Predicting reamputation risk in patients undergoing lower extremity amputation due to the complications of peripheral artery disease and/or diabetes
Predicting reamputation risk in patients undergoing lower extremity amputation due to the complications of peripheral artery disease and/or diabetes
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DOI：
10.1002/bjs.11160
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发表时间：
2019-07-01
影响因子：
9.6
通讯作者：
Norvell, D. C.
中科院分区：
文献类型：
--
作者：
Czerniecki, J. M.;Thompson, M. L.;Norvell, D. C.
背景：因周围动脉疾病和/或糖尿病并发症而接受截肢的患者面临治疗失败的风险，需要在更高的水平上进行截肢。本研究的目的是建立特定患者的截肢风险预测模型。方法：利用退伍军人健康管理数据库，对2004-2014年间因糖尿病和/或周围动脉疾病继发的单侧经足趾、经胫骨或经股骨截肢的患者进行识别，并在截肢后12个月存活。程序代码和自然语言处理用于定义相同或更高水平的后续同侧截肢。采用逐步Logistic回归建立预测模型。结果：共鉴定出5260例患者，其中1283例(24.4%)在初次截肢后12个月内接受了同侧截肢。粗大截肢风险分别为40%~3%、25%~9%和9%~7%。最终的预测模型包括11个预测因素(截肢程度、性别、吸烟、酒精、休息疼痛、门诊抗凝药物的使用、糖尿病、慢性阻塞性肺疾病、白细胞计数、肾功能衰竭和既往血运重建)，以及4个交互作用项。对预测特性的评估表明，通过拟合优度检验、良好的分辨率(AUC 0-72)和分辨率斜率(11-2%)可以很好地对模型进行校正。结论：建立了一个预测模型来计算每个截肢节段的个体初次愈合失败的风险和再截肢手术的需要。该模型可以辅助临床选择截肢节段的决策。
Background: Patients undergoing amputation of the lower extremity for the complications of peripheral artery disease and/or diabetes are at risk of treatment failure and the need for reamputation at a higher level. The aim of this study was to develop a patient-specific reamputation risk prediction model.Methods: Patients with incident unilateral transmetatarsal, transtibial or transfemoral amputation between 2004 and 2014 secondary to diabetes and/or peripheral artery disease, and who survived 12 months after amputation, were identified using Veterans Health Administration databases. Procedure codes and natural language processing were used to define subsequent ipsilateral reamputation at the same or higher level. Stepdown logistic regression was used to develop the prediction model. It was then evaluated for calibration and discrimination by evaluating the goodness of fit, area under the receiver operating characteristic curve (AUC) and discrimination slope.Results: Some 5260 patients were identified, of whom 1283 (24.4 per cent) underwent ipsilateral reamputation in the 12 months after initial amputation. Crude reamputation risks were 40-3, 25-9 and 9-7 per cent in the transmetatarsal, transtibial and transfemoral groups respectively. The final prediction model included 11 predictors (amputation level, sex, smoking, alcohol, rest pain, use of outpatient anticoagulants, diabetes, chronic obstructive pulmonary disease, white blood cell count, kidney failure and previous revascularization), along with four interaction terms. Evaluation of the prediction characteristics indicated good model calibration with goodness-of-fit testing, good discrimination (AUC 0-72) and a discrimination slope of 11-2 per cent.Conclusion: A prediction model was developed to calculate individual risk of primary healing failure and the need for reamputation surgery at each amputation level. This model may assist clinical decision-making regarding amputation-level selection.