The HOPE Asia Network consensus on blood pressure measurements corresponding to office measurements: Automated office, home, and ambulatory blood pressures

For adopting recently introduced hypertension phenotypes categorized using office and out of office blood pressure (BP) for the diagnosis of hypertension and antihypertension drug therapy, it is mandatory to define the corresponding out of office BP with the specific target BP recommended by the major guidelines. Such conditions include white-coat hypertension (WCH), masked hypertension (MH), white-coat uncontrolled hypertension (WUCH), and masked uncontrolled hypertension (MUCH). Here, the authors review the relevant literature and discuss the related issue to facilitate the use of corresponding BPs for proper diagnosis of WCH, MH, WUCH, and MUCH in the setting of standard target BP as well as intensive target BP. The methodology of deriving the corresponding BP has evolved from statistical methods such as standard deviation, percentile value, and regression to an outcome-based approach using pooled international cohort study data and comparative analysis in randomized clinical trials for target BPs such as the SPRINT and STEP studies. Corresponding BPs to 140/90 and 130/80 mm Hg in office BP is important for safe and strict achievement of intensive BP targets. The corresponding home, daytime, and 24-h BPs to 130/80 mm Hg in office BP are 130/80, 130/80, and 125/75 mm Hg, respectively. However, researchers have found some discrepancies among the home corresponding BPs. As tentative criterion for de-escalation of antihypertensive therapy as shown in European guidelines was 120 mm Hg in office BP, corresponding home, daytime, and 24-h systolic BPs to 120 mm Hg in office systolic BP are 120, 120, and 115 mm Hg, respectively.

Adverse cardiac remodeling is absent in patients with true controlled resistant hypertension

Resistant hypertension (RHTN), defined as blood pressure (BP) that is uncontrolled with ≥3 medications, including a long-acting thiazide diuretic, also includes a subset with BP that is controlled with ≥4 medications, so-called controlled RHTN. This resistance is attributed to intravascular volume excess. Patients with RHTN overall have a higher prevalence of left ventricular hypertrophy (LVH) and diastolic dysfunction compared to patients with non-RHTN. We tested the hypothesis that patients with controlled RHTN due to the intravascular volume excess have higher left ventricular mass index (LVMI), higher prevalence of LVH, larger intracardiac volumes, and more diastolic dysfunction compared to patients with controlled non-resistant hypertension (CHTN), defined as BP controlled with ≤3 anti-hypertensive medications. Patients with controlled RHTN (n = 69) or CHTN (n = 63) who were treated at the University of Alabama at Birmingham were offered enrollment and underwent cardiac magnetic resonance imaging. Diastolic function was assessed by peak filling rate, time needed in diastole to recover 80% of stroke volume, E:A ratios and left atrial volume. LVMI was higher in patients with controlled RHTN (64.4 ± 22.5 vs 56.9 ± 11.5; P = .017). Intracardiac volumes were similar in both groups. Diastolic function parameters were not significantly different between groups. There were no significant differences in age, gender, race, body mass index, dyslipidemia between the two groups. The findings show that patients with controlled RHTN have higher LVMI, but comparable diastolic function to those of patients with CHTN.

Nomogram based on clinical features at a single outpatient visit to predict masked hypertension and masked uncontrolled hypertension: A study of diagnostic accuracy

