Dataset Information

How many measurements are needed to estimate blood pressure variability without loss of prognostic information?

ABSTRACT:

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.

SUBMITTER: Mena LJ

PROVIDER: S-EPMC3848629 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Publications

How many measurements are needed to estimate blood pressure variability without loss of prognostic information?

Mena Luis J LJ Maestre Gladys E GE Hansen Tine W TW Thijs Lutgarde L Liu Yanping Y Boggia José J Li Yan Y Kikuya Masahiro M Björklund-Bodegård Kristina K Ohkubo Takayoshi T Jeppesen Jørgen J Torp-Pedersen Christian C Dolan Eamon E Kuznetsova Tatiana T Stolarz-Skrzypek Katarzyna K Tikhonoff Valérie V Malyutina Sofia S Casiglia Edoardo E Nikitin Yuri Y Lind Lars L Sandoya Edgardo E Kawecka-Jaszcz Kalina K Filipovsky Jan J Lmai Yutaka Y Wang Jiguang J O'Brien Eoin E Staessen Jan A JA

American journal of hypertension 20130816 1

<h4>Background</h4>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.<h4>Methods</h4>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 ...[more]

PMID: 23955605

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Project description:PurposeTo describe variability of intraocular pressure (IOP) measurements within the same eye and between right and left eyes over a 60-month period in participants in the Ocular Hypertension Treatment Study.DesignAnalysis of data from a prospective, randomized clinical trial.ParticipantsEight hundred ten participants randomized to the observation group.MethodsIntraocular pressure measurements were obtained at the baseline visit and every 6 months thereafter. Pearson correlation coefficients were calculated for IOP measurements in the same eye between visits and for IOP measurements between right and left eyes of participants at each visit. Differences in IOP measurements between visits are reported in percent change (>15%, >20%, and >30%) and in millimeters of mercury (<3 mmHg, 3-5 mmHg, and >5 mmHg). The effects of regression to the mean, consistency in time of day, and sequence of IOP measurement of right and left eyes were examined.Main outcome measuresCorrelation of IOP measurements between consecutive 6-month visits.ResultsThe correlation of IOP measurements within the same eye between consecutive visits was r = 0.62, whereas the correlation of IOP measurements between right and left eyes at the same visit was r = 0.72. Thirteen percent of eyes had >20% change in IOP between consecutive visits. Sixty-six percent of eyes had a change in IOP within 3 mmHg, and 10% of eyes had a change in IOP >5 mmHg between visits. Eyes with a higher baseline IOP had a lower IOP at 6 months. There was a stronger correlation of IOP measured within 2 hours of the time of day between visits (r = 0.56) than >2 hours apart (r = 0.39). IOP of the right eye, which was measured first, was 0.3+/-2.8 mmHg higher than the left eye.ConclusionsThe variability of IOP measurements in the same eye between consecutive visits is moderate and is greater than the variability of IOP measurements between right and left eyes at the same visit. Factors affecting the variability of IOP measurement include regression to the mean, time of day, and measurement order. Knowledge of variability in IOP and its measurements may help clinicians establish a more accurate baseline IOP, target IOP, and assessment of medication effect.

Dataset Information

How many measurements are needed to estimate blood pressure variability without loss of prognostic information?

Background

Methods

Results

Conclusions

Publications

How many measurements are needed to estimate blood pressure variability without loss of prognostic information?

Similar Datasets

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