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Radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation

Background and purpose — Compressive osseointegration fixation is an alternative to intramedullary fixation for endoprosthetic reconstruction. Mechanical failure of compressive osseointegration presents differently on radiographs than stemmed implants, therefore we aimed to develop a reliable radiog...

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Autores principales: Kagan, Ryland, Parlee, Lindsay, Beckett, Brooke, Hayden, James B, Gundle, Kenneth R, Doung, Yee-Cheen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144214/
https://www.ncbi.nlm.nih.gov/pubmed/31960731
http://dx.doi.org/10.1080/17453674.2020.1716295
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author Kagan, Ryland
Parlee, Lindsay
Beckett, Brooke
Hayden, James B
Gundle, Kenneth R
Doung, Yee-Cheen
author_facet Kagan, Ryland
Parlee, Lindsay
Beckett, Brooke
Hayden, James B
Gundle, Kenneth R
Doung, Yee-Cheen
author_sort Kagan, Ryland
collection PubMed
description Background and purpose — Compressive osseointegration fixation is an alternative to intramedullary fixation for endoprosthetic reconstruction. Mechanical failure of compressive osseointegration presents differently on radiographs than stemmed implants, therefore we aimed to develop a reliable radiographic method to determine stable integration. Patients and methods — 8 reviewers evaluated 11 radiographic parameters from 29 patients twice, 2 months apart. Interclass correlation coefficients (ICCs) were used to assess test–retest and inter-rater reliability. We constructed a fast and frugal decision tree using radiographic parameters with substantial test–retest agreement, and then tested using radiographs from a new cohort of 49 patients. The model’s predictions were compared with clinical outcomes and a confusion matrix was generated. Results — 6 of 8 reviewers had non-significant intra-rater ICCs for ≥ one parameter; all inter-rater ICCs were highly reliable (p < 0.001). Change in length between the top of the spindle sleeve and bottom of the anchor plug (ICC 0.98), bone cortex hypertrophy (ICC 0.86), and bone pin hypertrophy (ICC 0.81) were used to create the decision tree. The sensitivity and specificity of the training cohort were 100% (95% CI 52–100) and 87% (CI 74–94) respectively. The decision tree demonstrated 100% (CI 40–100) sensitivity and 89% (CI 75–96) specificity with the test cohort. Interpretation — A stable spindle length and at least 3 cortices with bone hypertrophy at the implant interface predicts stable osseointegration; failure is predicted in the absence of bone hypertrophy at the implant interface if the pin sites show hypertrophy. Thus, our decision tree can guide clinicians as they follow patients with compressive osseo­integration implants.
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spelling pubmed-71442142020-04-13 Radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation Kagan, Ryland Parlee, Lindsay Beckett, Brooke Hayden, James B Gundle, Kenneth R Doung, Yee-Cheen Acta Orthop Articles Background and purpose — Compressive osseointegration fixation is an alternative to intramedullary fixation for endoprosthetic reconstruction. Mechanical failure of compressive osseointegration presents differently on radiographs than stemmed implants, therefore we aimed to develop a reliable radiographic method to determine stable integration. Patients and methods — 8 reviewers evaluated 11 radiographic parameters from 29 patients twice, 2 months apart. Interclass correlation coefficients (ICCs) were used to assess test–retest and inter-rater reliability. We constructed a fast and frugal decision tree using radiographic parameters with substantial test–retest agreement, and then tested using radiographs from a new cohort of 49 patients. The model’s predictions were compared with clinical outcomes and a confusion matrix was generated. Results — 6 of 8 reviewers had non-significant intra-rater ICCs for ≥ one parameter; all inter-rater ICCs were highly reliable (p < 0.001). Change in length between the top of the spindle sleeve and bottom of the anchor plug (ICC 0.98), bone cortex hypertrophy (ICC 0.86), and bone pin hypertrophy (ICC 0.81) were used to create the decision tree. The sensitivity and specificity of the training cohort were 100% (95% CI 52–100) and 87% (CI 74–94) respectively. The decision tree demonstrated 100% (CI 40–100) sensitivity and 89% (CI 75–96) specificity with the test cohort. Interpretation — A stable spindle length and at least 3 cortices with bone hypertrophy at the implant interface predicts stable osseointegration; failure is predicted in the absence of bone hypertrophy at the implant interface if the pin sites show hypertrophy. Thus, our decision tree can guide clinicians as they follow patients with compressive osseo­integration implants. Taylor & Francis 2020-01-21 /pmc/articles/PMC7144214/ /pubmed/31960731 http://dx.doi.org/10.1080/17453674.2020.1716295 Text en © 2020 The Author(s). Published by Taylor & Francis on behalf of the Nordic Orthopedic Federation https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Kagan, Ryland
Parlee, Lindsay
Beckett, Brooke
Hayden, James B
Gundle, Kenneth R
Doung, Yee-Cheen
Radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation
title Radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation
title_full Radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation
title_fullStr Radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation
title_full_unstemmed Radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation
title_short Radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation
title_sort radiographic parameter-driven decision tree reliably predicts aseptic mechanical failure of compressive osseointegration fixation
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144214/
https://www.ncbi.nlm.nih.gov/pubmed/31960731
http://dx.doi.org/10.1080/17453674.2020.1716295
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