Department of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Department of Family Medicine, G012F, Health Sciences Centre, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N 4N1, Canada.
Sci Rep. 2022 Jul 27;12(1):12780. doi: 10.1038/s41598-022-16904-x.
Identifying high-risk individuals for targeted intervention may prevent or delay hypertension onset. We developed a hypertension risk prediction model and subsequent risk sore among the Canadian population using measures readily available in a primary care setting. A Canadian cohort of 18,322 participants aged 35-69 years without hypertension at baseline was followed for hypertension incidence, and 625 new hypertension cases were reported. At a 2:1 ratio, the sample was randomly divided into derivation and validation sets. In the derivation sample, a Cox proportional hazard model was used to develop the model, and the model's performance was evaluated in the validation sample. Finally, a risk score table was created incorporating regression coefficients from the model. The multivariable Cox model identified age, body mass index, systolic blood pressure, diabetes, total physical activity time, and cardiovascular disease as significant risk factors (p < 0.05) of hypertension incidence. The variable sex was forced to enter the final model. Some interaction terms were identified as significant but were excluded due to their lack of incremental predictive capacity. Our model showed good discrimination (Harrel's C-statistic 0.77) and calibration (Grønnesby and Borgan test, [Formula: see text] statistic = 8.75, p = 0.07; calibration slope 1.006). A point-based score for the risks of developing hypertension was presented after 2-, 3-, 5-, and 6 years of observation. This simple, practical prediction score can reliably identify Canadian adults at high risk of developing incident hypertension in the primary care setting and facilitate discussions on modifying this risk most effectively.
识别高危个体进行针对性干预可能预防或延迟高血压的发生。我们使用初级保健环境中易于获得的措施，为加拿大人群开发了高血压风险预测模型和随后的风险评分。在一项无高血压基线的 18322 名 35-69 岁加拿大队列中，对高血压发病进行了随访，报告了 625 例新发高血压病例。按照 2:1 的比例，将样本随机分为推导和验证集。在推导样本中，使用 Cox 比例风险模型开发模型，并在验证样本中评估模型性能。最后，创建了一个风险评分表，其中包含模型的回归系数。多变量 Cox 模型确定年龄、体重指数、收缩压、糖尿病、总体力活动时间和心血管疾病是高血压发病的显著危险因素（p<0.05）。变量性别被强制纳入最终模型。一些交互项被确定为显著，但由于缺乏增量预测能力而被排除。我们的模型显示出良好的区分度（Harrell 的 C 统计量为 0.77）和校准度（Grønnesby 和 Borgan 检验，[公式：见文本]统计量=8.75，p=0.07；校准斜率 1.006）。提出了一种基于点的高血压发病风险评分，观察 2、3、5 和 6 年后。这个简单实用的预测评分可以可靠地识别出加拿大成年人在初级保健环境中发生高血压的高危人群，并有助于讨论如何最有效地改变这种风险。
