Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal

Zixing Bai1 *, Xuhan Cao1 *, Yanjun Yang,1 Xudong Sun,1 Yongli Dong,2 Jianmin Wen,1 Weidong Sun1 1Second Department of Orthopedics, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China; 2Scientific Research Department, Wangjing Hospital...

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Main Authors: Bai Z, Cao X, Yang Y, Sun X, Dong Y, Wen J, Sun W
Format: Article
Language:English
Published: Dove Medical Press 2022-11-01
Series:Journal of Pain Research
Subjects:
Online Access:https://www.dovepress.com/establishment-and-validation-of-a-predictive-nomogram-for-hallux-valgu-peer-reviewed-fulltext-article-JPR
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author Bai Z
Cao X
Yang Y
Sun X
Dong Y
Wen J
Sun W
author_facet Bai Z
Cao X
Yang Y
Sun X
Dong Y
Wen J
Sun W
author_sort Bai Z
collection DOAJ
description Zixing Bai1 &ast;, Xuhan Cao1 &ast;, Yanjun Yang,1 Xudong Sun,1 Yongli Dong,2 Jianmin Wen,1 Weidong Sun1 1Second Department of Orthopedics, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China; 2Scientific Research Department, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Weidong Sun, Wangjing Hospital of China Academy of Chinese Medical Sciences, No. 6 Central South Road, Wangjing, Chaoyang District, Beijing, 100102, People’s Republic of China, Tel +86-84739140, Email sunweidong8239@aliyun.comObjective: To investigate the risk factors for hallux valgus complicated with pain under the second metatarsal and construct an effective model and method for predicting hallux valgus complicated with pain under the second metatarsal based on risk factors.Methods: A total of 545 patients with hallux valgus who were admitted to our hospital were divided randomly into a training set and a validation set. The demographic characteristics, imaging indices and gait test indices of the patients were collected. The risk factors were identified by univariate and multivariate logistic regression analyses. A risk prediction model for hallux valgus with pain under the second metatarsal was established, and the area under the curve (AUC) of the receiver operating characteristic and a decision curve analysis were used for verification and identification. The value of the model was tested in the verification group.Results: Second metatarsal length, second metatarsal peak pressure, hallux valgus angle (HVA), intermetatarsal angle 1– 2 (IMA1– 2) and weight were the risk factors for hallux valgus complicated with pain under the second metatarsal. Based on the weighting of these seven risk factors, a prediction model was established. The AUC of the prediction model was 0.84 (95% confidence interval [CI]: 0.802~0.898, P < 0.05), and the results of a Hosmer–Lemeshow test showed a good degree of calibration (χ2 = 10.62, P > 0.05). The internal validation of the AUC was 0.83 (95% CI: 0.737– 0.885, P < 0.05). The model had obvious net benefits when the threshold probability was 10%– 70%.Conclusion: Second metatarsal length, second metatarsal peak pressure, HVA, IMA1– 2 and weight were the risk factors for hallux valgus combined with second metatarsal pain. The risk prediction model for hallux valgus complicated with pain under the second metatarsal based on these seven variables was proven effective.Level of Evidence: Level III, retrospective comparative study.Keywords: hallux valgus, metatarsalgia, nomogram, predictive model, risk factors
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spelling doaj.art-7129b7089b5b4ccda36354c8fc58e0af2022-12-22T03:36:33ZengDove Medical PressJournal of Pain Research1178-70902022-11-01Volume 153523353679490Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second MetatarsalBai ZCao XYang YSun XDong YWen JSun WZixing Bai1 &ast;, Xuhan Cao1 &ast;, Yanjun Yang,1 Xudong Sun,1 Yongli Dong,2 Jianmin Wen,1 Weidong Sun1 1Second Department of Orthopedics, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China; 2Scientific Research Department, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Weidong Sun, Wangjing Hospital of China Academy of Chinese Medical Sciences, No. 6 Central South Road, Wangjing, Chaoyang District, Beijing, 100102, People’s Republic of China, Tel +86-84739140, Email sunweidong8239@aliyun.comObjective: To investigate the risk factors for hallux valgus complicated with pain under the second metatarsal and construct an effective model and method for predicting hallux valgus complicated with pain under the second metatarsal based on risk factors.Methods: A total of 545 patients with hallux valgus who were admitted to our hospital were divided randomly into a training set and a validation set. The demographic characteristics, imaging indices and gait test indices of the patients were collected. The risk factors were identified by univariate and multivariate logistic regression analyses. A risk prediction model for hallux valgus with pain under the second metatarsal was established, and the area under the curve (AUC) of the receiver operating characteristic and a decision curve analysis were used for verification and identification. The value of the model was tested in the verification group.Results: Second metatarsal length, second metatarsal peak pressure, hallux valgus angle (HVA), intermetatarsal angle 1– 2 (IMA1– 2) and weight were the risk factors for hallux valgus complicated with pain under the second metatarsal. Based on the weighting of these seven risk factors, a prediction model was established. The AUC of the prediction model was 0.84 (95% confidence interval [CI]: 0.802~0.898, P < 0.05), and the results of a Hosmer–Lemeshow test showed a good degree of calibration (χ2 = 10.62, P > 0.05). The internal validation of the AUC was 0.83 (95% CI: 0.737– 0.885, P < 0.05). The model had obvious net benefits when the threshold probability was 10%– 70%.Conclusion: Second metatarsal length, second metatarsal peak pressure, HVA, IMA1– 2 and weight were the risk factors for hallux valgus combined with second metatarsal pain. The risk prediction model for hallux valgus complicated with pain under the second metatarsal based on these seven variables was proven effective.Level of Evidence: Level III, retrospective comparative study.Keywords: hallux valgus, metatarsalgia, nomogram, predictive model, risk factorshttps://www.dovepress.com/establishment-and-validation-of-a-predictive-nomogram-for-hallux-valgu-peer-reviewed-fulltext-article-JPRhallux valgusmetatarsalgianomogrampredictive modelrisk factors
spellingShingle Bai Z
Cao X
Yang Y
Sun X
Dong Y
Wen J
Sun W
Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal
Journal of Pain Research
hallux valgus
metatarsalgia
nomogram
predictive model
risk factors
title Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal
title_full Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal
title_fullStr Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal
title_full_unstemmed Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal
title_short Establishment and Validation of a Predictive Nomogram for Hallux Valgus with Pain Under the Second Metatarsal
title_sort establishment and validation of a predictive nomogram for hallux valgus with pain under the second metatarsal
topic hallux valgus
metatarsalgia
nomogram
predictive model
risk factors
url https://www.dovepress.com/establishment-and-validation-of-a-predictive-nomogram-for-hallux-valgu-peer-reviewed-fulltext-article-JPR
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