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

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 dis...

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Detalles Bibliográficos
Autores principales: Huang, Jui‐Tzu, Cheng, Hao‐Min, Yu, Wen‐Chung, Lin, Yao‐Ping, Sung, Shih‐Hsien, Wang, Jiun‐Jr, Wu, Chung‐Li, Chen, Chen‐Huan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5779003/
https://www.ncbi.nlm.nih.gov/pubmed/29187389
http://dx.doi.org/10.1161/JAHA.117.006701
Descripción
Sumario: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.