Kontopantelis Evangelos, Springate David A, Reeves David, Ashcroft Darren M, Rutter Martin K, Buchan Iain, Doran Tim
NIHR School for Primary Care Research, Centre for Primary Care, Institute of Population Health, University of Manchester, Manchester, UK,
Diabetologia. 2015 Mar;58(3):505-18. doi: 10.1007/s00125-014-3473-8. Epub 2014 Dec 16.
AIMS/HYPOTHESIS: We aimed to describe the shape of observed relationships between risk factor levels and clinically important outcomes in type 2 diabetes after adjusting for multiple confounders.
We used retrospective longitudinal data on 246,544 adults with type 2 diabetes from 600 practices in the Clinical Practice Research Datalink, 2006-2012. Proportional hazards regression models quantified the risks of mortality and microvascular or macrovascular events associated with four modifiable biological variables (HbA1c, systolic BP, diastolic BP and total cholesterol), while controlling for important patient and practice covariates.
U-shaped relationships were observed between all-cause mortality and levels of the four biometric risk factors. Lowest risks were associated with HbA1c 7.25-7.75% (56-61 mmol/mol), total cholesterol 3.5-4.5 mmol/l, systolic BP 135-145 mmHg and diastolic BP 82.5-87.5 mmHg. Coronary and stroke mortality related to the four risk factors in a positive, curvilinear way, with the exception of systolic BP, which related to deaths in a U-shape. Macrovascular events showed a positive and curvilinear relationship with HbA1c but a U-shaped relationship with total cholesterol and systolic BP. Microvascular events related to the four risk factors in a curvilinear way: positive for HbA1c and systolic BP but negative for cholesterol and diastolic BP.
CONCLUSIONS/INTERPRETATION: We identified several relationships that support a call for major changes to clinical practice. Most importantly, our results support trial data indicating that normalisation of glucose and BP can lead to poorer outcomes. This makes a strong case for target ranges for these risk factors rather than target levels.
目的/假设：我们旨在描述在调整多个混杂因素后，2型糖尿病患者风险因素水平与临床重要结局之间观察到的关系的形态。
我们使用了临床实践研究数据链中600家医疗机构的246,544例2型糖尿病成年患者的回顾性纵向数据，时间跨度为2006年至2012年。比例风险回归模型量化了与四个可改变的生物学变量（糖化血红蛋白、收缩压、舒张压和总胆固醇）相关的死亡风险以及微血管或大血管事件风险，同时控制重要的患者和医疗机构协变量。
全因死亡率与四个生物测量风险因素水平之间呈现U型关系。最低风险与糖化血红蛋白7.25 - 7.75%（56 - 61 mmol/mol）、总胆固醇3.5 - 4.5 mmol/l、收缩压135 - 145 mmHg和舒张压82.5 - 87.5 mmHg相关。冠心病和卒中死亡率与这四个风险因素呈正的曲线关系，但收缩压与死亡呈U型关系。大血管事件与糖化血红蛋白呈正的曲线关系，但与总胆固醇和收缩压呈U型关系。微血管事件与这四个风险因素呈曲线关系：与糖化血红蛋白和收缩压呈正相关，但与胆固醇和舒张压呈负相关。
结论/解读：我们确定了几种支持呼吁对临床实践进行重大改变的关系。最重要的是，我们的结果支持试验数据，表明血糖和血压正常化可能导致更差的结局。这有力地说明了这些风险因素应设定目标范围而非目标水平。
