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Factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model

BACKGROUND: Identifying risk factors and early intervention are critical for improving the satisfaction rate of total knee arthroplasty (TKA). Our study aimed to identify patient-specific variables and establish a nomogram model to predict dissatisfaction at 1 year after TKA. METHODS: This prospecti...

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Autores principales: Muertizha, Mieralimu, Cai, XinTian, Ji, Baochao, Aimaiti, Abudousaimi, Cao, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330701/
https://www.ncbi.nlm.nih.gov/pubmed/35902950
http://dx.doi.org/10.1186/s13018-022-03205-2
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author Muertizha, Mieralimu
Cai, XinTian
Ji, Baochao
Aimaiti, Abudousaimi
Cao, Li
author_facet Muertizha, Mieralimu
Cai, XinTian
Ji, Baochao
Aimaiti, Abudousaimi
Cao, Li
author_sort Muertizha, Mieralimu
collection PubMed
description BACKGROUND: Identifying risk factors and early intervention are critical for improving the satisfaction rate of total knee arthroplasty (TKA). Our study aimed to identify patient-specific variables and establish a nomogram model to predict dissatisfaction at 1 year after TKA. METHODS: This prospective cohort study involved 208 consecutive primary TKA patients with end-stage arthritis who completed self-reported measures preoperatively and at 1 year postoperatively. All participants were randomized into a training cohort (n = 154) and validation cohort (n = 54). Multiple regression models with preoperative and postoperative factors were used to establish the nomogram model for dissatisfaction at 1 year postoperatively. The least absolute shrinkage and selection operator method was used to screen the suitable and effective risk factors (demographic variables, preoperative variables, surgical variable, and postoperative variables) collected. These variables were compared between the satisfied and dissatisfied groups in the training cohort. The receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis were used to validate the discrimination, calibration, and clinical usefulness of the model. Results were evaluated by internal validation of the validation cohort. RESULTS: The overall satisfaction rate 1 year after TKA was 77.8%. The nomogram prediction model included the following risk factors: gender; primary diagnosis; postoperative residual pain; poor postoperative range of motion; wound healing; and the rate of change in the degree of coronal lower limb alignment (hip–knee–ankle angle, HKA).The ROC curves of the training and validation cohorts were 0.9206 (95% confidence interval [CI], 0.8785–0.9627) and 0.9662 (0.9231, 1.0000) (95% CI, 0.9231, 1.0000), respectively. The Hosmer–Lemeshow test showed good calibration of the nomogram (training cohort, p = 0.218; validation cohort, p = 0.103). CONCLUSION: This study developed a prediction nomogram model based on partially modifiable risk factors for predicting dissatisfaction 1 year after TKA. This model demonstrated good discriminative capacity for identifying those at greatest risk for dissatisfaction and may help surgeons and patients identify and evaluate the risk factors for dissatisfaction and optimize TKA outcomes.
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spelling pubmed-93307012022-07-29 Factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model Muertizha, Mieralimu Cai, XinTian Ji, Baochao Aimaiti, Abudousaimi Cao, Li J Orthop Surg Res Research Article BACKGROUND: Identifying risk factors and early intervention are critical for improving the satisfaction rate of total knee arthroplasty (TKA). Our study aimed to identify patient-specific variables and establish a nomogram model to predict dissatisfaction at 1 year after TKA. METHODS: This prospective cohort study involved 208 consecutive primary TKA patients with end-stage arthritis who completed self-reported measures preoperatively and at 1 year postoperatively. All participants were randomized into a training cohort (n = 154) and validation cohort (n = 54). Multiple regression models with preoperative and postoperative factors were used to establish the nomogram model for dissatisfaction at 1 year postoperatively. The least absolute shrinkage and selection operator method was used to screen the suitable and effective risk factors (demographic variables, preoperative variables, surgical variable, and postoperative variables) collected. These variables were compared between the satisfied and dissatisfied groups in the training cohort. The receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis were used to validate the discrimination, calibration, and clinical usefulness of the model. Results were evaluated by internal validation of the validation cohort. RESULTS: The overall satisfaction rate 1 year after TKA was 77.8%. The nomogram prediction model included the following risk factors: gender; primary diagnosis; postoperative residual pain; poor postoperative range of motion; wound healing; and the rate of change in the degree of coronal lower limb alignment (hip–knee–ankle angle, HKA).The ROC curves of the training and validation cohorts were 0.9206 (95% confidence interval [CI], 0.8785–0.9627) and 0.9662 (0.9231, 1.0000) (95% CI, 0.9231, 1.0000), respectively. The Hosmer–Lemeshow test showed good calibration of the nomogram (training cohort, p = 0.218; validation cohort, p = 0.103). CONCLUSION: This study developed a prediction nomogram model based on partially modifiable risk factors for predicting dissatisfaction 1 year after TKA. This model demonstrated good discriminative capacity for identifying those at greatest risk for dissatisfaction and may help surgeons and patients identify and evaluate the risk factors for dissatisfaction and optimize TKA outcomes. BioMed Central 2022-07-28 /pmc/articles/PMC9330701/ /pubmed/35902950 http://dx.doi.org/10.1186/s13018-022-03205-2 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Muertizha, Mieralimu
Cai, XinTian
Ji, Baochao
Aimaiti, Abudousaimi
Cao, Li
Factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model
title Factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model
title_full Factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model
title_fullStr Factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model
title_full_unstemmed Factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model
title_short Factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model
title_sort factors contributing to 1-year dissatisfaction after total knee arthroplasty: a nomogram prediction model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330701/
https://www.ncbi.nlm.nih.gov/pubmed/35902950
http://dx.doi.org/10.1186/s13018-022-03205-2
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