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Predicting Amputation using Local Circulating Mononuclear Progenitor Cells in Angioplasty-treated Patients with Critical Limb Ischemia
Published on: September 22, 2020
Predictors of amputation in patients with diabetic foot ulcers: a multi-centre retrospective cohort study
Dehui Che1, Zhengwan Jiang1, Xinjian Xiang1
1The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Purpose:
Investigating risk factors for amputation in patients with diabetic foot ulcer (DFU) and developing a nomogram prediction model.
Methods:
We gathered case data of DFU patients from five medical institutions in Anhui Province, China. Following eligibility criteria, a retrospective case-control study was performed on data from 526 patients.
Results:
Among the 526 patients (mean age: 63.32 ± 12.14), 179 were female, and 347 were male; 264 underwent amputation. Univariate analysis identified several predictors for amputation, including Blood type-B, Ambulation, history of amputation (Hx. Of amputation), Bacterial culture-positive, Wagner grade, peripheral arterial disease (PAD), and laboratory parameters (HbA1c, Hb, CRP, ALB, FIB, PLT, Protein). In the multivariate regression, six variables emerged as independent predictors: Blood type-B (OR = 2.332, 95%CI [1.488-3.657], p < 0.001), Hx. Of amputation (2.298 [1.348-3.917], p = 0.002), Bacterial culture-positive (2.490 [1.618-3.830], p <0.001), Wagner 3 (1.787 [1.049-3.046], p = 0.033), Wagner 4-5 (4.272 [2.444-7.468], p <0.001), PAD (1.554 [1.030-2.345], p = 0.036). We developed a nomogram prediction model utilizing the aforementioned independent risk factors. The model demonstrated a favorable predictive ability for amputation risk, as evidenced by its area under the receiver operating characteristics (ROC) curve of 0.756 and the well-fitted corrected nomogram calibration curve.
Conclusion:
Our findings underscore Blood type-B, Hx. Of amputation, Bacterial culture-positive, Wagner 3-5, and PAD as independent risk factors for amputation in DFU patients. The resultant nomogram exhibits substantial accuracy in predicting amputation occurrence. Timely identification of these risk factors can reduce DFU-related amputation rates.
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