Dataset Information

Invasively Measured Aortic Systolic Blood Pressure and Office Systolic Blood Pressure in Cardiovascular Risk Assessment in CKD.

ABSTRACT:

Introduction

Central aortic blood pressure (BP) could be a better risk predictor than brachial BP. This study examined whether invasively measured aortic systolic BP improved outcome prediction beyond risk prediction by conventional cuff-based office systolic BP in patients with and without chronic kidney disease (CKD).

Methods

In a prospective, longitudinal cohort study, aortic and office systolic BPs were registered in patients undergoing elective coronary angiography (CAG). CKD was defined as estimated glomerular filtration rate (eGFR) <60 ml/min per 1.73 m². Multivariable Cox models were used to determine the association with incident myocardial infarction (MI), stroke, and death.

Results

Aortic and office systolic BPs were available in 39,866 patients (mean age: 64 years; 58% males; 64% with hypertension) out of which 6605 (17%) had CKD. During a median follow-up of 7.2 years (interquartile range: 4.6-10.1 years), 1367 strokes (CKD: 353), 1858 MIs (CKD: 446), and 7551 deaths (CKD: 2515) occurred. CKD increased the risk of stroke, MI, and death significantly. Office and aortic systolic BP were both associated with stroke in non-CKD patients (adjusted hazard ratios with 95% confidence interval per 10 mm Hg: 1.08 [1.05-1.12] and 1.06 [1.03-1.09], respectively) and with MI in patients with CKD (adjusted hazard ratios: 1.08 [1.03-1.13] and 1.08 [1.04-1.12], respectively). There was no significant difference between prediction of outcome with office or aortic systolic BP when adjusted models were compared with C-statistics.

Conclusion

Regardless of CKD status, invasively measured central aortic systolic BP does not improve the ability to predict outcome compared with brachial office BP measurement.

SUBMITTER: Peters CD

PROVIDER: S-EPMC10851008 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Publications

Invasively Measured Aortic Systolic Blood Pressure and Office Systolic Blood Pressure in Cardiovascular Risk Assessment in CKD.

Peters Christian D CD Olesen Kevin K W KKW Laugesen Esben E Mæng Michael M Bøtker Hans Erik HE Poulsen Per L PL Buus Niels Henrik NH

Kidney international reports 20231107 2

<h4>Introduction</h4>Central aortic blood pressure (BP) could be a better risk predictor than brachial BP. This study examined whether invasively measured aortic systolic BP improved outcome prediction beyond risk prediction by conventional cuff-based office systolic BP in patients with and without chronic kidney disease (CKD).<h4>Methods</h4>In a prospective, longitudinal cohort study, aortic and office systolic BPs were registered in patients undergoing elective coronary angiography (CAG). CKD ...[more]

