Department of Clinical Epidemiology and Biostatistics, Pontificia Universidad Javeriana, Bogotá, Colombia; Department of Orthopaedics and Traumatology, Hospital Universitario de la Samaritana, Bogotá, Colombia.
Department of Clinical Epidemiology and Biostatistics, Pontificia Universidad Javeriana, Bogotá, Colombia.
Foot Ankle Surg. 2024 Aug;30(6):471-479. doi: 10.1016/j.fas.2024.03.007. Epub 2024 Mar 21.
The decision to perform amputation of a limb in a patient with diabetic foot ulcer (DFU) is not an easy task. Prediction models aim to help the surgeon in decision making scenarios. Currently there are no prediction model to determine lower limb amputation during the first 30 days of hospitalization for patients with DFU.
Classification And Regression Tree analysis was applied on data from a retrospective cohort of patients hospitalized for the management of diabetic foot ulcer, using an existing database from two Orthopaedics and Traumatology departments. The secondary analysis identified independent variables that can predict lower limb amputation (mayor or minor) during the first 30 days of hospitalization.
Of the 573 patients in the database, 290 feet underwent a lower limb amputation during the first 30 days of hospitalization. Six different models were developed using a loss matrix to evaluate the error of not detecting false negatives. The selected tree produced 13 terminal nodes and after the pruning process, only one division remained in the optimal tree (Sensitivity: 69%, Specificity: 75%, Area Under the Curve: 0.76, Complexity Parameter: 0.01, Error: 0.85). Among the studied variables, the Wagner classification with a cut-off grade of 3 exceeded others in its predicting capacity.
Wagner classification was the variable with the best capacity for predicting amputation within 30 days. Infectious state and vascular occlusion described indirectly by this classification reflects the importance of taking quick decisions in those patients with a higher compromise of these two conditions. Finally, an external validation of the model is still required.
III.
在糖尿病足溃疡（DFU）患者中决定截肢并非易事。预测模型旨在帮助外科医生做出决策。目前尚无预测模型可确定 DFU 患者住院前 30 天内是否需要进行下肢截肢。
对来自两个骨科和创伤科住院治疗糖尿病足溃疡患者的回顾性队列数据应用分类回归树分析，使用现有的数据库。二次分析确定了可预测住院前 30 天内下肢截肢（主要或次要）的独立变量。
在数据库中的 573 例患者中，290 例足部在住院前 30 天内进行了下肢截肢。使用损失矩阵开发了 6 种不同的模型来评估未检测到假阴性的错误。所选树生成了 13 个终端节点，在修剪过程之后，最优树中仅保留了一个分支（敏感性：69%，特异性：75%，曲线下面积：0.76，复杂度参数：0.01，误差：0.85）。在所研究的变量中，Wagner 分级在 3 级以上的分级在预测能力方面表现最佳。
Wagner 分级是预测 30 天内截肢的最佳变量。该分类法间接描述的感染状态和血管阻塞反映了在这些患者中需要迅速做出决策的重要性，因为他们的这两种情况更严重。最后，仍需要对模型进行外部验证。
III。
