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Am J Hypertens. 2019 Mar 16;32(4):350-364. doi: 10.1093/ajh/hpy185.

Schedules for Self-monitoring Blood Pressure: A Systematic Review.

Author information

1
Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
2
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
3
School of Clinical Sciences, University of Bristol, Bristol, UK.
4
Primary Care Unit, Strangeways Research Laboratory, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
5
Stroke Research Unit. School of Nursing, University of Central Lancashire, Preston, UK.
6
Institute of Clinical Sciences, University of Birmingham, Birmingham, UK.
7
Centre for Guidelines, National Institute for Health and Care Excellence, London, UK.
8
Bodleian Health Care Libraries, Knowledge Centre, Oxford, UK.
9
NIHR UCL Hospitals Biomedical Research Centre, Institute of Cardiovascular Science, University College London, London, UK.

Abstract

BACKGROUND:

Self-monitoring of blood pressure better predicts prognosis than clinic measurement, is popular with patients, and endorsed in hypertension guidelines. However, there is uncertainty over the optimal self-monitoring schedule. We therefore aimed to determine the optimum schedule to predict future cardiovascular events and determine "true" underlying blood pressure.

METHODS:

Six electronic databases were searched from November 2009 (updating a National Institute for Health and Care Excellence [NICE] systematic review) to April 2017. Studies that compared aspects of self-monitoring schedules to either prognosis or reliability/reproducibility in hypertensive adults were included. Data on study and population characteristics, self-monitoring regime, and outcomes were extracted by 2 reviewers independently.

RESULTS:

From 5,164 unique articles identified, 25 met the inclusion criteria. Twelve studies were included from the original NICE review, making a total of 37 studies. Increasing the number of days of measurement improved prognostic power: 72%-91% of the theoretical maximum predictive value (asymptotic maximum hazard ratio) was reached by 3 days and 86%-96% by 7 days. Increasing beyond 3 days of measurement did not result in better correlation with ambulatory monitoring. There was no convincing evidence that the timing or number of readings per day had an effect, or that ignoring the first day's measurement was necessary.

CONCLUSIONS:

Home blood pressure should be measured for 3 days, increased to 7 only when mean blood pressure is close to a diagnostic or treatment threshold. Other aspects of a monitoring schedule can be flexible to facilitate patient uptake of and adherence with self-monitoring.

KEYWORDS:

blood pressure; blood pressure monitoring; hypertension; regression dilution; schedule; self-monitoring; systematic review

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