Evidence map›Paper›PMID 40665145›Full record

Observational studyJournal of nephrology2025

Long-term prediction of mortality by heart rate turbulence in hemodialysis patients and the impact of diabetes mellitus-a longitudinal observational study.

Nora Hannane, Christopher C Mayer, Julia Matschkal, Felix Bormann, Axel Krieter, Jürgen R Braun, Claudius Küchle, Lutz Renders, Roman Günthner, Georg Schmidt and 7 more

Abstract readObservational StudyMulticenter Study
In one paragraph

Observational study in Journal of nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Nora HannaneDepartment of Nephrology, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
Christopher C MayerCenter for Health & Bioresources, Medical Signal Analysis, AIT Austrian Institute of Technology GmbH, Vienna, Austria.
Julia MatschkalDepartment of Nephrology, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
Felix BormannDialysis Center Munich Nord, Munich, Germany.
Axel KrieterNephrocare Munich East, Munich, Germany.
Jürgen R BraunPraxen Dr. Braun, Dialysis Center, Dingolfing, Germany.
Claudius KüchleDepartment of Nephrology, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
Lutz RendersDepartment of Nephrology, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
Roman GünthnerDepartment of Nephrology, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
Georg SchmidtKlinik Für Innere Medizin I, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Munich, Germany.
Alexander MüllerKlinik Für Innere Medizin I, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Munich, Germany.
Siegfried WassertheurerCenter for Health & Bioresources, Medical Signal Analysis, AIT Austrian Institute of Technology GmbH, Vienna, Austria.
Uwe HeemannDepartment of Nephrology, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
Bernhard HallerTUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Institute of AI and Informatics in Medicine, Technical University of Munich, Munich, Germany.
Marek MalikNational Heart and Lung Institute, Imperial College London, London, UK.
Christoph Schmaderer *Department of Nephrology, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
Matthias Christoph Braunisch *Department of Nephrology, TUM School of Medicine and Health, TUM Universitätsklinikum, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany. Matthias.Braunisch@mri.tum.de.ORCID http://orcid.org/0000-0001-8527-0699

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetes-driven impaired autonomic nervous system function might contribute to increased mortality in hemodialysis patients. Our study aimed to validate heart rate turbulence as a long-term predictor of mortality in this vulnerable cohort.

methodsHeart rate turbulence is a non-invasive, 24 h electrocardiography-Holter-based assessment of cardiovascular autonomic responses. Hemodialysis patients of the "rISk strAtification in end-stage Renal disease" (ISAR) study, a prospective, multicenter observational study, were followed up for six years. Mortality hazard, and correlations between clinical characteristics and mortality, were assessed using Cox regression models.

resultsHeart rate turbulence measurement at baseline was available in 290 hemodialysis patients, 99 (34%) with diabetes mellitus. In a multivariable analysis, abnormal heart rate turbulence was associated with a 2.1-fold (95% CI: 1.4-3.2; p < 0.001) increased risk for all-cause and 3.1-fold (95% CI: 1.5-6.2; p = 0.001) increased risk for cardiovascular mortality. The co-occurrence of abnormal heart rate turbulence and diabetes mellitus represented the strongest risk constellation, increasing all-cause mortality risk to a hazard ratio of 5.8 (95% CI: 3.3-10.4; p < 0.001) and cardiovascular mortality risk to 6.1 (95% CI: 2.5-15.1; p < 0.001). This association with mortality risk remained significant after multivariate adjustment. The interaction term between the two comorbidities indicated an approximately additive effect on mortality risk.

conclusionsHeart rate turbulence significantly contributed to the prediction of long-term mortality risk in hemodialysis patients. Diabetes mellitus is a major driver of cardiovascular autonomic dysfunction, which plays a crucial role in mortality among dialysis patients. Heart rate turbulence measurement identifies high-risk patients in the dialysis setting, enhancing precision in risk prediction and stratification, and allowing an opportunity for personalized monitoring and prevention.

Indexed as

Autonomic Nervous SystemDiabetes MellitusHeart RateKidney Failure, ChronicRenal DialysisAgedElectrocardiography, AmbulatoryFemaleHumansLongitudinal StudiesMaleMiddle AgedPredictive Value of TestsProportional Hazards ModelsProspective StudiesRisk AssessmentCardiovascular autonomic dysfunctionDiabetes mellitusHeart rate turbulenceKidney failureProspective multicenter trial

Identifiers

PMID40665145
PMCPMC12630279

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.