Risk Stratification in End Stage Renal Disease (ESRD) - ISAR Study

NCT01152892 | Unknown

• 1 other identifier: ISAR ESRD 01 2010
• Study Type: observational
• Target: 500
• Locations: 1 country
• Sites: 17

Brief Summary

The purpose of this study is to evaluate the use of non-invasive markers of the autonomic function and micro- and macrocirculation to predict mortality and cardiovascular end points in end-stage renal disease patients. Furthermore we aim at getting new insight into the insufficiently understood pathophysiology leading to excessively high cardiovascular and non-cardiovascular mortality in dialysis patients.

Conditions

End Stage Renal Disease; Chronic Kidney Disease; Cardiovascular Event; Sudden Cardiac Death

Keywords

end stage renal disease; chronic kidney disease; cardiovascular event; sudden cardiac death; autonomic function

Outcome Measures

Primary Outcomes (1)

• Mortality of all causes

  24 month follow up

  24 months

Secondary Outcomes (5)

• Incidence of cardiovascular events

  24 months

• Blood pressure drops within a dialysis session

  24 months

• Incidence of infections requiring antibiotic treatment

  24 months

• Incidence of shunt thrombosis

  24 months

• incidence of death and hospitalization due to infection

  24 months

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

patients with end stage renal disease treated with chronic hemodialysis

You may qualify if:

• Age 18 or older
• End-stage renal disease (ESRD) and receiving maintenance hemodialysis

You may not qualify if:

• Any clinically significant infection.
• pregnancy
• history of malignant disease with a prognostic life expectancy less than 24 months
• missing of written and informed consent

Sponsors & Collaborators

• Technical University of Munich: lead
• Else Kröner Fresenius Foundation: collaborator
• AIT Austrian Institute of Technology GmbH: collaborator
• Ludwig-Maximilians - University of Munich: collaborator
• FH Aachen, University of applied sciences: collaborator

Study Sites (17)

KFH Dialysis Center

Altötting, Bavaria, 84503, Germany

Location

KFH Dialysis Center Dillingen

Dillingen an der Donau, Bavaria, 89407, Germany

Location

Praxen Dr. Braun Dingolfing

Dingolfing, Bavaria, 84130, Germany

Location

KFH Dialysis Center Elsenheimerstrasse

Munich, Bavaria, 80687, Germany

Location

KFH Dialysis Center Munich Schwabing

Munich, Bavaria, 80804, Germany

Location

KFH Dialysis Center Munich Harlaching

Munich, Bavaria, 81545, Germany

Location

KFH Dialysis Center Neuried

Munich, Bavaria, 82061, Germany

Location

Dialysezentrum München Nord

München, Bavaria, 80807, Germany

Location

Dialysezentrum München Solln

München, Bavaria, 81479, Germany

Location

KFH Nierenzentrum Giesinger Bahnhof

München, Bavaria, 81539, Germany

Location

Department of nephrology, Klinikum rechts der Isar

München, Bavaria, 81675, Germany

Location

Nierenzentrum Perlach

München, Bavaria, 81737, Germany

Location

Nierenzentrum Bogenhausen

München, Bavaria, 81925, Germany

Location

KFH Dialysis Center Oberschleißheim

Oberschleißheim, Bavaria, 85764, Germany

Location

KFH Dialysis Center Unterhaching

Unterhaching, Bavaria, 82008, Germany

Location

KFH Dialysis Center Weißenburg

Weißenburg in Bayern, Bavaria, 80804, Germany

Location

Dialyse im Zentrum

München, 80337, Germany

Location

Related Publications (5)

• Bauer A, Kantelhardt JW, Barthel P, Schneider R, Makikallio T, Ulm K, Hnatkova K, Schomig A, Huikuri H, Bunde A, Malik M, Schmidt G. Deceleration capacity of heart rate as a predictor of mortality after myocardial infarction: cohort study. Lancet. 2006 May 20;367(9523):1674-81. doi: 10.1016/S0140-6736(06)68735-7.

  PMID: 16714188 BACKGROUND

• Werfel S, Gunthner R, Hapfelmeier A, Hanssen H, Kotliar K, Heemann U, Schmaderer C. Identification of cardiovascular high-risk groups from dynamic retinal vessel signals using untargeted machine learning. Cardiovasc Res. 2022 Jan 29;118(2):612-621. doi: 10.1093/cvr/cvab040.

  PMID: 33576412 DERIVED

• Gunthner R, Hanssen H, Hauser C, Angermann S, Lorenz G, Kemmner S, Matschkal J, Braunisch MC, Kuechle C, Renders L, Moog P, Wassertheurer S, Baumann M, Hammes HP, Mayer CC, Haller B, Stryeck S, Madl T, Carbajo-Lozoya J, Heemann U, Kotliar K, Schmaderer C. Impaired Retinal Vessel Dilation Predicts Mortality in End-Stage Renal Disease. Circ Res. 2019 Apr 1. doi: 10.1161/CIRCRESAHA.118.314318. Online ahead of print.

  PMID: 30929571 DERIVED

• Hagmair S, Braunisch MC, Bachler M, Schmaderer C, Hasenau AL, Bauer A, Rizas KD, Wassertheurer S, Mayer CC. Implementation and verification of an enhanced algorithm for the automatic computation of RR-interval series derived from 24 h 12-lead ECGs. Physiol Meas. 2017 Jan;38(1):1-14. doi: 10.1088/1361-6579/38/1/1. Epub 2016 Dec 12.

  PMID: 27941217 DERIVED

• Schmaderer C, Tholen S, Hasenau AL, Hauser C, Suttmann Y, Wassertheurer S, Mayer CC, Bauer A, Rizas KD, Kemmner S, Kotliar K, Haller B, Mann J, Renders L, Heemann U, Baumann M. Rationale and study design of the prospective, longitudinal, observational cohort study "rISk strAtification in end-stage renal disease" (ISAR) study. BMC Nephrol. 2016 Oct 26;17(1):161. doi: 10.1186/s12882-016-0374-8.

  PMID: 27784272 DERIVED

Biospecimen

Retention: SAMPLES WITH DNA

Serum

MeSH Terms

Conditions

Kidney Failure, Chronic; Renal Insufficiency, Chronic; Death, Sudden, Cardiac

Condition Hierarchy (Ancestors)

Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Heart Arrest; Heart Diseases; Cardiovascular Diseases; Death, Sudden; Death

Study Officials

• Christoph Schmaderer, M.D., PD

  study chief investigator and head of the nephrological laboratory at the department of nephrology of the Klinikum rechts der Isar of the Technical University of Munich

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PD Dr. med. Christoph Schmaderer

Study Record Dates

• First Submitted: June 28, 2010
• First Posted: June 29, 2010
• Study Start: April 1, 2010
• Primary Completion: May 1, 2019
• Study Completion: May 1, 2020
• Last Updated: January 26, 2016

Record last verified: 2016-01

Locations

DE (17)