Patients with masked hypertension (MH) and masked uncontrolled hypertension (MUCH) are easily overlooked, and both cause target organ damage. We propose a prediction model for MH and MUCH patients based on clinical features at a single outpatient visit. Data collection was planned before the index test and reference standard were after. Thus, we retrospectively collect analyzed 804 subjects who underwent ambulatory blood pressure monitoring (ABPM) at Renmin Hospital of Wuhan University. These patients were divided into normotension/controlled hypertension group (n = 121), MH/MUCH (n = 347), and sustained hypertension (SH)/sustained uncontrolled hypertension group (SUCH) (n = 302) for baseline characteristic analysis. Models were constructed by logistic regression, a nomogram was visualized, and internal validation by bootstrapping. All groups were performed according to the definition proposed by the Chinese Hypertension Association. Compared with normotension/controlled hypertension, patients with MH/MUCH had higher office blood pressure (BP) and were more likely to have poor liver and kidney function, metabolic disorder and myocardial damage. By analysis, [office systolic blood pressure (OSBP)] (P = .004) and [office diastolic blood pressure (ODBP)] (P = .007) were independent predictors of MH and MUCH. By logistic regression backward stepping method, office BP, body mass index (BMI), total cholesterol (Tch), high-density lipoprotein cholesterol (HDL-C), and left ventricular mass index are contained in this model [area under curve (AUC) = 0.755] and its mean absolute error is 0.015. Therefore, the prediction model established by the clinical characteristics or relevant data obtained from a single outpatient clinic can accurately predict MH and MUCH.

Prediction of Masked Hypertension and Masked Uncontrolled Hypertension Using Machine Learning

Objective: This study aimed to develop machine learning-based prediction models to predict masked hypertension and masked uncontrolled hypertension using the clinical characteristics of patients at a single outpatient visit.

Methods: Data were derived from two cohorts in Taiwan. The first cohort included 970 hypertensive patients recruited from six medical centers between 2004 and 2005, which were split into a training set (n = 679), a validation set (n = 146), and a test set (n = 145) for model development and internal validation. The second cohort included 416 hypertensive patients recruited from a single medical center between 2012 and 2020, which was used for external validation. We used 33 clinical characteristics as candidate variables to develop models based on logistic regression (LR), random forest (RF), eXtreme Gradient Boosting (XGboost), and artificial neural network (ANN).

Results: The four models featured high sensitivity and high negative predictive value (NPV) in internal validation (sensitivity = 0.914–1.000; NPV = 0.853–1.000) and external validation (sensitivity = 0.950–1.000; NPV = 0.875–1.000). The RF, XGboost, and ANN models showed much higher area under the receiver operating characteristic curve (AUC) (0.799–0.851 in internal validation, 0.672–0.837 in external validation) than the LR model. Among the models, the RF model, composed of 6 predictor variables, had the best overall performance in both internal and external validation (AUC = 0.851 and 0.837; sensitivity = 1.000 and 1.000; specificity = 0.609 and 0.580; NPV = 1.000 and 1.000; accuracy = 0.766 and 0.721, respectively).

Conclusion: An effective machine learning-based predictive model that requires data from a single clinic visit may help to identify masked hypertension and masked uncontrolled hypertension.

High incidence of masked hypertension in patientswith obstructive sleep apnoea despite normal automatedoffice blood pressure measurement results

INTRODUCTION

Obstructive sleep apnoea (OSA) is a well-known risk factor for masked hypertension (MH) and masked uncontrolled hypertension (MUCH). Automated ambulatory office blood pressure measurement (AOBP) might better correlate with the results of ambulatory blood pressure measurements (ABPM) compared to routine office blood pressure measurement (OBPM). The aim of this study was to compare the diagnostic rate of MH/MUCH when using OBPM and AOBP in combination with ABPM.

MATERIAL AND METHODS

65 OSA patients, of which 58 were males, (AHI > 5, mean 44.4; range 5-103) of average age 48.8 ± 10.7 years were involved in this study. Following MH/MUCH criteria were used; Criteria I: OBPM < 140/90 mm Hg and daytime ABPM > 135/85 mm Hg; Criteria II: AOBP < 140/90 mm Hg and daytime ABPM > 135/85 mm Hg; Criteria III: AOBP < 135/85 mm Hg and daytime ABPM > 135/85 mm Hg.

