Derivation and validation of a prediction score for major coronary heart disease events in a UK type 2 diabetic population
Derivation and validation of a prediction score for major coronary heart disease events in a UK type 2 diabetic population
复制标题
DOI：
10.2337/dc05-1911
复制
发表时间：
2006-06-01
期刊：
影响因子：
16.2
通讯作者：
Morris, Andrew D.
中科院分区：
文献类型：
--
作者：
Donnan, Peter T.;Donnelly, Louise;Morris, Andrew D.
目的：推导并验证英国主要冠心病事件的绝对风险算法。研究设计和方法-2004年在苏格兰Tay side UK和lonitudinallfill建立了患有2型糖尿病的人群队列。参与者均为2型糖尿病患者，在苏格兰泰赛德的糖尿病审计和研究数据库（97%敏感）中注册，既往无CHD事件，并进行了完整的测量（n = 4，569）。主要结局指标为CHD风险，定义为致死性或非致死性心肌梗死或CHD死亡，来自Weibull加速失效时间模型。在来自英国英格兰索尔福德的独立数据集上进行算法验证。结果-在1995年1月1日至2004年6月30日的随访期间（最长随访时间为9.5年），共有243例受试者（5.3%）发生致死性或非致死性心肌梗死或CHD死亡。最终的威布尔模型包括诊断时的年龄、糖尿病持续时间、HbA（1c）、吸烟（目前、过去、从未）、性别、收缩压、治疗的高血压、总胆固醇和身高的显著预测因素。Salford验证数据集的鉴别和校准评估显示出良好的拟合（c = 0.71 [95%CI 0.63- 0.79]）。结论-本研究提供了第一个经验证的、人群衍生的模型，用于预测2型糖尿病患者CHD的绝对风险。它为临床医生治疗2型糖尿病提供了一个有用的额外决策辅助，通过指示适当的早期行动来降低不良结局的风险。
OBJECTIVE- To derive and validate an absolute risk algorithm for major coronary heart disease (CHD) events in the U.K. population with type 2 diabetes.RESEARCH DESIGN AND METHODS- A population cohort With type 2 diabetes was constructed in Tay side Scotland U K and lonitudinallfll d 2004. Participants were all people with type 2 diabetes registered with general practices and the Diabetes Audit and Research in Tayside, Scotland, database (97% sensitive) with no previous CHD event and with complete measurements (n = 4,569). The main outcome measure was risk of CHD defined as fatal or nonfatal myocardial infarction or CHD death, derived from the Weibull accelerated failure-time model. Validation of the algorithin was performed on an independent dataset from Salford, England, U.K.RESULTS- There were a total of 243 subjects (5.3%) with a fatal or nonfatal myocardial infarction or CHD death over the follow-up period from I January 1995 to 30 June 2004 (maximum follow-up 9.5 years). The final Weibull model included the significant predictors Of age at diagnosis, duration of diabetes, HbA(1c), smoking (current, past, never), Sex, Systolic blood pressure, treated hypertension, total cholesterol, and height. Assessment of discrimination and calibration in the Salford validation dataset demonstrated a good fit (c = 0.71 [95% Cl 0.63- 0.79]).CONCLUSIONS- This study provides the first Validated, population-derived model for prediction of absolute risk of CHD in people with type 2 diabetes. It provides a useful additional decision aid for the clinician treating type 2 diabetes by indicating appropriate early action to decrease the risk of adverse outcomes.