PMID: 38344723

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Project description:Rational & objectiveMany drugs, metabolites, and toxins are cleared by the kidneys via tubular secretion. Whether novel endogenous measures of tubular secretion provide information about kidney, cardiovascular, and mortality risk is uncertain.Study designLongitudinal subgroup analysis of clinical trial participants.Setting & participants2,089 Systolic Blood Pressure Intervention Trial participants with estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 at baseline.ExposureSummary score incorporating urine-to-plasma ratios of 10 endogenous secretion markers measured in paired urine and plasma samples at baseline.OutcomeThe primary outcome was longitudinal change in eGFR. Secondary outcomes included chronic kidney disease (CKD) progression (≥50% eGFR decline or incident kidney failure requiring dialysis or kidney transplantation), a cardiovascular disease (CVD) composite (myocardial infarction, acute coronary syndrome, stroke, acute decompensated heart failure, or death from cardiovascular causes), and mortality.Analytical approachLinear mixed-effect models were used to evaluate the association between the secretion score and change in eGFR, and Cox proportional hazards models were used to evaluate associations with CKD progression, CVD, and mortality.ResultsAt baseline, mean age was 73 ± 9 years and eGFR was 46 ± 11 mL/min/1.73 m2. During a median follow-up of 3.3 years, mean change in eGFR was -1.44% per year, and 72 CKD progression events, 272 CVD events, and 144 deaths occurred. In multivariable analyses, lower secretion score was associated with faster eGFR decline and greater risk of CKD progression, CVD, and mortality. After further adjustment for baseline eGFR and albuminuria, each 1-standard deviation lower secretion score was associated with faster eGFR decline (-0.65% per year; 95% CI, -0.84% to -0.46%), but not CKD progression (HR, 1.23; 95% CI, 0.96-1.58), CVD (HR, 1.02; 95% CI, 0.89-1.18), or mortality (HR, 0.90; 95% CI, 0.74-1.09). The secretion score association with eGFR decline appeared stronger in participants with baseline eGFR <45 mL/min/1.73 m2 (P for interaction < 0.001).LimitationsPersons with diabetes and proteinuria >1 g/d were excluded.ConclusionsAmong SPRINT participants with CKD, lower estimated tubular secretion was associated with faster eGFR decline, independent of baseline eGFR and albuminuria, but not with CKD progression, CVD, or mortality.

Project description:Background: The non-invasive estimation of aortic systolic (aoSBP) and pulse pressure (aoPP) is achieved by a great variety of devices, which differ markedly in the: 1) principles of recording (applied technology), 2) arterial recording site, 3) model and mathematical analysis applied to signals, and/or 4) calibration scheme. The most reliable non-invasive procedure to obtain aoSBP and aoPP is not well established. Aim: To evaluate the agreement between aoSBP and aoPP values invasively and non-invasively obtained using different: 1) recording techniques (tonometry, oscilometry/plethysmography, ultrasound), 2) recording sites [radial, brachial (BA) and carotid artery (CCA)], 3) waveform analysis algorithms (e.g., direct analysis of the CCA pulse waveform vs. peripheral waveform analysis using general transfer functions, N-point moving average filters, etc.), 4) calibration schemes (systolic-diastolic calibration vs. methods using BA diastolic and mean blood pressure (bMBP); the latter calculated using different equations vs. measured directly by oscillometry, and 5) different equations to estimate bMBP (i.e., using a form factor of 33% (“033”), 41.2% (“0412”) or 33% corrected for heart rate (“033HR”). Methods: The invasive aortic (aoBP) and brachial pressure (bBP) (catheterization), and the non-invasive aoBP and bBP were simultaneously obtained in 34 subjects. Non-invasive aoBP levels were obtained using different techniques, analysis methods, recording sites, and calibration schemes. Results: 1) Overall, non-invasive approaches yielded lower aoSBP and aoPP levels than those recorded invasively. 2) aoSBP and aoPP determinations based on CCA recordings, followed by BA recordings, were those that yielded values closest to those recorded invasively. 3) The “033HR” and “0412” calibration schemes ensured the lowest mean error, and the “033” method determined aoBP levels furthest from those recorded invasively. 4) Most of the non-invasive approaches considered overestimated and underestimated aoSBP at low (i.e., 80 mmHg) and high (i.e., 180 mmHg) invasive aoSBP values, respectively. 5) The higher the invasively measured aoPP, the higher the level of underestimation provided by the non-invasive methods. Conclusion: The recording method and site, the mathematical method/model used to quantify aoSBP and aoPP, and to calibrate waveforms, are essential when estimating aoBP. Our study strongly emphasizes the need for methodological transparency and consensus for the non-invasive aoBP assessment.

Dataset Information

Invasively Measured Aortic Systolic Blood Pressure and Office Systolic Blood Pressure in Cardiovascular Risk Assessment in CKD.

Introduction

Methods

Results

Conclusion

Publications

Invasively Measured Aortic Systolic Blood Pressure and Office Systolic Blood Pressure in Cardiovascular Risk Assessment in CKD.

Similar Datasets

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