Dataset Information

Real World Home Blood Pressure Variability in Over 56,000 Individuals With Nearly 17 Million Measurements.

ABSTRACT: BACKGROUND:Using the data from 56,365 individuals, from 185 countries, and a Nokia Health Wireless blood pressure (BP) monitor, we investigated real-world characteristics of BP variability (BPV). METHODS:All included individuals self-measured and uploaded their BP using Bluetooth at least 20 times over a period of ?1 month at a frequency and duration of their choosing. In total, 16,904,844 BP measurements were analyzed, with a median of 146 measurements per person (interquartile range [IQR] 73-321) over a median of 14 months (IQR 7-31). SD, coefficient of variation, maximum BP, and maximum minus minimum BP difference were all calculated as measures of BPV. RESULTS:BPV showed a distinct pattern, influenced by season of year, day of week, and time of day. BPV index was higher in females compared with males (P < 0.001) and increased with age (P < 0.001). Compared to the weekend, the weekday BPV index was significantly higher, and this finding was more prominent in females (P = 0.001). In multivariate analysis, BPV index were significantly associated with age, gender, geographic location, and mean BP values. CONCLUSION:Using the largest BP data set we are aware of, with the benefits and limitations of real-world measurement, we could show the pattern of BPV and provide reference values that may be helpful in understanding the nature of BPV as self-measurement at home becomes more common, and help guide individualized management.

SUBMITTER: Kim KI

PROVIDER: S-EPMC5905665 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Real World Home Blood Pressure Variability in Over 56,000 Individuals With Nearly 17 Million Measurements.

Kim Kwang-Il KI Nikzad Nima N Quer Giorgio G Wineinger Nathan E NE Vegreville Matthieu M Normand Alexis A Schmidt Nicolas N Topol Eric J EJ Steinhubl Steven S

American journal of hypertension 20180401 5

<h4>Background</h4>Using the data from 56,365 individuals, from 185 countries, and a Nokia Health Wireless blood pressure (BP) monitor, we investigated real-world characteristics of BP variability (BPV).<h4>Methods</h4>All included individuals self-measured and uploaded their BP using Bluetooth at least 20 times over a period of ≥1 month at a frequency and duration of their choosing. In total, 16,904,844 BP measurements were analyzed, with a median of 146 measurements per person (interquartile r ...[more]

PMID: 29365036

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Project description:BackgroundAtrial fibrillation (AF) is associated with increased risks of stroke and heart failure. Electronic health record (EHR)-based AF risk prediction may facilitate efficient deployment of interventions to diagnose or prevent AF altogether.MethodsWe externally validated an electronic health record AF (EHR-AF) score in IBM Explorys Life Sciences, a multi-institutional dataset containing statistically deidentified EHR data for over 21 million individuals (Explorys Dataset). We included individuals with complete AF risk data, ≥2 office visits within 2 years, and no prevalent AF. We compared EHR-AF to existing scores including CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology Atrial Fibrillation), C2HEST (coronary artery disease or chronic obstructive pulmonary disease, hypertension, elderly, systolic heart failure, thyroid disease), and CHA2DS2-VASc. We assessed association between AF risk scores and 5-year incident AF, stroke, and heart failure using Cox proportional hazards modeling, 5-year AF discrimination using C indices, and calibration of predicted AF risk to observed AF incidence.ResultsOf 21 825 853 individuals in the Explorys Dataset, 4 508 180 comprised the analysis (age 62.5, 56.3% female). AF risk scores were strongly associated with 5-year incident AF (hazard ratio per SD increase 1.85 using CHA2DS2-VASc to 2.88 using EHR-AF), stroke (1.61 using C2HEST to 1.92 using CHARGE-AF), and heart failure (1.91 using CHA2DS2-VASc to 2.58 using EHR-AF). EHR-AF (C index, 0.808 [95% CI, 0.807-0.809]) demonstrated favorable AF discrimination compared to CHARGE-AF (0.806 [95% CI, 0.805-0.807]), C2HEST (0.683 [95% CI, 0.682-0.684]), and CHA2DS2-VASc (0.720 [95% CI, 0.719-0.722]). Of the scores, EHR-AF demonstrated the best calibration to incident AF (calibration slope, 1.002 [95% CI, 0.997-1.007]). In subgroup analyses, AF discrimination using EHR-AF was lower in individuals with stroke (C index, 0.696 [95% CI, 0.692-0.700]) and heart failure (0.621 [95% CI, 0.617-0.625]).ConclusionsEHR-AF demonstrates predictive accuracy for incident AF using readily ascertained EHR data. AF risk is associated with incident stroke and heart failure. Use of such risk scores may facilitate decision support and population health management efforts focused on minimizing AF-related morbidity.

Dataset Information

Real World Home Blood Pressure Variability in Over 56,000 Individuals With Nearly 17 Million Measurements.

Publications

Real World Home Blood Pressure Variability in Over 56,000 Individuals With Nearly 17 Million Measurements.

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