Luis Mena

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

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.

Age-specific differences between conventional and ambulatory daytime blood pressure values.

Mean daytime ambulatory blood pressure (BP) values are considered to be lower than conventional BP values, but data on this relation among younger individuals <50 years are scarce. Conventional and 24-hour ambulatory BP were measured in 9550 individuals not taking antihypertensive treatment from 13 population-based cohorts. We compared individual differences between daytime ambulatory and conventional BP according to 10-year age categories. Age-specific prevalences of white coat and masked hypertension were calculated. Among individuals aged 18 to 30, 30 to 40, and 40 to 50 years, mean daytime BP was significantly higher than the corresponding conventional BP (6.0, 5.2, and 4.7 mm Hg for systolic; 2.5, 2.7, and 1.7 mm Hg for diastolic BP; all P<0.0001). In individuals aged 60 to 70 and ≥70 years, conventional BP was significantly higher than daytime ambulatory BP (5.0 and 13.0 mm Hg for systolic; 2.0 and 4.2 mm Hg for diastolic BP; all P<0.0001).The prevalence of white coat hypertension exponentially increased from 2.2% to 19.5% from those aged 18 to 30 years to those aged ≥70 years, with little variation between men and women (8.0% versus 6.1%; P=0.0003). Masked hypertension was more prevalent among men (21.1% versus 11.4%; P<0.0001). The age-specific prevalences of masked hypertension were 18.2%, 27.3%, 27.8%, 20.1%, 13.6%, and 10.2% among men and 9.0%, 9.9%, 12.2%, 11.9%, 14.7%, and 12.1% among women. In conclusion, this large collaborative analysis showed that the relation between daytime ambulatory and conventional BP strongly varies by age. These findings may have implications for diagnosing hypertension and its subtypes in clinical practice.

Ambulatory Hypertension Subtypes and 24-Hour Systolic and Diastolic Blood Pressure as Distinct Outcome Predictors in 8341 Untreated People Recruited From 12 Populations

Background— Data on risk associated with 24-hour ambulatory diastolic (DBP24) versus systolic (SBP24) blood pressure are scarce. Methods and Results— We recorded 24-hour blood pressure and health outcomes in 8341 untreated people (mean age, 50.8 years; 46.6% women) randomly recruited from 12 populations. We computed hazard ratios (HRs) using multivariable-adjusted Cox regression. Over 11.2 years (median), 927 (11.1%) participants died, 356 (4.3%) from cardiovascular causes, and 744 (8.9%) experienced a fatal or nonfatal cardiovascular event. Isolated diastolic hypertension (DBP24≥80 mm Hg) did not increase the risk of total mortality, cardiovascular mortality, or stroke (HRs⩽1.54; P≥0.18), but was associated with a higher risk of fatal combined with nonfatal cardiovascular, cardiac, or coronary events (HRs≥1.75; P⩽0.0054). Isolated systolic hypertension (SBP24≥130 mm Hg) and mixed diastolic plus systolic hypertension were associated with increased risks of all aforementioned end points (P⩽0.0012). Below age 50, DBP24 was the main driver of risk, reaching significance for total (HR for 1-SD increase, 2.05; P=0.0039) and cardiovascular mortality (HR, 4.07; P=0.0032) and for all cardiovascular end points combined (HR, 1.74; P=0.039) with a nonsignificant contribution of SBP24 (HR⩽0.92; P≥0.068); above age 50, SBP24 predicted all end points (HR≥1.19; P⩽0.0002) with a nonsignificant contribution of DBP24 (0.96⩽HR⩽1.14; P≥0.10). The interactions of age with SBP24 and DBP24 were significant for all cardiovascular and coronary events (P⩽0.043). Conclusions— The risks conferred by DBP24 and SBP24 are age dependent. DBP24 and isolated diastolic hypertension drive coronary complications below age 50, whereas above age 50 SBP24 and isolated systolic and mixed hypertension are the predominant risk factors.

