Construction and validation of a risk prediction model for the delayed healing of venous leg ulcers
10.3761/j.issn.0254-1769.2024.13.010
- VernacularTitle:下肢静脉溃疡延迟愈合风险预测模型的构建与验证
- Author:
Siyuan HUANG
1
;
Xinjun LIU
;
Xi YANG
;
Mingfeng ZHANG
;
Dan WANG
;
Huarong XIONG
;
Zuoyi YAO
;
Meihong SHI
Author Information
1. 646000 泸州市 西南医科大学护理学院
- Keywords:
Venous Leg Ulcers;
Delayed Healing;
Risk Factors;
Prediction Model;
Nursing Care
- From:
Chinese Journal of Nursing
2024;59(13):1600-1607
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct and validate a risk prediction model for delayed healing of venous leg ulcer(VLU),so as to provide a reference basis for early identification of people at high risk of delayed healing.Methods Using a convenience sampling method,331 VLU patients attending vascular surgery departments in 2 tertiary A hospitals in Sichuan Province from January 2018 to December 2022 were selected as a modeling group and an internal validation group,and 112 patients admitted to another tertiary A hospital were selected as an external validation group.Risk factors for delayed healing in VLU patients were screened using univariate analysis,LASSO regression,and multivariate logistic regression analysis,and a risk prediction model was constructed using R software,and the predictive effects of the models were examined using the area under the receiver operating characteristic curve,the Hosmer-Lemeshow test,decision curve,and the bootstrap resampling for internal validation and spatial external validation were performed,respectively.Results The predictors that ultimately entered the prediction model were diabetes(OR=4.752),deep vein thrombosis(OR=4.104),lipodermatosclerosis(OR=5.405),ulcer recurrence(OR=3.239),and ankle mobility(OR=5.520).The model had good discrimination(AUC:0.819 for internal validation and 0.858 for external validation),calibration(Hosmer-Lemeshow test:χ2=13.517,P=0.095 for internal validation and χ2=3.375,P=0.909 for external validation)and clinical validity.Conclusion The model constructed in this study has good differentiation and calibration,and it can effectively predict people at high risk of delayed healing of VLU,which facilitates targeted clinical interventions to improve ulcer outcomes and reduce the risk of delayed ulcer healing.
