Dataset Information

Setting thresholds to varying blood pressure monitoring intervals differentially affects risk estimates associated with white-coat and masked hypertension in the population.

ABSTRACT: Outcome-driven recommendations about time intervals during which ambulatory blood pressure should be measured to diagnose white-coat or masked hypertension are lacking. We cross-classified 8237 untreated participants (mean age, 50.7 years; 48.4% women) enrolled in 12 population studies, using ?140/?90, ?130/?80, ?135/?85, and ?120/?70 mm Hg as hypertension thresholds for conventional, 24-hour, daytime, and nighttime blood pressure. White-coat hypertension was hypertension on conventional measurement with ambulatory normotension, the opposite condition being masked hypertension. Intervals used for classification of participants were daytime, nighttime, and 24 hours, first considered separately, and next combined as 24 hours plus daytime or plus nighttime, or plus both. Depending on time intervals chosen, white-coat and masked hypertension frequencies ranged from 6.3% to 12.5% and from 9.7% to 19.6%, respectively. During 91 046 person-years, 729 participants experienced a cardiovascular event. In multivariable analyses with normotension during all intervals of the day as reference, hazard ratios associated with white-coat hypertension progressively weakened considering daytime only (1.38; P=0.033), nighttime only (1.43; P=0.0074), 24 hours only (1.21; P=0.20), 24 hours plus daytime (1.24; P=0.18), 24 hours plus nighttime (1.15; P=0.39), and 24 hours plus daytime and nighttime (1.16; P=0.41). The hazard ratios comparing masked hypertension with normotension were all significant (P<0.0001), ranging from 1.76 to 2.03. In conclusion, identification of truly low-risk white-coat hypertension requires setting thresholds simultaneously to 24 hours, daytime, and nighttime blood pressure. Although any time interval suffices to diagnose masked hypertension, as proposed in current guidelines, full 24-hour recordings remain standard in clinical practice.

SUBMITTER: Asayama K

PROVIDER: S-EPMC4420482 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Setting thresholds to varying blood pressure monitoring intervals differentially affects risk estimates associated with white-coat and masked hypertension in the population.

Asayama Kei K Thijs Lutgarde L Li Yan Y Gu Yu-Mei YM Hara Azusa A Liu Yan-Ping YP Zhang Zhenyu Z Wei Fang-Fei FF Lujambio Inés I Mena Luis J LJ Boggia José J Hansen Tine W TW Björklund-Bodegård Kristina K Nomura Kyoko K Ohkubo Takayoshi T Jeppesen Jørgen J Torp-Pedersen Christian C Dolan Eamon E Stolarz-Skrzypek Katarzyna K Malyutina Sofia S Casiglia Edoardo E Nikitin Yuri Y Lind Lars L Luzardo Leonella L Kawecka-Jaszcz Kalina K Sandoya Edgardo E Filipovský Jan J Maestre Gladys E GE Wang Jiguang J Imai Yutaka Y Franklin Stanley S SS O'Brien Eoin E Staessen Jan A JA

Hypertension (Dallas, Tex. : 1979) 20140818 5

Outcome-driven recommendations about time intervals during which ambulatory blood pressure should be measured to diagnose white-coat or masked hypertension are lacking. We cross-classified 8237 untreated participants (mean age, 50.7 years; 48.4% women) enrolled in 12 population studies, using ≥140/≥90, ≥130/≥80, ≥135/≥85, and ≥120/≥70 mm Hg as hypertension thresholds for conventional, 24-hour, daytime, and nighttime blood pressure. White-coat hypertension was hypertension on conventional measure ...[more]

