Diabetes Metab Res Rev. 2023 Jan 19:e3616. doi: 10.1002/dmrr.3616. Online ahead of print.
ABSTRACT
AIMS: To develop and validate a risk prediction model for Chinese patients with type 2 diabetes with the recurrence of diabetes foot ulcers (DFU) based on systematic review and meta-analysis.
METHODS: A prospective analysis was performed with 1333 participants and followed up for 60 months. Three models were analyzed using derived cohort. The risk factors were screened by meta-analysis and logistic regression, and the missing variables were interpolated by multiple imputation. The internal validation was performed by the bootstrap procedure, validation cohort was applied to the external validation. The performance of model was evaluated the area under the discrimination receiver Operating Characteristic Curve (ROC). The calibration and discrimination methods were used for the validation cohort. The variables were selected according to their clinical and statistical importance to construct the nomograms.
RESULTS: Three models were developed and validated. Model 1 included seven social and clinical indicators like Sex, DM duration, Previous DFU, Location of ulcer, Smoker, History of amputation and Foot deformity. Model 2 included four more indicators besides those in Model 1, which were Statin agents used, Antiplatelet agents used, SBP and BMI. Model 3 added further laboratory indicators to Model 2 such as LDL-C, HbA1C, FIB and BUN. In the derivation cohort, 20.1% (206/1027) participants with DFU were recurred as compared to the validation cohort, which was 38.2% (117/306). The AUC in the derivation cohort for Models1-3 were 0.781 (0.744-0.817), 0.843 (0.813-0.873) and 0.899 (0.876-0.922) respectively. The Youden index for Model 1-3 were 0.430, 0.559 and 0.653 respectively. Model 3 showed the highest sensitivity and specificity. All models performed well for both discrimination and calibration.
CONCLUSION: Model 1-2 were non-invasive, which indicated their role in general screening for patients at the high-risk of recurrence DFU. However, Model 3 offered a more specific screening due to its best performance in predicting the risk of DFU recurrence amongst three models. This article is protected by copyright. All rights reserved.
PMID:36657181 | DOI:10.1002/dmrr.3616