RESULTS

MH/MUCH criteria I was met in 16 patients (24.6%) with criteria II being met in 37 patients (56.9%), and criteria III in 33 (51.0%), p < 0.0001. Both systolic and diastolic OBPM were significantly higher than AOBP; Systolic (mm Hg): 135.3 ± 12.3 vs 122.1 ± 10.1 (p < 0.0001); Diastolic (mm Hg): 87.4 ± 8.9 vs 77.1 ± 9.3 (p < 0.0001). AOBP was significantly lower than daytime ABPM; Systolic (mm Hg): 122.1 ± 10.1 vs 138.9 ± 10.5 (p < 0.0001); Diastolic (mm Hg): 77.1 ± 9.3 vs 81.6 ± 8.1 (p < 0.0001). Non-dipping phenomenon was present in 38 patients (58.4%). Nocturnal hypertension was present in 55 patients (84.6%).

CONCLUSIONS

In patients with OSA there is a much higher prevalence of MH/MUCH despite normal AOBP, therefore it is necessary to perform a 24-hour ABPM even if OBPM and AOBP are normal.

Reproducibility of masked uncontrolled hypertension detected through home blood pressure monitoring

Masked uncontrolled hypertension (MUCH) is an entity described in treated hypertensive subjects, where office blood pressure (BP) is well controlled and out-of-office BP is elevated. It has been related to a higher cardiovascular risk. However, the reproducibility of MUCH has been scarcely studied. In this study, we aimed to determine the reproducibility of MUCH detected through home blood pressure monitoring (HBPM). Two sets of measurements were performed in hypertensive adults under stable treatment with a 1-week interval. Each set of measurements included three office BP readings and a 4-day HBPM with duplicate readings in the morning, afternoon, and evening (the same validated oscillometric device was employed in both settings). We determined the percentage of agreement regarding the presence of MUCH in the two sets of measurements and quantified such agreement through the Cohen's kappa coefficient (κ), its 95% confidence interval, and P value. We included 105 patients (median age 58.6 [IQR 45.6-67.2] years old, 53.4% men). MUCH prevalence on at least one occasion was 22.3% (95% CI: 15.2-31.5). The reproducibility of MUCH was scant: κ = 0.19 (95% CI: 0.0002-0.38), P = 0.02, due to the poor reproducibility of the office BP component of MUCH in comparison with the home BP component: κ = 0.21 (95% CI: 0.03-0.39), P = 0.01 vs κ = 0.48 (95% CI 0.29-0.67), P < 0.001, respectively. In conclusion, the reproducibility of MUCH detected through HBPM is minimal, mainly due to the poor reproducibility of office BP measurements. An HBPM-based strategy for the management of patients with MUCH may be more adequate in terms of cardiovascular morbidity and mortality.

MASked-unconTrolled hypERtension management based on office BP or on ambulatory blood pressure measurement (MASTER) Study: a randomised controlled trial protocol

INTRODUCTION

Masked uncontrolled hypertension (MUCH) carries an increased risk of cardiovascular (CV) complications and can be identified through combined use of office (O) and ambulatory (A) blood pressure (BP) monitoring (M) in treated patients. However, it is still debated whether the information carried by ABPM should be considered for MUCH management. Aim of the MASked-unconTrolled hypERtension management based on OBP or on ambulatory blood pressure measurement (MASTER) Study is to assess the impact on outcome of MUCH management based on OBPM or ABPM.

METHODS AND ANALYSIS

MASTER is a 4-year prospective, randomised, open-label, blinded-endpoint investigation. A total of 1240 treated hypertensive patients from about 40 secondary care clinical centres worldwide will be included -upon confirming presence of MUCH (repeated on treatment OBP <140/90 mm Hg, and at least one of the following: daytime ABP ≥135/85 mm Hg; night-time ABP ≥120/70 mm Hg; 24 hour ABP ≥130/80 mm Hg), and will be randomised to a management strategy based on OBPM (group 1) or on ABPM (group 2). Patients in group 1 will have OBP measured at 0, 3, 6, 12, 18, 24, 30, 36, 42 and 48 months and taken as a guide for treatment; ABPM will be performed at randomisation and at 12, 24, 36 and 48 months but will not be used to take treatment decisions. Patients randomised to group 2 will have ABPM performed at randomisation and all scheduled visits as a guide to antihypertensive treatment. The effects of MUCH management strategy based on ABPM or on OBPM on CV and renal intermediate outcomes (changing left ventricular mass and microalbuminuria, coprimary outcomes) at 1 year and on CV events at 4 years and on changes in BP-related variables will be assessed.