Outcome-Driven Thresholds for Ambulatory Pulse Pressure in 9938 Participants Recruited From 11 Populations

Evidence-based thresholds for risk stratification based on pulse pressure (PP) are currently unavailable. To derive outcome-driven thresholds for the 24-hour ambulatory PP, we analyzed 9938 participants randomly recruited from 11 populations (47.3% women). After age stratification (<60 versus ≥60 years) and using average risk as reference, we computed multivariable-adjusted hazard ratios (HRs) to assess risk by tenths of the PP distribution or risk associated with stepwise increasing (+1 mm Hg) PP levels. All adjustments included mean arterial pressure. Among 6028 younger participants (68 853 person-years), the risk of cardiovascular (HR, 1.58; P=0.011) or cardiac (HR, 1.52; P=0.056) events increased only in the top PP tenth (mean, 60.6 mm Hg). Using stepwise increasing PP levels, the lower boundary of the 95% confidence interval of the successive thresholds did not cross unity. Among 3910 older participants (39 923 person-years), risk increased (P⩽0.028) in the top PP tenth (mean, 76.1 mm Hg). HRs were 1.30 and 1.62 for total and cardiovascular mortality, and 1.52, 1.69, and 1.40 for all cardiovascular, cardiac, and cerebrovascular events. The lower boundary of the 95% confidence interval of the HRs associated with stepwise increasing PP levels crossed unity at 64 mm Hg. While accounting for all covariables, the top tenth of PP contributed less than 0.3% (generalized R2 statistic) to the overall risk among the elderly. Thus, in randomly recruited people, ambulatory PP does not add to risk stratification below age 60; in the elderly, PP is a weak risk factor with levels below 64 mm Hg probably being innocuous.

Mobile Personal Health System for Ambulatory Blood Pressure Monitoring

The ARVmobile v1.0 is a multiplatform mobile personal health monitor (PHM) application for ambulatory blood pressure (ABP) monitoring that has the potential to aid in the acquisition and analysis of detailed profile of ABP and heart rate (HR), improve the early detection and intervention of hypertension, and detect potential abnormal BP and HR levels for timely medical feedback. The PHM system consisted of ABP sensor to detect BP and HR signals and smartphone as receiver to collect the transmitted digital data and process them to provide immediate personalized information to the user. Android and Blackberry platforms were developed to detect and alert of potential abnormal values, offer friendly graphical user interface for elderly people, and provide feedback to professional healthcare providers via e-mail. ABP data were obtained from twenty-one healthy individuals (>51 years) to test the utility of the PHM application. The ARVmobile v1.0 was able to reliably receive and process the ABP readings from the volunteers. The preliminary results demonstrate that the ARVmobile 1.0 application could be used to perform a detailed profile of ABP and HR in an ordinary daily life environment, bedsides of estimating potential diagnostic thresholds of abnormal BP variability measured as average real variability.

How Many Measurements Are Needed to Estimate Blood Pressure Variability Without Loss of Prognostic Information

BACKGROUND Average real variability (ARV) is a recently proposed index for short-term blood pressure (BP) variability. We aimed to determine the minimum number of BP readings required to compute ARV without loss of prognostic information. METHODS ARV was calculated from a discovery dataset that included 24-hour ambulatory BP measurements for 1,254 residents (mean age = 56.6 years; 43.5% women) of Copenhagen, Denmark. Concordance between ARV from full (≥80 BP readings) and randomly reduced 24-hour BP recordings was examined, as was prognostic accuracy. A test dataset that included 5,353 subjects (mean age = 54.0 years; 45.6% women) with at least 48 BP measurements from 11 randomly recruited population cohorts was used to validate the results. RESULTS In the discovery dataset, a minimum of 48 BP readings allowed an accurate assessment of the association between cardiovascular risk and ARV. In the test dataset, over 10.2 years (median), 806 participants died (335 cardiovascular deaths, 206 cardiac deaths) and 696 experienced a major fatal or nonfatal cardiovascular event. Standardized multivariable-adjusted hazard ratios (HRs) were computed for associations between outcome and BP variability. Higher diastolic ARV in 24-hour ambulatory BP recordings predicted (P < 0.01) total (HR = 1.12), cardiovascular (HR = 1.19), and cardiac (HR = 1.19) mortality and fatal combined with nonfatal cerebrovascular events (HR = 1.16). Higher systolic ARV in 24-hour ambulatory BP recordings predicted (P < 0.01) total (HR = 1.12), cardiovascular (HR = 1.17), and cardiac (HR = 1.24) mortality. CONCLUSIONS Forty-eight BP readings over 24 hours were observed to be adequate to compute ARV without meaningful loss of prognostic information.

