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Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved

PURPOSE: Joint dynamics following Total Knee Arthroplasty (TKA) may influence patient-reported outcome. Simulations allow many knee alignment approaches to a single patient to be considered prior to surgery. The simulated kinematics can be matched to patient-reported outcome to predict kinematic pat...

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Autores principales: Twiggs, Joshua, Miles, Brad, Parker, David, Liu, David, Shimmin, Andrew, Fritsch, Brett, Roe, Justin, Baré, Jonathan, Solomon, Michael, Dickison, David, McMahon, Stephen, Boyle, Richard, Walter, Len
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9957835/
https://www.ncbi.nlm.nih.gov/pubmed/36446908
http://dx.doi.org/10.1007/s00167-022-07225-7
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author Twiggs, Joshua
Miles, Brad
Parker, David
Liu, David
Shimmin, Andrew
Fritsch, Brett
Roe, Justin
Baré, Jonathan
Solomon, Michael
Dickison, David
McMahon, Stephen
Boyle, Richard
Walter, Len
author_facet Twiggs, Joshua
Miles, Brad
Parker, David
Liu, David
Shimmin, Andrew
Fritsch, Brett
Roe, Justin
Baré, Jonathan
Solomon, Michael
Dickison, David
McMahon, Stephen
Boyle, Richard
Walter, Len
author_sort Twiggs, Joshua
collection PubMed
description PURPOSE: Joint dynamics following Total Knee Arthroplasty (TKA) may influence patient-reported outcome. Simulations allow many knee alignment approaches to a single patient to be considered prior to surgery. The simulated kinematics can be matched to patient-reported outcome to predict kinematic patterns most likely to give the best outcome. This study aims to validate one such previously developed algorithm based on a simulated deep knee bend (the Dynamic Knee Score, DKS). METHODS: 1074 TKA patients with pre- and post-operative Computerised Tomography (CT) scans and 12-month post-operative Knee Injury and Osteoarthritis Outcomes (KOOS) Scores were identified from the 360 Med Care Joint Registry. Landmarking and registration of implant position was performed on all CT scans, and each of the achieved TKAs was computationally simulated and received a predictive outcome score from the DKS. In addition, a set of potential alternative surgical plans which might have been followed were simulated. Comparison of patient-reported issues and DKS score was evaluated in a counter-factual study design. RESULTS: Patient-reported impairment with the knee catching and squatting was shown to be 30% lower (p = 0.005) and 22% lower (p = 0.026) in patients where the best possible DKS result was the one surgically achieved. Similar findings were found relating attainment of the best tibial slope and posterior femoral resection DKS plans to patient-reported difficulty straightening the knee (40% less likely, p < 0.001) and descending stairs (35% less likely, p = 0.006). CONCLUSION: The DKS has been shown to correlate with presence of patient-reported impairments post-TKA and the resultant algorithm can be applied in a pre-operative planning setting. Outcome optimization in the future may come from patient-specific selection of an alignment strategy and simulations may be a technological enabler of this trend. LEVEL OF EVIDENCE. III (Retrospective Cohort Study).
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spelling pubmed-99578352023-02-26 Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved Twiggs, Joshua Miles, Brad Parker, David Liu, David Shimmin, Andrew Fritsch, Brett Roe, Justin Baré, Jonathan Solomon, Michael Dickison, David McMahon, Stephen Boyle, Richard Walter, Len Knee Surg Sports Traumatol Arthrosc Knee PURPOSE: Joint dynamics following Total Knee Arthroplasty (TKA) may influence patient-reported outcome. Simulations allow many knee alignment approaches to a single patient to be considered prior to surgery. The simulated kinematics can be matched to patient-reported outcome to predict kinematic patterns most likely to give the best outcome. This study aims to validate one such previously developed algorithm based on a simulated deep knee bend (the Dynamic Knee Score, DKS). METHODS: 1074 TKA patients with pre- and post-operative Computerised Tomography (CT) scans and 12-month post-operative Knee Injury and Osteoarthritis Outcomes (KOOS) Scores were identified from the 360 Med Care Joint Registry. Landmarking and registration of implant position was performed on all CT scans, and each of the achieved TKAs was computationally simulated and received a predictive outcome score from the DKS. In addition, a set of potential alternative surgical plans which might have been followed were simulated. Comparison of patient-reported issues and DKS score was evaluated in a counter-factual study design. RESULTS: Patient-reported impairment with the knee catching and squatting was shown to be 30% lower (p = 0.005) and 22% lower (p = 0.026) in patients where the best possible DKS result was the one surgically achieved. Similar findings were found relating attainment of the best tibial slope and posterior femoral resection DKS plans to patient-reported difficulty straightening the knee (40% less likely, p < 0.001) and descending stairs (35% less likely, p = 0.006). CONCLUSION: The DKS has been shown to correlate with presence of patient-reported impairments post-TKA and the resultant algorithm can be applied in a pre-operative planning setting. Outcome optimization in the future may come from patient-specific selection of an alignment strategy and simulations may be a technological enabler of this trend. LEVEL OF EVIDENCE. III (Retrospective Cohort Study). Springer Berlin Heidelberg 2022-11-29 2023 /pmc/articles/PMC9957835/ /pubmed/36446908 http://dx.doi.org/10.1007/s00167-022-07225-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Knee
Twiggs, Joshua
Miles, Brad
Parker, David
Liu, David
Shimmin, Andrew
Fritsch, Brett
Roe, Justin
Baré, Jonathan
Solomon, Michael
Dickison, David
McMahon, Stephen
Boyle, Richard
Walter, Len
Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved
title Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved
title_full Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved
title_fullStr Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved
title_full_unstemmed Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved
title_short Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved
title_sort patient-reported impairment following tka is reduced when a computationally simulated predicted ideal alignment is achieved
topic Knee
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9957835/
https://www.ncbi.nlm.nih.gov/pubmed/36446908
http://dx.doi.org/10.1007/s00167-022-07225-7
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