Preindex Social Context and Cardiovascular Events Across Blood Pressure, LDL Cholesterol, and A1c Cohorts.

Sana Mirza, Joshua Moen
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Abstract

Background: Cardiovascular prevention is organized around target metrics. Blood pressure, LDL cholesterol, and A1c define treatment targets, quality metrics, and, implicitly, who is considered safe. Yet a value below a cutoff is a correlative measurement, not an outcome. We tested whether social context recorded before the measurement separated subsequent cardiovascular events among people whose numbers already met the cutoff.

Methods: In this retrospective cohort study, we analyzed All of Us participants without recorded cardiovascular disease and with low comorbidity in three separately indexed cohorts: systolic blood pressure (SBP), LDL cholesterol, and A1c. A preindex score combined household income, education, food security, physical activity, and ZIP-linked deprivation, standardized against a fixed pooled reference of 325,652 eligible people. Cox models adjusted for the measured biomarker value, its square, a score-by-biomarker term, medication exposure, and clinical covariates. The outcome was first myocardial infarction, ischemic stroke, or heart failure. A sensitivity analysis indexed participants at the first measurement after the score became computable and counted only events recorded in inpatient or emergency settings.

Results: The SBP, LDL, and A1c cohorts included 19,525, 16,578, and 18,539 participants with 144, 129, and 191 events. Each one-SD more favorable score was associated with lower hazard: HR 0.611 (95% CI 0.498-0.749), 0.631 (0.512-0.778), and 0.544 (0.457-0.648), respectively. Below each study cutoff (SBP <140 mmHg, LDL <100 mg/dL, A1c <8%), less favorable context had event rates of 3.39 versus 1.68, 7.16 versus 2.05, and 8.67 versus 2.34 per 1,000 person-years. In a one-year analysis restricted to 2019-2023 index dates, the corresponding adjusted HRs were 0.530, 0.336, and 0.365. In the sensitivity cohorts (54,338, 41,451, and 33,607 participants; 493, 288, and 316 events), HRs were 0.732 (0.657-0.815), 0.660 (0.573-0.761), and 0.631 (0.552-0.722).

Conclusions: A biomarker below the study cutoff did not identify a uniform, low-risk population. Social context recorded before the measurement separated cardiovascular events after adjustment for the measured value and clinical factors. Risk assessment that stops at the number misses this variation.

血压、低密度脂蛋白胆固醇和糖化血红蛋白队列的指标前社会背景和心血管事件
背景:心血管预防是围绕目标指标组织的。血压、低密度脂蛋白胆固醇和糖化血红蛋白确定了治疗目标、质量指标,并隐含地确定了谁被认为是安全的。然而,低于临界值的值是一种相关测量,而不是结果。我们测试了在测量之前记录的社会背景是否会在已经达到临界值的人群中分离出随后的心血管事件。方法:在这项回顾性队列研究中,我们分析了在收缩压(SBP)、低密度脂蛋白胆固醇和A1c三个单独索引队列中所有无心血管疾病和低合并症的参与者。指数前得分综合了家庭收入、教育、食品安全、体育活动和与邮政相关的贫困,并根据325,652名符合条件的人的固定汇总参考标准进行了标准化。Cox模型调整了测量的生物标志物值、其平方、生物标志物评分项、药物暴露和临床协变量。结果首先是心肌梗死、缺血性中风或心力衰竭。敏感度分析在得分可计算后的第一次测量中对参与者进行索引,并仅计算住院或紧急情况下记录的事件。结果:收缩压、低密度脂蛋白和A1c队列包括19,525、16,578和18,539名参与者,分别发生144、129和191起事件。每多一个标准差的有利评分与更低的风险相关:HR分别为0.611 (95% CI 0.498-0.749)、0.631(0.512-0.778)和0.544(0.457-0.648)。结论:低于研究截止点的生物标志物不能识别出统一的低风险人群。测量前记录的社会背景将测量值和临床因素调整后的心血管事件分开。停留在数字上的风险评估忽略了这种变化。已知情况:社会、经济和社区条件决定心血管危险因素并预测心血管事件。血压、低密度脂蛋白胆固醇和糖化血红蛋白是锚定预防和质量测量的目标,但针对这些目标进行治疗的试验显示,硬结果的绝对降低幅度不大。研究补充:在对测量的生物标志物本身进行调整后,在收缩压、低密度脂蛋白胆固醇和A1c队列中,每一个更有利的指标前社会背景的SD与心肌梗死、缺血性中风或心力衰竭的风险降低37%至46%相关。协会坚持,在27%到37%之间,在敏感人群的1.8到2.8倍。下面每个生物标志物截止,不利于上下文进行2 -观察事件利率上涨近4倍。低于研究截止值的值表示生物标志物类别;所记录的社会背景确定了该类别中后续事件的变化。
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