Cardiovascular Risk Stratification and Blood Pressure Variability on Ambulatory and Home Blood Pressure Measurement

Variability is a phenomenon attributed to most biological processes and is a particular feature of blood pressure (BP) that concerns many physicians regarding the clinical meaning and the impact on their clinical practice. In this review, we assessed the role of different indices of BP variability in cardiovascular risk stratification. We reviewed the indices of BP variability derived from ambulatory BP monitoring (day-to-night ratio, morning surge of BP, and short-term BP variability) and home BP measurement (standardized conventional BP measurement and self-BP measurement), and summarized our recent results with the intention to provide a clear message for clinical practice. Conclusion: BP variability, either derived from ambulatory BP measurement or home BP measurement does not substantially refine cardiovascular risk prediction over and beyond the BP level. Practitioners should be aware that BP level remains the main modifiable risk factor derived from BP measurement and contributes to improving the control of hypertension and adverse health outcomes.

24‐Hour Blood Pressure Variability Assessed by Average Real Variability: A Systematic Review and Meta‐Analysis

Background Although 24‐hour blood pressure (BP) variability (BPV) is predictive of cardiovascular outcomes independent of absolute BP levels, it is not regularly assessed in clinical practice. One possible limitation to routine BPV assessment is the lack of standardized methods for accurately estimating 24‐hour BPV. We conducted a systematic review to assess the predictive power of reported BPV indexes to address appropriate quantification of 24‐hour BPV, including the average real variability (ARV) index. Methods and Results Studies chosen for review were those that presented data for 24‐hour BPV in adults from meta‐analysis, longitudinal or cross‐sectional design, and examined BPV in terms of the following issues: (1) methods used to calculate and evaluate ARV; (2) assessment of 24‐hour BPV determined using noninvasive ambulatory BP monitoring; (3) multivariate analysis adjusted for covariates, including some measure of BP; (4) association of 24‐hour BPV with subclinical organ damage; and (5) the predictive value of 24‐hour BPV on target organ damage and rate of cardiovascular events. Of the 19 assessed studies, 17 reported significant associations between high ARV and the presence and progression of subclinical organ damage, as well as the incidence of hard end points, such as cardiovascular events. In all these cases, ARV remained a significant independent predictor (P<0.05) after adjustment for BP and other clinical factors. In addition, increased ARV in systolic BP was associated with risk of all cardiovascular events (hazard ratio, 1.18; 95% confidence interval, 1.09–1.27). Only 2 cross‐sectional studies did not find that high ARV was a significant risk factor. Conclusions Current evidence suggests that ARV index adds significant prognostic information to 24‐hour ambulatory BP monitoring and is a useful approach for studying the clinical value of BPV.

Machine learning approach to extract diagnostic and prognostic thresholds: application in prognosis of cardiovascular mortality.

Machine learning has become a powerful tool for analysing medical domains, assessing the importance of clinical parameters, and extracting medical knowledge for outcomes research. In this paper, we present a machine learning method for extracting diagnostic and prognostic thresholds, based on a symbolic classification algorithm called REMED. We evaluated the performance of our method by determining new prognostic thresholds for well-known and potential cardiovascular risk factors that are used to support medical decisions in the prognosis of fatal cardiovascular diseases. Our approach predicted 36% of cardiovascular deaths with 80% specificity and 75% general accuracy. The new method provides an innovative approach that might be useful to support decisions about medical diagnoses and prognoses.

Incidence of dementia in elderly Latin Americans: Results of the Maracaibo Aging Study

There are few longitudinal studies of dementia in developing countries. We used longitudinal data from the Maracaibo Aging Study to accurately determine the age‐ and sex‐specific incidence of dementia in elderly Latin Americans.