Linear relationship between systolic and diastolic blood pressure monitored over 24 h: assessment and correlates

Gavish, Benjamin; Ben‐Dov, Iddo Z.; Bursztyn, Michael

doi:10.1097/hjh.0b013e3282f25b5a

Cited by 122 publications

(127 citation statements)

References 55 publications

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“…The odds of the LLA being above the median LLA of 65 mm Hg increased by only 26% for each 0.1 increment of the s‐AASI, but this relationship was not significant ( P =0.11, Table 3). As expected,9 the s‐AASI was almost always lower than the AASI (Figure 1B). PP was not significantly related to the LLA, as depicted in Figure 1C (β=0.00, P >0.99).…”

Section: Resultssupporting

confidence: 83%

“…The AASI was defined as 1 minus the regression slope of diastolic over systolic BP 9. If the computed AASI was outside the 0 to 1 range or R 2 of the fit was <0.2, the AASI was not retained for further analysis.…”

Section: Methodsmentioning

confidence: 99%

“…For the s‐AASI, we plotted systolic BP values against diastolic BP values and assessed a linear relationship between the 2 using a symmetric regression procedure that treats both variables in a symmetric way. The resulting symmetric slope was used for the calculation of the s‐AASI 9. The s‐AASI was defined as 1 minus the symmetric regression slope as suggested by Gavish et al 9.…”

Section: Methodsmentioning

confidence: 99%

“…The resulting symmetric slope was used for the calculation of the s‐AASI 9. The s‐AASI was defined as 1 minus the symmetric regression slope as suggested by Gavish et al 9. PP was defined as the mean of the difference between systolic and diastolic BP.…”

Section: Methodsmentioning

confidence: 99%

“…PP, however, while easy to determine clinically, is not a robust measure of vascular stiffness and, by definition, depends directly on blood pressure. To minimize some of these shortcomings, the ambulatory arterial stiffness index (AASI) was introduced in 2006 as a noninvasive marker of arterial stiffness that is less blood pressure dependent 9. The AASI is defined as 1 minus the average slope of diastolic on systolic blood pressure (BP) derived from multiple BP readings that are generally obtained over 24 hours in an ambulatory setting.…”

Section: Introductionmentioning

confidence: 99%

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Relationship Between the Ambulatory Arterial Stiffness Index and the Lower Limit of Cerebral Autoregulation During Cardiac Surgery

Obata

Barodka

Berkowitz

et al. 2018

JAHA

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BackgroundPulse pressure, the ambulatory arterial stiffness index (AASI), and the symmetric AASI are established predictors of adverse cardiovascular outcomes. However, little is known about their relationship to cerebral autoregulation. This study evaluated whether these markers of vascular properties relate to the lower limit of cerebral autoregulation (LLA).Methods and ResultsThe LLA was determined during cardiac surgery with transcranial Doppler ultrasonography in 181 patients. All other variables were calculated from continuous intraoperative readings obtained before cardiopulmonary bypass. The LLA varied directly with the AASI (β=3.12 per 0.1 change in AASI, P<0.001) and to a lesser extent the symmetric AASI (β=2.02 per 0.1 change in symmetric AASI, P≤0.022), while peripheral pulse pressure was not significantly related (β=0.0, P>0.99). Logistic regression revealed that the likelihood of LLA being >65 mm Hg increased by 50% (95% confidence interval, 11%–102%, P=0.008) for every 0.1 increase in the AASI. The AASI was able to predict a LLA above certain thresholds (area under the curve receiver operating characteristic for AASI predicting an LLA >65 mm Hg: 0.60; 95% confidence interval, 0.51%–0.68%, P=0.043). Incorporating additional variables improved the model's predictive ability (area under the curve for AASI predicting a LLA >65 mm Hg: 0.75; 95% confidence interval, 0.68–0.82, P=0.036).ConclusionsThese data indicate that the LLA is related to the mechanical properties of the vasculature as represented by the AASI. The AASI can be used to predict LLA threshold levels during cardiac surgery. It is now possible to link elevations in the LLA with an increased AASI as determined from readily accessible intraoperative variables.

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Section: Resultssupporting

confidence: 83%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Relationship Between the Ambulatory Arterial Stiffness Index and the Lower Limit of Cerebral Autoregulation During Cardiac Surgery

Obata

Barodka

Berkowitz

et al. 2018

JAHA

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Random‐effects meta‐analysis of combined outcomes based on reconstructions of individual patient data

Song

Sun

Redline

et al. 2020

Research Synthesis Methods

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Meta‐analyses of clinical trials typically focus on one outcome at a time. However, treatment decision‐making depends on an overall assessment of outcomes balancing benefit in various domains and potential risks. This calls for meta‐analysis methods for combined outcomes that encompass information from different domains. When individual patient data (IPD) are available from all studies, combined outcomes can be calculated for each individual and standard meta‐analysis methods would apply. However, IPD are usually difficult to obtain. We propose a method to estimate the overall treatment effect for combined outcomes based on first reconstructing pseudo IPD from available summary statistics and then pooling estimates from multiple reconstructed datasets. We focus on combined outcomes constructed from two continuous original outcomes. The reconstruction step requires the specification of the joint distribution of these two original outcomes, including the correlation which is often unknown. For outcomes that are combined in a linear fashion, misspecifications of this correlation affect efficiency, but not consistency, of the resulting treatment effect estimator. For other combined outcomes, an accurate estimate of the correlation is necessary to ensure the consistency of treatment effect estimates. To this end, we propose several ways to estimate this correlation under different data availability scenarios. We evaluate the performance of the proposed methods through simulation studies and apply these to two examples: (a) a meta‐analysis of dipeptidyl peptidase‐4 inhibitors vs control on treating type 2 diabetes; and (b) a meta‐analysis of positive airway pressure therapy vs control on lowering blood pressure among patients with obstructive sleep apnea.

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Estimating within‐study covariances in multivariate meta‐analysis with multiple outcomes

Wei

Higgins

2012

Statistics in Medicine

126

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Multivariate meta-analysis allows the joint synthesis of effect estimates based on multiple outcomes from multiple studies, accounting for the potential correlations among them. However, standard methods for multivariate meta-analysis for multiple outcomes are restricted to problems where the within-study correlation is known or where individual participant data are available. This paper proposes an approach to approximating the within-study covariances based on information about likely correlations between underlying outcomes. We developed methods for both continuous and dichotomous data and for combinations of the two types. An application to a meta-analysis of treatments for stroke illustrates the use of the approximated covariance in multivariate meta-analysis with correlated outcomes. Copyright © 2012 John Wiley & Sons, Ltd.

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Linear relationship between systolic and diastolic blood pressure monitored over 24 h: assessment and correlates

Cited by 122 publications

References 55 publications

Relationship Between the Ambulatory Arterial Stiffness Index and the Lower Limit of Cerebral Autoregulation During Cardiac Surgery

Relationship Between the Ambulatory Arterial Stiffness Index and the Lower Limit of Cerebral Autoregulation During Cardiac Surgery

Random‐effects meta‐analysis of combined outcomes based on reconstructions of individual patient data

Estimating within‐study covariances in multivariate meta‐analysis with multiple outcomes

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