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Article Abstract
Background: Diabetic foot ulcer is one of the most prevalent, serious, and costly consequences of diabetes, often associated with peripheral neuropathy and peripheral arterial disease. These ulcers contribute to high disability and mortality rates in patients and pose a major challenge to clinical management.
Objective: To systematically review the risk prediction models for post-healing recurrence in diabetic foot ulcer (DFU) patients, so as to provide a reference for clinical staff to choose appropriate prediction models.
Methods: The authors searched five databases (Cochrane Library, PubMed, Web of Science, EMBASE, and Chinese Biomedical Database) from their inception to September 23, 2023, for relevant literature. After data extraction, the quality of the literature was evaluated using the Predictive Model Research Bias Risk and Suitability Assessment tool (PROBAST). Meta-analysis was performed using STATA 17.0 software.
Results: A total of 9 studies involving 5956 patients were included. The recurrence rate after DFU healing ranged from 6.2 % to 41.4 %. Nine studies established 15 risk prediction models, and the area under the curve (AUC) ranged from 0.660 to 0.940, of which 12 models had an AUC≥0.7, indicating good prediction performance. The combined AUC value of the 9 validation models was 0.83 (95 % confidence interval: 0.79-0.88). Hosmer-Lemeshow test was performed for 10 models, external validation for 5 models, and internal validation for 6 models. Meta-analysis showed that 14 predictors, such as age and living alone, could predict post-healing recurrence in DFU patients (p < 0.05).
Conclusion: To enhance the quality of these risk prediction models, there is potential for future improvements in terms of follow-up duration, model calibration, and validation processes.
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| http://dx.doi.org/10.1016/j.jtv.2024.07.002 | DOI Listing |
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Article Synopsis
- Diabetic foot ulcers (DFUs) are common complications of diabetes that lead to significant health risks and management challenges, associated with nerve and artery issues.
- The study systematically reviewed 9 studies with nearly 6,000 DFU patients to evaluate 15 risk prediction models for recurrence after healing, finding good predictive performance with area under the curve (AUC) values generally above 0.7.
- Key predictors for recurrence included factors like age and living alone, suggesting that improvements in follow-up duration and model validation could enhance these prediction models in the future.