PMID: 25135185

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Project description:BackgroundMultiple epidemiological studies from Europe and Asia have demonstrated increased cardiovascular risks associated with isolated elevation of home blood pressure (BP) or masked hypertension (MH). Previous studies have not addressed cardiovascular outcomes associated with MH and white-coat hypertension (WCH) in the general population in the United States.ObjectivesThe goal of this study was to determine hypertensive target organ damage and adverse cardiovascular outcomes associated with WCH (high clinic BP, ≥140/90 mm Hg; normal home BP, <135/85 mm Hg), MH (high home BP, ≥135/85 mm Hg; normal clinic BP, <140/90 mm Hg), and sustained hypertension (high home and clinic BP) in the DHS (Dallas Heart Study), a large, multiethnic, probability-based population cohort.MethodsAssociations among WCH, MH, sustained hypertension, and aortic pulsed wave velocity by magnetic resonance imaging; urinary albumin-to-creatinine ratio; and cystatin C were evaluated at study baseline. Then, associations between WCH and MH with incident cardiovascular outcomes (coronary heart disease, stroke, atrial fibrillation, heart failure, and cardiovascular death) over a median follow-up period of 9 years were assessed.ResultsThe study cohort comprised 3,027 subjects (50% African Americans). The sample-weighted prevalence rates of WCH and MH were 3.3% and 17.8%, respectively. Both WCH and MH were independently associated with increased aortic pulsed wave velocity, cystatin C, and urinary albumin-to-creatinine ratio. Both WCH (adjusted hazard ratio: 2.09; 95% confidence interval: 1.05 to 4.15) and MH (adjusted hazard ratio: 2.03; 95% confidence interval: 1.36 to 3.03) were independently associated with higher cardiovascular events compared with the normotensive group, even after adjustment for traditional cardiovascular risk factors.ConclusionsIn a multiethnic U.S. population, both WCH and MH were independently associated with increased aortic stiffness, renal injury, and incident cardiovascular events. Because MH is common and associated with an adverse cardiovascular profile, home BP monitoring should be routinely performed among U.S. adults.

Project description:Abstract Aims The detection of white-coat hypertension/white-coat uncontrolled hypertension (WCH/WUCH) with out-of-office blood pressure (BP) monitoring is time- and resource-consuming. We aim to develop a machine learning (ML)-derived prediction model based on the characteristics of patients from a single outpatient visit. Methods and results Data from two cohorts in Taiwan were used. Cohort one (970 patients) was used for development and internal validation, and cohort two (464 patients) was used for external validation. WCH/WUCH was defined as an office BP of ≥140/90 mmHg and daytime ambulatory BP of <135/85 mmHg in treatment-naïve or treated individuals. Logistic regression, random forest (RF), eXtreme Gradient Boosting, and artificial neural network models were trained using 26 patient parameters. We used SHapley Additive exPlanations values to provide explanations for the risk factors. All models achieved great area under the receiver operating characteristic curve (AUROC), specificity, and negative predictive value in both validations (AUROC = 0.754–0.891; specificity = 0.682–0.910; negative predictive value = 0.831–0.968). The RF model was the best performing (AUROC = 0.884; sensitivity = 0.619; specificity = 0.887; negative predictive value = 0.872; accuracy = 0.819). The five most influential features of the RF model were office diastolic BP, office systolic BP, current smoker, estimated glomerular filtration rate, and fasting glucose level. Conclusion Our prediction models achieved good performance, underlining the feasibility of applying ML models to outpatient populations for the diagnosis of WCH and WUCH. Further validation with other prospective data sets should be considered in the future. Graphical Abstract Graphical Abstract Two cohorts were used for model development after splitting and external validation respectively. With oversampled training set, four algorithms were developed through the process of feature ranking with SHapley Additive exPlantions values, feature selection, and threshold tuning under five-fold cross-validation. Models were then evaluated by variant metrics. Present study demonstrated the feasibility of applying machine learning models to outpatient population for the identify of white-coat hypertension and white-coat uncontrolled hypertension. ANN, artificial neural network; AUROC, area under the receiver operating characteristic curve; DBP, diastolic blood pressure; LR, logistic regression; NPV, negative predictive value; PPV, positive predictive value; RF, random forest; ROC, receiver operating characteristic; SBP, systolic blood pressure; Sen, sensitivity; SHAP, SHapley Additive exPlanations; Spe, specificity; WCH/WUCH, white-coat hypertension/white-coat uncontrolled hypertension; XGboost, eXtreme Gradient Boosting.

Dataset Information

Setting thresholds to varying blood pressure monitoring intervals differentially affects risk estimates associated with white-coat and masked hypertension in the population.

Publications

Setting thresholds to varying blood pressure monitoring intervals differentially affects risk estimates associated with white-coat and masked hypertension in the population.

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