Predicting risk of mortality and revision after dysvascular amputation

描述(由申请人提供)： 项目摘要/摘要：患有糖尿病和/或动脉周围血管疾病的退伍军人患者有极大的截肢风险。没有一种诊断性测试可以准确或可靠地预测哪个截肢节段会愈合，患者具体是什么， 死亡风险、再次截肢风险或活动结果将在每个重大截肢水平上进行。因此，决策通常是根据临床经验做出的。这导致了VHA中截肢的相对频率的极端差异，因为外科医生以不同的方式优先考虑风险和好处。横断面研究表明，截肢水平与活动能力、再次截肢和死亡率之间存在关系。如果在经股水平(Tf)进行截肢，死亡风险更大，活动能力降低的可能性更大，但发生一期愈合的可能性很大。相反，在经跖骨水平(TM)截肢与非常高的翻修率、低死亡率以及对于那些愈合的人来说，良好的活动效果有关。经胫骨截肢(TT)的结果介于这两个极端之间。这些一般性的和非特异性的结果很可能受到患者特定因素的强烈影响，但目前还没有证据来指导决定哪一个是最严重的。 适当的截肢水平，也不允许个别患者根据自己的优先顺序提供意见。这种不确定性给手术团队和患者都带来了挑战。文献表明，有必要开发预测模型，以便更好地为手术建议提供信息，同时允许考虑以患者为中心的优先事项。特定目标声明：我们将使用临床和管理VA数据库来开发和验证两个特定于患者的多变量预测模型。具体目标1：建立和验证患者特有的多变量预测模型，以预测意外事件中血管异常的经趾(TM)、经胫骨(TT)和经股(TF)截肢术后1年的死亡风险。具体目标2：建立和验证患者特有的多变量预测模型，该模型预测TM、TT和TF截肢事件后同侧再截肢(相同或更高截肢水平)1年的手术风险。这些预测模型的成功开发将补充目前由VA RR&D资助的活动结果预测模型的开发，它们将使外科医生能够更好地量化与在每个主要下肢截肢水平进行截肢相关的患者特定结果概率。将这些概率传达给患者，将使他们能够在平衡个人活动能力、死亡率和再次截肢的优先事项时，为决策提供输入。

DESCRIPTION (provided by applicant): Project Summary / Abstract: Veteran patients with Diabetes and/or Arterial Peripheral Vascular Disease are at significant risk for lower extremity amputation. There is no diagnostic test that can accurately or reliably predict which amputation level will heal, and what the patient specific, mortality risk, re-amputation risk or mobility outcome will be at each major amputation level. Decisions are therefore often made empirically based upon clinical experience. This has led to extreme variability in the relative frequencies of lower extremity amputation across VHA, as surgeons prioritize the risks and benefits in different ways. Cross sectional research has shown that there is a relationship between amputation level and the outcomes of mobility, re-amputation, and mortality. If an amputation is performed at the transfemoral level (TF) there is a greater risk of mortality, a greater likelihood of reduced mobility, but a very good probability tht primary healing will take place. In contrast an amputation at the transmetatarsal level (TM) is associated with very high revision rates, low mortality and for those that heal, a good mobility outcome. The outcome after transtibial (TT) amputation lies between these two extremes. These general and non-specific outcomes are likely strongly influenced by patient specific factors, but there is no evidence available at this time to guide decisions about which is the most appropriate amputation level, nor for the individual patient to provide input based upon their own priorities. This uncertainty leads to challenges for both the surgical team, and the patient. The literature indicates there is an important need for predictive models to be developed to better inform surgical recommendations and at the same time allow for patient centric priorities to be considered. Specific Aims Statement: We will use both clinical and administrative VA databases to develop and validate two patient-specific multivariable prediction models. Specific Aim 1: To develop and validate a patient-specific multivariable prediction model for 1-year mortality risk after incident dysvascular transmetatarsal (TM), transtibial (TT), and transfemoral (TF) amputation. Specific Aim 2: To develop and validate a patient-specific multivariable prediction model that predicts 1-year ipsilateral re-amputation (same or higher amputation level) surgery risk after incident TM, TT, and TF amputation. The successful development of these predictive models will complement a mobility outcome prediction model whose development is currently funded by VA RR&D. Together they will enable surgeons to better quantify patient specific outcome probabilities associated with performing an amputation at each major lower extremity amputation level. Communication of these probabilities to the patient will enable them to provide input to the decision as they balance their personal priorities of mobility, mortality and re-amputation.