs and age in females
title_sort prediction of osteoporosis using dental radiographs and age in females
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481743/
https://www.ncbi.nlm.nih.gov/pubmed/26167057
http://dx.doi.org/10.4103/0976-7800.158952
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