ETHICS AND DISSEMINATION

MASTER study protocol has received approval by the ethical review board of Istituto Auxologico Italiano. The procedures set out in this protocol are in accordance with principles of Declaration of Helsinki and Good Clinical Practice guidelines. Results will be published in accordance with the CONSORT statement in a peer-reviewed scientific journal.

TRIAL REGISTRATION NUMBER

NCT02804074; Pre-results.

Prognosis of Masked and White Coat Uncontrolled Hypertension Detected by Ambulatory Blood Pressure Monitoring in Elderly Treated Hypertensive Patients

BACKGROUND

Prognosis of masked and white coat uncontrolled hypertension (MUCH and WCUCH, respectively) detected by ambulatory blood pressure (BP) monitoring is incompletely clear in elderly treated hypertensive patients. We evaluated prognosis of MUCH and WCUCH identified by ambulatory BP monitoring in this setting.

METHODS

The occurrence of a composite endpoint was evaluated in 1,191 elderly treated hypertensive patients. Controlled hypertension (CH) was defined as clinic BP <140/90 mm Hg and 24-hour BP <130/80 mm Hg, MUCH as clinic BP <140/90 mm Hg and 24-hour BP ≥130 and/or ≥80 mm Hg, WCUCH as clinic BP ≥140 and/or ≥90 mm Hg and 24-hour BP <130/80 mm Hg and sustained uncontrolled hypertension (SUCH) as clinic BP ≥140 and/or ≥90 mm Hg and 24-hour BP ≥130 and/or ≥80 mm Hg.

RESULTS

MUCH was identified in 142 patients (12% of all the population, 34% of those with normal clinic BP) and WCUCH in 230 patients (19% of all the population, 30% of those with high clinic BP). During the follow-up (9.1 ± 4.9 years, range 0.4-20 years), 392 events occurred. After adjustment for various covariates, patients with MUCH (hazard ratio (HR) 1.60, 95% confidence interval (CI) 1.12-2.29, P = 0.01) and SUCH (HR 1.81, 95% CI, 1.35-2.42, P < 0.001) had significantly higher cardiovascular risk than those with CH, whereas those with WCUCH (HR 1.09, 95% CI, 0.74-1.60, P = 0.66) had not significantly higher risk.

CONCLUSIONS

In elderly treated hypertensive patients evaluated by ambulatory BP monitoring, compared to individuals with CH, those with MUCH have significantly higher risk and those with WCUCH have slightly and not significantly higher risk.

Effort-Reward Imbalance at Work and the Prevalence of Unsuccessfully Treated Hypertension Among White-Collar Workers

We examined the association between effort-reward imbalance (ERI) exposure at work and unsuccessfully treated hypertension among white-collar workers from a large cohort in Quebec City, Canada. The study used a repeated cross-sectional design involving 3 waves of data collection (2000-2009). The study sample was composed of 474 workers treated for hypertension, accounting for 739 observations. At each observation, ERI was measured using validated scales, and ambulatory blood pressure (BP) was measured every 15 minutes during the working day. Unsuccessfully treated hypertension was defined as daytime ambulatory BP of at least 135/85 mm Hg and was further divided into masked and sustained hypertension. Adjusted prevalence ratios and 95% confidence intervals were estimated. Participants in the highest tertile of ERI exposure had a higher prevalence of unsuccessfully treated hypertension (prevalence ratio = 1.45, 95% confidence interval: 1.16, 1.81) after adjustment for gender, age, education, family history of cardiovascular diseases, body mass index, diabetes, smoking, sedentary behaviors, and alcohol intake. The present study supports the effect of adverse psychosocial work factors from the ERI model on BP control in treated workers. Reducing these frequent exposures at work might lead to substantial benefits on BP control at the population level.