Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
J Hypertens. 2019 Mar;37(3):522-529. doi: 10.1097/HJH.0000000000001923.
Blood pressure (BP) is a long-established risk factor for cardiovascular disease (CVD). SBP is used in all widely used cardiovascular risk scores for clinical decision-making. Recently, within-person BP variability has been shown to be a major predictor of CVD. We investigated whether cardiovascular risk scores could be improved by incorporating BP variability with standard risk factors.
We used cohort data on patients aged 40-74 on 1 January 2005, from English general practices contributing to the Clinical Practice Research Datalink, a research database derived from electronic health records. Data were linked to hospital episodes and mortality data. SBP variability independent of the mean was calculated across up to six clinic visits. We divided data geographically into derivation and validation data sets. In the derivation data set, we developed a reference model, incorporating risk factors used in previous scores and an index model, incorporating the same factors and BP variability. We calculated model validation statistics in the validation data set including calibration ratio and c-statistic.
In the derivation data set, BP variability was associated with CVD, independently of other risk factors (P = 0.005). However, in the validation data set, both models had similar c-statistic (0.7415 and 0.7419, respectively), R (31.8 and 32.0, respectively) and calibration ratio (0.938 and 0.940, respectively).
The association of BP variability with CVD is statistically significant in a large data set but does not substantially improve the performance of a cardiovascular risk score.
血压(BP)是心血管疾病(CVD)的一个长期确立的风险因素。SBP 被广泛用于所有心血管风险评分以用于临床决策。最近,个体内 BP 变异性已被证明是 CVD 的主要预测因素。我们研究了通过将 BP 变异性与标准风险因素结合起来,心血管风险评分是否可以得到改善。
我们使用了 2005 年 1 月 1 日在参与临床实践研究数据库的英国全科医生中的 40-74 岁患者的队列数据,这是一个从电子健康记录中衍生出来的研究数据库。数据与医院就诊和死亡率数据相关联。在多达六次就诊中计算 SBP 变异性,该变异性独立于平均值。我们将数据按地理位置分为推导数据和验证数据集。在推导数据集中,我们开发了一个参考模型,该模型包含以前评分中使用的风险因素和一个指数模型,该模型包含相同的因素和 BP 变异性。我们在验证数据集中计算了模型验证统计数据,包括校准比和 c 统计量。
在推导数据集中,BP 变异性与 CVD 独立于其他风险因素相关(P=0.005)。然而,在验证数据集中,两个模型的 c 统计量(分别为 0.7415 和 0.7419)、R(分别为 31.8 和 32.0)和校准比(分别为 0.938 和 0.940)相似。
在大型数据集,BP 变异性与 CVD 的关联在统计学上是显著的,但并没有实质性地改善心血管风险评分的性能。