Interplay of Age and Sex With Clinic and Ambulatory Blood Pressure and Mortality

医学 血压 动态血压 急诊医学 回廊的 风险因素 终身风险 内科学 授权 梅德林 儿科 风险评估 流行病学 心脏病学 重症监护医学
作者
Michael Böhm,Alejandro de la Sierra,Igor Schwantke,Bernhard Haring,Ernest Vinyoles,Manuel Gorostidi,Julián Segura,Bryan Williams,Natalie Staplin,Mert Tokcan,F Mahfoud,Lucas Lauder,Susanne Fleig,Carolin V. Schneider,Luis Miguel Ruilope
出处
期刊:Hypertension [Lippincott Williams & Wilkins]
卷期号:83 (6): e26084-e26084 被引量:1
标识
DOI:10.1161/hypertensionaha.125.26084
摘要

BACKGROUND: To explore associations of clinic and 24-hour ambulatory blood pressure (BP) monitoring (ABPM) with cardiovascular death (CVD), parameters were modeled for age and sex in this large cohort in primary care. METHODS: In the Spanish ABPM Registry, 59.124 patients had complete data on mortality, age, sex, and all ABPM. Office, mean, 24-hour, daytime, and nighttime systolic BP (SBP), diastolic BP, and pulse pressure (PP) were related to CVD according to age and sex and were modelled with restricted cubic splines to get trajectories. During a median of 9.7 years, 2361 patients had CVD (1229 males, 1132 females). RESULTS: Nonlinear relationships for office, 24-hour mean, daytime, and nighttime SBP, diastolic BP, and PP ( P <0.0001 for all) for both sexes were observed. Until 75 years, SBP was higher in males than females, but differences were minimized after ≈60 to 70 years ( P for interaction <0.0001). High SBP and PP are associated with CVD without heterogeneity between sexes and across aging. The increase of SBP and PP was higher at a higher age for females than males ( P for interaction <0.0001). CVD was age-dependent, and ABPM, in particular nighttime BP did more closely associated with risk than office BP in younger than in older individuals. CONCLUSIONS: Twenty-four-hour mean, nighttime BP, and PP were closely associated with risk being higher in elderly females than males after 75 years, corresponding to a rise in BP in older females. Guidelines should continue to mandate the evaluation of 24-hour ABPM data for risk prediction.
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