Development of Predictive Equations for Nocturnal Hypertension and Nondipping Systolic Blood Pressure

Author:

Jaeger Byron C.1,Booth John N.2,Butler Mark3,Edwards Lloyd J.1,Lewis Cora E.2,Lloyd‐Jones Donald M.4,Sakhuja Swati2,Schwartz Joseph E.56,Shikany James M.7,Shimbo Daichi6,Yano Yuichiro8,Muntner Paul2

Affiliation:

1. Department of Biostatistics University of Alabama at Birmingham AL

2. Department of Epidemiology University of Alabama at Birmingham AL

3. Department of Population Health Sciences New York University School of Medicine New York NY

4. Department of Preventive Medicine Northwestern University Evanston IL

5. Department of Psychiatry Stony Brook School of Medicine Stony Brook NY

6. Department of Medicine Columbia University Medical Center New York NY

7. Division of Preventive Medicine Department of Medicine University of Alabama at Birmingham AL

8. Department of Community and Family Medicine Duke University Durham NC

Abstract

Background Nocturnal hypertension, defined by a mean asleep systolic blood pressure (SBP)/diastolic blood pressure (BP) ≥120/70 mm Hg, and nondipping SBP , defined by an awake‐to‐asleep decline in SBP <10%, are each associated with increased risk for cardiovascular disease. Methods and Results We developed predictive equations to identify adults with a high probability of having nocturnal hypertension or nondipping SBP using data from the CARDIA (Coronary Artery Risk Development in Young Adults) study (n=787), JHS (Jackson Heart Study) (n=1063), IDH (Improving the Detection of Hypertension) study (n=395), and MHT (Masked Hypertension) study (n=772) who underwent 24‐hour ambulatory BP monitoring. Participants were randomized to derivation (n=2511) or validation (n=506) data sets. The prevalence rates of nocturnal hypertension and nondipping SBP were 39.7% and 44.9% in the derivation data set, respectively, and 36.6% and 44.5% in the validation data set, respectively. The predictive equation for nocturnal hypertension included age, race/ethnicity, smoking status, neck circumference, height, high‐density lipoprotein cholesterol, albumin/creatinine ratio, and clinic SBP and diastolic BP. The predictive equation for nondipping SBP included age, sex, race/ethnicity, waist circumference, height, alcohol use, high‐density lipoprotein cholesterol, and albumin/creatinine ratio. Concordance statistics (95% CI) for nocturnal hypertension and nondipping SBP predictive equations in the validation data set were 0.84 (0.80–0.87) and 0.73 (0.69–0.78), respectively. Compared with reference models including antihypertensive medication use and clinic SBP and diastolic BP as predictors, the continuous net reclassification improvement (95% CI) values for the nocturnal hypertension and nondipping SBP predictive equations were 0.52 (0.35–0.69) and 0.51 (0.34–0.69), respectively. Conclusions These predictive equations can direct ambulatory BP monitoring toward adults with high probability of having nocturnal hypertension and nondipping SBP .

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

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