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Prediction of lip response to orthodontic treatment using a multivariable regression model
BACKGROUND: This was a retrospective cephalometric study to develop a more precise estimation of soft tissue changes related to underlying tooth movment than simple relatioship betweenhard and soft tissues. MATERIALS AND METHODS: The lateral cephalograms of 61 adult patients undergoing orthodontic t...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4770468/ https://www.ncbi.nlm.nih.gov/pubmed/26962314 http://dx.doi.org/10.4103/1735-3327.174697 |
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author | Shirvani, Amin Sadeghian, Saeid Abbasi, Safieh |
author_facet | Shirvani, Amin Sadeghian, Saeid Abbasi, Safieh |
author_sort | Shirvani, Amin |
collection | PubMed |
description | BACKGROUND: This was a retrospective cephalometric study to develop a more precise estimation of soft tissue changes related to underlying tooth movment than simple relatioship betweenhard and soft tissues. MATERIALS AND METHODS: The lateral cephalograms of 61 adult patients undergoing orthodontic treatment (31 = premolar extraction, 31 = nonextraction) were obtained, scanned and digitized before and immediately after the end of treatment. Hard and soft tissues, angular and linear measures were calculated by Viewbox 4.0 software. The changes of the values were analyzed using paired t-test. The accuracy of predictions of soft tissue changes were compared with two methods: (1) Use of ratios of the means of soft tissue to hard tissue changes (Viewbox 4.0 Software), (2) use of stepwise multivariable regression analysis to create prediction equations for soft tissue changes at superior labial sulcus, labrale superius, stomion superius, inferior labial sulcus, labrale inferius, stomion inferius (all on a horizontal plane). RESULTS: Stepwise multiple regressions to predict lip movements showed strong relations for the upper lip (adjusted R(2) = 0.92) and the lower lip (adjusted R(2) = 0.91) in the extraction group. Regression analysis showed slightly weaker relations in the nonextraction group. CONCLUSION: Within the limitation of this study, multiple regression technique was slightly more accurate than the ratio of mean prediction (Viewbox4.0 software) and appears to be useful in the prediction of soft tissue changes. As the variability of the predicted individual outcome seems to be relatively high, caution should be taken in predicting hard and soft tissue positional changes. |
format | Online Article Text |
id | pubmed-4770468 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-47704682016-03-09 Prediction of lip response to orthodontic treatment using a multivariable regression model Shirvani, Amin Sadeghian, Saeid Abbasi, Safieh Dent Res J (Isfahan) Original Article BACKGROUND: This was a retrospective cephalometric study to develop a more precise estimation of soft tissue changes related to underlying tooth movment than simple relatioship betweenhard and soft tissues. MATERIALS AND METHODS: The lateral cephalograms of 61 adult patients undergoing orthodontic treatment (31 = premolar extraction, 31 = nonextraction) were obtained, scanned and digitized before and immediately after the end of treatment. Hard and soft tissues, angular and linear measures were calculated by Viewbox 4.0 software. The changes of the values were analyzed using paired t-test. The accuracy of predictions of soft tissue changes were compared with two methods: (1) Use of ratios of the means of soft tissue to hard tissue changes (Viewbox 4.0 Software), (2) use of stepwise multivariable regression analysis to create prediction equations for soft tissue changes at superior labial sulcus, labrale superius, stomion superius, inferior labial sulcus, labrale inferius, stomion inferius (all on a horizontal plane). RESULTS: Stepwise multiple regressions to predict lip movements showed strong relations for the upper lip (adjusted R(2) = 0.92) and the lower lip (adjusted R(2) = 0.91) in the extraction group. Regression analysis showed slightly weaker relations in the nonextraction group. CONCLUSION: Within the limitation of this study, multiple regression technique was slightly more accurate than the ratio of mean prediction (Viewbox4.0 software) and appears to be useful in the prediction of soft tissue changes. As the variability of the predicted individual outcome seems to be relatively high, caution should be taken in predicting hard and soft tissue positional changes. Medknow Publications & Media Pvt Ltd 2016 /pmc/articles/PMC4770468/ /pubmed/26962314 http://dx.doi.org/10.4103/1735-3327.174697 Text en Copyright: © Dental Research Journal 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 Shirvani, Amin Sadeghian, Saeid Abbasi, Safieh Prediction of lip response to orthodontic treatment using a multivariable regression model |
title | Prediction of lip response to orthodontic treatment using a multivariable regression model |
title_full | Prediction of lip response to orthodontic treatment using a multivariable regression model |
title_fullStr | Prediction of lip response to orthodontic treatment using a multivariable regression model |
title_full_unstemmed | Prediction of lip response to orthodontic treatment using a multivariable regression model |
title_short | Prediction of lip response to orthodontic treatment using a multivariable regression model |
title_sort | prediction of lip response to orthodontic treatment using a multivariable regression model |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4770468/ https://www.ncbi.nlm.nih.gov/pubmed/26962314 http://dx.doi.org/10.4103/1735-3327.174697 |
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