| 白子兴,石雷,龚龙,等.（足母）外翻合并第2跖骨头下疼痛预测模型的构建及有效性验证.骨科,2025,16(1): 32-39. |
| （足母）外翻合并第2跖骨头下疼痛预测模型的构建及有效性验证 |
| Establishment and validation of a predictive Nomogram for hallux valgus with pain under the second metatarsal |
| 投稿时间：2024-09-22 |
| DOI：10.3969/j.issn.1674-8573.2025.01.006 |
| 中文关键词: （足母）外翻 跖痛症 预后模型 危险因素 |
| 英文关键词: Hallux valgus Metatarsalgia Predictive model Risk factors |
| 基金项目:北京市属医院科研培育计划项目（PZ2023024）；中国中医科学院望京医院中医药临床循证研究专项（WJ-KY-XY-2023-18）；北京中医医院顺义医院院级课题（SYYJLC-202401） |
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| 中文摘要: |
| 目的 探讨（足母）外翻合并第2跖骨头下疼痛的危险因素，构建预测模型并完成验证。方法 选择2019年6月至2021年6月在中国中医科学院望京医院接受治疗的（足母）外翻病人进行回顾性分析，共纳入545例，随机拆分为训练集（70%）和验证集（30%）。采集病人的社会人口指标、体征、影像指标以及步态测试指标，采用单因素分析和多因素Logistic回归分析（足母）外翻并发第2跖骨头下疼痛危险因素，根据各危险因素的加权赋分建立（足母）外翻并发第2跖骨头下疼痛风险预测模型，通过受试者工作特征曲线（ROC）计算曲线下面积（AUC）及Hosmer-Lemeshow检验检测模型的区分度和校准度，并在验证集中检验该模型的价值。结果 545例病人中157例合并第2跖骨头下疼痛。多因素Logistic回归分析显示第2跖骨长度[OR=1.078，95% CI（1.105，1.105），P＜0.001]、第2跖骨头下峰压强[OR=1.607，95% CI（1.342，1.925），P＜0.001]、（足母）外翻角（HVA）[OR=1.068，95% CI（1.028，1.109），P＜0.001]、第1、2跖骨间角（IMA1-2）[OR=1.222，95% CI（1.044，1.430），P=0.013]及体重[OR=1.014，95% CI（1.013，1.108），P=0.039]是（足母）外翻病人合并第2跖骨头下疼痛的独立危险因素。而第1跖骨头下触地面积[OR=0.806，95% CI（0.726，0.895），P=0.052]和身体质量指数[OR=0.925，95% CI（0.832，1.029），P=0.150]是其保护因素。基于多因素Logistic回归分析得出的变量因素建立预测模型。本研究预测模型的AUC为0.844[95% CI（0.802，0.898），P=0.015]；Hosmer-Lemeshow检验（χ2=10.620，P=0.253），内部验证AUC为0.828[95% CI（0.737，0.885），P=0.011]，Hosmer-Lemeshow检验（χ2=11.570，P=0.282），提示该模型对（足母）外翻并发第2跖骨头下疼痛具有较好预测能力。结论 第2跖骨长度、第2跖骨头下峰压强、HVA、IMA1-2及体重是（足母）外翻合并第2跖骨头下疼痛的危险因素，而第1跖骨头下触地面积、身体质量指数是其保护因素，基于这些变量建立风险预测模型有望用于术前风险预测，对高危人群进行干预治疗。 |
| 英文摘要: |
| Objective To explore the risk factors for hallux valgus combined with pain beneath the second metatarsal head, construct a predictive model, and complete validation. Methods A retrospective analysis was conducted on 545 patients with hallux valgus who received treatment at Wangjing Hospital, Chinese Academy of Traditional Chinese Medicine from June 2019 to June 2021. The patients were randomly divided into a training set (70%) and a validation set (30%). The social demographic indicators, physical signs, imaging indicators, and gait test indicators of patients were collected. Single factor analysis and multiple Logistic regression were used to analyze the risk factors for hallux valgus complicated with second metatarsal head pain. Based on the weighted scores of each risk factor, a risk prediction model for hallux valgus complicated with second metatarsal head pain was established. The area under the curve (AUC) was calculated by the receiver operating characteristic (ROC) curve of the subjects, and the discrimination and calibration of the model were tested by Hosmer-Lemeshow test. The value of the model was tested in the validation set. Results Out of 545 patients, 157 were found to have pain beneath the second metatarsal head. Multivariate Logistic regression analysis showed that the length of the second metatarsal bone [OR=1.078, 95% CI (1.105, 1.105), P＜0.001], the peak pressure under the second metatarsal head [OR=1.607, 95% CI (1.342, 1.925), P＜0.001], the hallux valgus angle (HVA) [OR=1.068, 95% CI (1.028, 1.109), P=0.001], the angle between the first and second metatarsals (IMA1-2) [OR=1.222, 95% CI (1.044, 1.430), P=0.013], and weight [OR=1.014, 95% CI (1.013, 1.108), P=0.039] were independent risk factors for the occurrence of pain under the second metatarsal head in patients with hallux valgus. And the first metatarsal head contact area [OR=0.806, 95% CI (0.726, 0.895), P=0.052] and body mass index [OR=0.925, 95% CI (0.832, 1.029), P=0.150] were its protective factors. A predictive model was established based on 7 variable factors obtained from multiple Logistic regression analysis. The AUC of the prediction model in this study was 0.844 [95% CI (0.802, 0.898), P=0.015], Hosmer-Lemeshow test (χ2=10.620, P=0.253), internal validation AUC was 0.828 [95% CI (0.737, 0.885), P=0.011], Hosmer-Lemeshow test (χ2=11.570, P=0.282), indicating that the model had good predictive ability for pain under the second metatarsal head caused by hallux valgus. Conclusion The length of the second metatarsal bone, the peak pressure below the second metatarsal head, HVA, IMA1-2, and body weight are risk factors for hallux valgus combined with pain below the second metatarsal head, while the contact area below the first metatarsal head and body mass index are protective factors. A risk prediction model based on these 7 variables is expected to be used for preoperative risk prediction and intervention therapy for high-risk populations. |
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