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陆军军医大学(第三军医大学)第一附属医院皮肤科,重庆
尹锐,E-mail:swyinrui@tmmu.edu.cn
收稿日期:2025-06-17,
修回日期:2025-08-09,
录用日期:2025-08-15,
纸质出版日期:2025-09-30
移动端阅览
韩炜东,范一鸣,陈盼,等.基于系统评价和Meta分析的糖尿病足溃疡患者截肢风险预测模型的开发和验证[J].陆军军医大学学报,2025,47(18):2262-2271.DOI:10.16016/j.2097-0927.202506048.
HAN WEIDONG,FAN YIMING,CHEN PAN,et al.Development and validation of a prediction model for amputation risk in patients with diabetic foot ulcers based on systematic review and meta-analysis[J].J Army Med Univ,2025,47(18):2262-2271.DOI:10.16016/j.2097-0927.202506048.
韩炜东,范一鸣,陈盼,等.基于系统评价和Meta分析的糖尿病足溃疡患者截肢风险预测模型的开发和验证[J].陆军军医大学学报,2025,47(18):2262-2271.DOI:10.16016/j.2097-0927.202506048. DOI:
HAN WEIDONG,FAN YIMING,CHEN PAN,et al.Development and validation of a prediction model for amputation risk in patients with diabetic foot ulcers based on systematic review and meta-analysis[J].J Army Med Univ,2025,47(18):2262-2271.DOI:10.16016/j.2097-0927.202506048. DOI:
目的
2
基于系统评价和Meta分析开发并验证一种预测糖尿病足溃疡(diabetic foot ulcers,DFU)患者截肢风险的模型。
方法
2
采用主题词+自由词的检索方式,检索关于研究DFU患者截肢风险因素的文献。经筛选最终纳入37项队列研究,采用纽卡斯尔-渥太华量表(Newcastle-Ottawa Scale,NOS)进行质量评价。对DFU的截肢风险因素进行Meta分析。DFU截肢风险预测模型纳入Meta分析中具有统计学意义的风险因素,根据各风险因素合并的比值比(odds ratio, OR)计算其相应
β
系数并进行评分赋值,建立评分制模型。收集2021年至2023年于陆军军医大学第一附属医院内分泌科住院的453例DFU患者的临床数据作为验证队列,对模型进行验证。模型性能评估基于受试者工作特征曲线下面积(area under the curve of receiver operating characteristic,AUC),通过灵敏度和特异性计算最大约登指数来确定最佳界值分数。
结果
2
Meta分析显示在11 779例DFU患者中,累积截肢率约34.65%。最终的风险预测模型纳入5个风险因素,包括坏疽[
OR
=11.92(5.86~24.24)]、溃疡深度[
OR
=4.93(2.52~9.64)]、骨髓炎[
OR
=3.19(2.36~4.29)]、既往截肢史[
OR
=3.19(2.00~5.09)]和下肢动脉疾病[
OR
=3.10(2.31~4.17)]。根据各风险因素的权重,模型总分为76分,最佳界值分数为36.5分。预测模型性能良好,
AUC
=0.864(0.824~0.903),灵敏度为
0.743,特异性为0.859,准确率为83.00%。
结论
2
本研究开发了一种基于风险因素评分的DFU截肢风险预测模型,模型具有良好的区分度和校准度,为DFU截肢相关的临床研究和临床决策提供有效的科学依据。
Objective
2
To develop and validate a prediction model for risk of amputation in patients with diabetic foot ulcers (DFU) based on systematic review and meta-analysis.
Methods
2
The studies on the risk factors of amputation in DFU patients was retrieved by using subject words+free words. After screening
37 cohort studies were finally included
and the Newcastle-Ottawa scale (NOS) was used for quality evaluation. Meta-analysis was performed on the risk factors of amputation in DFU. Then a prediction model for DFU amputation risk were constructed based on the statistically significant risk factors in the meta-analysis. The corresponding
β
value was calculated based on the combined odds ratio (OR) value of each risk factor
and each risk factor was scored to establish a scoring system model. The clinical data of 453 DFU patients hospitalized in our department from 2021 to 2023 were collected as a validation cohort. Receiver operating characteristic (ROC) curve analysis was used to evaluate the model performance. The area under the curve (AUC) was calculated
and the optimal cutoff score was determined by calculation of the maximum Youden index through sensitivity and specificity.
Results
2
Our meta-analysis showed a cumulative amputation rate of approximately 34.65% in 11 779 DFU patients. The final risk prediction models include gangrene [
OR
=11.92 (5.86~24.24)
]
ulcer depth [
OR
=4.93 (2.52~9.64)
]
osteomyelitis [
OR
=3.19 (2.36~4.29)
]
previous amputation history [
OR
=3.19 (2.00~5.09)
]
and lower extremity arterial disease [
OR
=3.10 (2.31~4.17)
]
. According to the weights of each risk factor
the total score of the model is 76
and the
optimal cut-off score is 36.5. The prediction model performed well
with an AUC value of 0.864 (0.824
0.903)
a sensitivity of 0.743
a specificity of 0.859
and an accuracy rate of 83.00%.
Conclusion
2
A prediction model for DFU amputation risk is developed based on risk factor scoring
and has good discrimination and calibration
providing effective scientific basis for clinical research and clinical decision-making related to DFU amputation.
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