Brownrigg Jack R W, de Lusignan Simon, McGovern Andrew, Hughes Cian, Thompson Matthew M, Ray Kausik K, Hinchliffe Robert J
St George's Vascular Institute, Division of Cardiovascular Sciences, St Georges University of London, UK.
Department of Health Care Management and Policy, University of Surrey, Guildford, UK.
Heart. 2014 Dec;100(23):1837-43. doi: 10.1136/heartjnl-2014-305657. Epub 2014 Aug 5.
Identifying individuals with diabetes at high risk of cardiovascular disease (CVD) remains challenging. We aimed to establish whether peripheral neuropathy (PN) is associated with incident CVD events and to what extent information on PN may improve risk prediction among individuals with type 2 diabetes.
We obtained data for individuals with type 2 diabetes, and free of CVD, from a large primary care patient cohort. Incident CVD events were recorded during a 30-month follow-up period. Eligible individuals had complete ascertainment of cardiovascular risk factors and PN status at baseline. The association between PN and incident CVD events (non-fatal myocardial infarction, coronary revascularisation, congestive cardiac failure, transient ischaemic attack and stroke) was evaluated using Cox regression, adjusted for standard CVD risk factors. We assessed the predictive accuracy of models including conventional CVD risk factors with and without information on PN.
Among 13 043 eligible individuals, we recorded 407 deaths from any cause and 399 non-fatal CVD events. After adjustment for age, sex, ethnicity, systolic blood pressure, cholesterol, body mass index, HbA1c, smoking status and use of statin or antihypertensive medication, PN was associated with incident CVD events (HR 1.33; 95% CI 1.02 to 1.75, p=0.04). The addition of information on PN to a model based on standard CVD risk factors resulted in modest improvements in discrimination for CVD risk prediction and reclassified 6.9% of individuals into different risk categories.
PN is associated with increased risk for a first cardiovascular event among individuals with diabetes.
识别心血管疾病(CVD)高危糖尿病患者仍具有挑战性。我们旨在确定周围神经病变(PN)是否与CVD事件的发生相关,以及PN信息在多大程度上可以改善2型糖尿病患者的风险预测。
我们从一个大型初级保健患者队列中获取了2型糖尿病且无CVD患者的数据。在30个月的随访期内记录CVD事件的发生情况。符合条件的个体在基线时已全面确定心血管危险因素和PN状态。使用Cox回归评估PN与CVD事件(非致命性心肌梗死、冠状动脉血运重建、充血性心力衰竭、短暂性脑缺血发作和中风)之间的关联,并对标准CVD危险因素进行校正。我们评估了包含常规CVD危险因素且有或无PN信息的模型的预测准确性。
在13043名符合条件的个体中,我们记录了407例任何原因导致的死亡和399例非致命性CVD事件。在对年龄、性别、种族、收缩压、胆固醇、体重指数、糖化血红蛋白、吸烟状况以及他汀类药物或抗高血压药物的使用进行校正后,PN与CVD事件的发生相关(风险比1.33;95%置信区间1.02至1.75,p=0.04)。在基于标准CVD危险因素的模型中添加PN信息,在CVD风险预测的辨别力方面有适度改善,并将6.9%的个体重新分类到不同风险类别。
PN与糖尿病患者首次发生心血管事件的风险增加相关。