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. 2017 Nov 29;6(12):e006701.
doi: 10.1161/JAHA.117.006701.

Value of Excess Pressure Integral for Predicting 15-Year All-Cause and Cardiovascular Mortalities in End-Stage Renal Disease Patients

Jui-Tzu Huang  1 , Hao-Min Cheng  2   3   4 , Wen-Chung Yu  1   5 , Yao-Ping Lin  1   5 , Shih-Hsien Sung  1   5 , Jiun-Jr Wang  6 , Chung-Li Wu  4 , Chen-Huan Chen  2   3   4
Affiliations

Value of Excess Pressure Integral for Predicting 15-Year All-Cause and Cardiovascular Mortalities in End-Stage Renal Disease Patients

Jui-Tzu Huang et al. J Am Heart Assoc. .

Abstract

Background: The excess pressure integral (XSPI), derived from analysis of the arterial pressure curve, may be a significant predictor of cardiovascular events in high-risk patients. We comprehensively investigated the prognostic value of XSPI for predicting long-term mortality in end-stage renal disease patients undergoing regular hemodialysis.

Methods and results: A total of 267 uremic patients (50.2% female; mean age 54.2±14.9 years) receiving regular hemodialysis for more than 6 months were enrolled. Cardiovascular parameters were obtained by echocardiography and applanation tonometry. Calibrated carotid arterial pressure waveforms were analyzed according to the wave-transmission and reservoir-wave theories. Multivariable Cox proportional hazard models were constructed to account for age, sex, diabetes mellitus, albumin, body mass index, and hemodialysis treatment adequacy. Incremental utility of the parameters to risk stratification was assessed by net reclassification improvement. During a median follow-up of 15.3 years, 124 deaths (46.4%) incurred. Baseline XSPI was significantly predictive of all-cause (hazard ratio per 1 SD 1.4, 95% confidence interval 1.15-1.70, P=0.0006) and cardiovascular mortalities (1.47, 1.18-1.84, P=0.0006) after accounting for the covariates. The addition of XSPI to the base prognostic model significantly improved prediction of both all-cause mortality (net reclassification improvement=0.1549, P=0.0012) and cardiovascular mortality (net reclassification improvement=0.1535, P=0.0033). XSPI was superior to carotid-pulse wave velocity, forward and backward wave amplitudes, and left ventricular ejection fraction in consideration of overall independent and incremental prognostics values.

Conclusions: In end-stage renal disease patients undergoing regular hemodialysis, XSPI was significantly predictive of long-term mortality and demonstrated an incremental value to conventional prognostic factors.

Keywords: cardiovascular mortality; hemodynamics; prognosis; reservoir‐pressure analysis; uremia.

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Figures

Figure 1
Figure 1
A, Kaplan‐Meier curves for subgroups with high and low excess pressure integral (XSPI), showing a significant difference in all‐cause mortality in hemodialysis patients who had achieved ideal dry weight. B, Kaplan‐Meier curves for subgroups with high and low XSPI, showing a significant difference in cardiovascular mortality in hemodialysis patients who had achieved ideal dry weight.
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References

    1. United States Renal Data System . 2015 USRDS annual data report: Epidemiology of Kidney Disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2015.
    1. Collins AJ, Foley R, Herzog C, Chavers B, Gilbertson D, Ishani A, Kasiske B, Liu J, Mau LW, McBean M, Murray A, St Peter W, Xue J, Fan Q, Guo H, Li Q, Li S, Peng Y, Qiu Y, Roberts T, Skeans M, Snyder J, Solid C, Wang C, Weinhandl E, Zaun D, Zhang R, Arko C, Chen SC, Dalleska F, Daniels F, Dunning S, Ebben J, Frazier E, Hanzlik C, Johnson R, Sheets D, Wang X, Forrest B, Constantini E, Everson S, Eggers P, Agodoa L. Excerpts from the United States Renal Data System 2007 annual data report. Am J Kidney Dis. 2008;51:S1–S320. - PubMed
    1. Tonelli M, Karumanchi SA, Thadhani R. Epidemiology and mechanisms of uremia‐related cardiovascular disease. Circulation. 2016;133:518–536. - PubMed
    1. Schiffrin EL, Lipman ML, Mann JF. Chronic kidney disease: effects on the cardiovascular system. Circulation. 2007;116:85–97. - PubMed
    1. Zoccali C, Tripepi G, Mallamaci F. Predictors of cardiovascular death in ESRD. Semin Nephrol. 2005;25:358–362. - PubMed

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