Impaired Retinal Vessel Dilation Predicts Mortality in End-Stage Renal Disease.

renal failure retinal vessels vascular biomarker

Journal

Circulation research
ISSN: 1524-4571
Titre abrégé: Circ Res
Pays: United States
ID NLM: 0047103

Informations de publication

Date de publication:
01 Apr 2019
Historique:
entrez: 2 4 2019
pubmed: 2 4 2019
medline: 2 4 2019
Statut: aheadofprint

Résumé

Patients with end-stage renal disease (ESRD) are characterized by increased cardiovascular (CV) and all-cause mortality due to advanced remodeling of the macro- and microvascular beds. The aim of this study was to determine whether retinal microvascular function can predict all-cause and CV mortality in patients with ESRD. In the multicenter prospective observational ISAR (Risk Stratification in End-Stage Renal Disease) study, data on dynamic retinal vessel analysis (DVA) was available in a sub-cohort of 214 dialysis patients (mean age 62.6{plus minus}15.0; 32% female). Microvascular dysfunction was quantified by measuring maximum arteriolar (aMax) and venular dilation (vMax) of retinal vessels in response to flicker light stimulation. During a mean follow-up of 44 months, 55 patients died, including 25 CV and 30 non-CV fatal events. vMax emerged as a strong independent predictor for all-cause mortality. In the Kaplan-Meier analysis, individuals within the lowest tertile of vMax showed significantly shorter three-year survival rates than those within the highest tertile (66.9{plus minus}5.8% vs 92.4{plus minus}3.3%). Uni- and multivariate hazard ratios for all-cause mortality per SD increase of vMax were 0.62 [0.47;0.82] and 0.65[0.47;0.91], respectively. aMax and vMax were able to significantly predict nonfatal and fatal CV events (HR 0.74[0.57;0.97] and 0.78[0.61;0.99], respectively). Our results provide the first evidence that impaired retinal venular dilation is a strong and independent predictor of all-cause mortality in hemodialyzed ESRD patients. DVA provides added value for prediction of all-cause mortality and may be a novel diagnostic tool to optimize CV risk stratification in ESRD and other high-risk CV cohorts. NCT01152892.

Identifiants

pubmed: 30929571
doi: 10.1161/CIRCRESAHA.118.314318
doi:

Banques de données

ClinicalTrials.gov
['NCT01152892']

Types de publication

Journal Article

Langues

eng

Commentaires et corrections

Type : CommentIn

Auteurs

Roman Günthner (R)

Nephrology, Technical University of Munich.

Henner Hanssen (H)

Sport, Exercise and Health, University of Basel.

Christine Hauser (C)

Nephrology, Technical University of Munich.

Susanne Angermann (S)

Nephrology, Technical University of Munich.

Georg Lorenz (G)

Nephrology, Technical University of Munich.

Stephan Kemmner (S)

Nephrology, Technical University of Munich.

Julia Matschkal (J)

Nephrology, Technical University of Munich.

Matthias C Braunisch (MC)

Nephrology, Technical University of Munich.

Claudius Kuechle (C)

Nephrology, Technical University of Munich.

Lutz Renders (L)

Nephrology, Technical University of Munich.

Philipp Moog (P)

Nephrology, Technical University of Munich.

Siegfried Wassertheurer (S)

Health and Environment, AIT Austrian Institute of Technology GmbH.

Marcus Baumann (M)

Nephrology, Technical University of Munich.

Hans-Peter Hammes (HP)

Medical Faculty Mannheim, Heidelberg University.

Christopher C Mayer (CC)

Center for Health and Bioresources, Biomedical Systems, AIT Austrian Institute of Technology GmbH, AUSTRIA.

Bernhard Haller (B)

Institute for Medical Statistics and Epidemiology, Technical University of Munich.

Sarah Stryeck (S)

Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz.

Tobias Madl (T)

Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz.

Javier Carbajo-Lozoya (J)

Nephrology, Technical University of Munich.

Uwe Heemann (U)

Nephrology, Technical University of Munich.

Konstantin Kotliar (K)

Medical Engineering and Technomathematics, FH Aachen University of Applied Sciences.

Christoph Schmaderer (C)

Nephrology, Technical University of Munich.

Classifications MeSH