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Cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the Johnston County Osteoarthritis Project

BACKGROUND: Injury is an important risk factor for osteoarthritis (OA), a highly prevalent and disabling joint disease. Joint shape is linked to OA, but the interplay of injury and joint shape and their combined role in OA, particularly at the ankle, is not well known. Therefore, we explored cross-s...

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Autores principales: Nelson, Amanda E., Golightly, Yvonne M., Lateef, Shahmeer, Renner, Jordan B., Jordan, Joanne M., Aspden, Richard M., Hillstrom, Howard, Gregory, Jennifer S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5530536/
https://www.ncbi.nlm.nih.gov/pubmed/28770007
http://dx.doi.org/10.1186/s13047-017-0216-3
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author Nelson, Amanda E.
Golightly, Yvonne M.
Lateef, Shahmeer
Renner, Jordan B.
Jordan, Joanne M.
Aspden, Richard M.
Hillstrom, Howard
Gregory, Jennifer S.
author_facet Nelson, Amanda E.
Golightly, Yvonne M.
Lateef, Shahmeer
Renner, Jordan B.
Jordan, Joanne M.
Aspden, Richard M.
Hillstrom, Howard
Gregory, Jennifer S.
author_sort Nelson, Amanda E.
collection PubMed
description BACKGROUND: Injury is an important risk factor for osteoarthritis (OA), a highly prevalent and disabling joint disease. Joint shape is linked to OA, but the interplay of injury and joint shape and their combined role in OA, particularly at the ankle, is not well known. Therefore, we explored cross-sectional associations between ankle shape and injury in a large community-based cohort. METHODS: Ankles without radiographic OA were selected from the current data collection of the Johnston County OA Project. Ankles with self-reported prior injury were included as injury cases (n = 108) along with 1:1 randomly selected non-injured ankles. To define ankle shape, a 68 point model on weight-bearing lateral ankle radiographs was entered into a statistical shape model, producing a mean shape and a set of continuous variables (modes) representing variation in that shape. Nineteen modes, explaining 80% of shape variance, were simultaneously included in a logistic regression model with injury status as the dependent variable, adjusted for intra-person correlation, sex, race, body mass index (BMI), baseline OA radiographic grade, and baseline symptoms. RESULTS: A total of 194 participants (213 ankles) were included; mean age 71 years, BMI 30 kg/m(2), 67% white and 71% women. Injured ankles were more often symptomatic and from whites. In a model adjusted only for intra-person correlation, associations were seen between injury status and modes 1, 6, 13, and 19. In a fully adjusted model, race strongly affected the estimate for mode 1 (which was no longer statistically significant). CONCLUSIONS: This study showed variations in ankle shape and history of injury as well as with race. These novel findings may indicate a change in ankle morphology following injury, or that ankle morphology predisposes to injury, and suggest that ankle shape is a potentially important factor in the development of ankle OA.
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spelling pubmed-55305362017-08-02 Cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the Johnston County Osteoarthritis Project Nelson, Amanda E. Golightly, Yvonne M. Lateef, Shahmeer Renner, Jordan B. Jordan, Joanne M. Aspden, Richard M. Hillstrom, Howard Gregory, Jennifer S. J Foot Ankle Res Research BACKGROUND: Injury is an important risk factor for osteoarthritis (OA), a highly prevalent and disabling joint disease. Joint shape is linked to OA, but the interplay of injury and joint shape and their combined role in OA, particularly at the ankle, is not well known. Therefore, we explored cross-sectional associations between ankle shape and injury in a large community-based cohort. METHODS: Ankles without radiographic OA were selected from the current data collection of the Johnston County OA Project. Ankles with self-reported prior injury were included as injury cases (n = 108) along with 1:1 randomly selected non-injured ankles. To define ankle shape, a 68 point model on weight-bearing lateral ankle radiographs was entered into a statistical shape model, producing a mean shape and a set of continuous variables (modes) representing variation in that shape. Nineteen modes, explaining 80% of shape variance, were simultaneously included in a logistic regression model with injury status as the dependent variable, adjusted for intra-person correlation, sex, race, body mass index (BMI), baseline OA radiographic grade, and baseline symptoms. RESULTS: A total of 194 participants (213 ankles) were included; mean age 71 years, BMI 30 kg/m(2), 67% white and 71% women. Injured ankles were more often symptomatic and from whites. In a model adjusted only for intra-person correlation, associations were seen between injury status and modes 1, 6, 13, and 19. In a fully adjusted model, race strongly affected the estimate for mode 1 (which was no longer statistically significant). CONCLUSIONS: This study showed variations in ankle shape and history of injury as well as with race. These novel findings may indicate a change in ankle morphology following injury, or that ankle morphology predisposes to injury, and suggest that ankle shape is a potentially important factor in the development of ankle OA. BioMed Central 2017-07-26 /pmc/articles/PMC5530536/ /pubmed/28770007 http://dx.doi.org/10.1186/s13047-017-0216-3 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Nelson, Amanda E.
Golightly, Yvonne M.
Lateef, Shahmeer
Renner, Jordan B.
Jordan, Joanne M.
Aspden, Richard M.
Hillstrom, Howard
Gregory, Jennifer S.
Cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the Johnston County Osteoarthritis Project
title Cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the Johnston County Osteoarthritis Project
title_full Cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the Johnston County Osteoarthritis Project
title_fullStr Cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the Johnston County Osteoarthritis Project
title_full_unstemmed Cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the Johnston County Osteoarthritis Project
title_short Cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the Johnston County Osteoarthritis Project
title_sort cross-sectional associations between variations in ankle shape by statistical shape modeling, injury history, and race: the johnston county osteoarthritis project
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5530536/
https://www.ncbi.nlm.nih.gov/pubmed/28770007
http://dx.doi.org/10.1186/s13047-017-0216-3
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