Interactive exploration of adverse events and multimorbidity in CKD.

adverse events chronic kidney disease epidemiology interactive visualization multimorbidity

Journal

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
ISSN: 1460-2385
Titre abrégé: Nephrol Dial Transplant
Pays: England
ID NLM: 8706402

Informations de publication

Date de publication:
25 Apr 2024
Historique:
medline: 26 4 2024
pubmed: 26 4 2024
entrez: 25 4 2024
Statut: aheadofprint

Résumé

Persons with chronic kidney disease (CKD) are at increased risk of adverse events, early mortality, and multimorbidity. A detailed overview of adverse event types and rates from a large CKD cohort under regular nephrological care is missing. We generated an interactive tool to enable exploration of adverse events and their combinations in the prospective, observational German CKD (GCKD) study. The GCKD study enrolled 5217 participants under regular nephrological care with an estimated glomerular filtration rate of 30-60 or >60 mL/min/1.73m2 and an overt proteinuria. Cardio-, cerebro- and peripheral vascular, kidney, infection, and cancer events, as well as deaths were adjudicated following a standard operation procedure. We summarized these time-to-event data points for exploration in interactive graphs within an R shiny app. Multivariable adjusted Cox models for time to first event were fitted. Cumulative incidence functions, Kaplan-Meier curves and intersection plots were used to display main adverse events and their combinations by sex and CKD etiology. Over a median of 6.5 years, 10 271 events occurred in total and 680 participants (13.0%) died while 2947 participants (56.5%) experienced any event. The new publicly available interactive platform enables readers to scrutinize adverse events and their combinations as well as mortality trends as a gateway to better understand multimorbidity in CKD: incident rates per 1000 patient-years varied by event type, CKD etiology, and baseline characteristics. Incidence rates for the most frequent events and their recurrence were 113.6 (cardiovascular), 75.0 (kidney), and 66.0 (infection). Participants with diabetic kidney disease and men were more prone to experiencing events. This comprehensive explorative tool to visualize adverse events (https://gckd.diz.uk-erlangen.de/), their combination, mortality, and multimorbidity among persons with CKD may manifest as a valuable resource for patient care, identification of high-risk groups, health services, and public health policy planning.

Sections du résumé

BACKGROUND AND HYPOTHESIS OBJECTIVE
Persons with chronic kidney disease (CKD) are at increased risk of adverse events, early mortality, and multimorbidity. A detailed overview of adverse event types and rates from a large CKD cohort under regular nephrological care is missing. We generated an interactive tool to enable exploration of adverse events and their combinations in the prospective, observational German CKD (GCKD) study.
METHODS METHODS
The GCKD study enrolled 5217 participants under regular nephrological care with an estimated glomerular filtration rate of 30-60 or >60 mL/min/1.73m2 and an overt proteinuria. Cardio-, cerebro- and peripheral vascular, kidney, infection, and cancer events, as well as deaths were adjudicated following a standard operation procedure. We summarized these time-to-event data points for exploration in interactive graphs within an R shiny app. Multivariable adjusted Cox models for time to first event were fitted. Cumulative incidence functions, Kaplan-Meier curves and intersection plots were used to display main adverse events and their combinations by sex and CKD etiology.
RESULTS RESULTS
Over a median of 6.5 years, 10 271 events occurred in total and 680 participants (13.0%) died while 2947 participants (56.5%) experienced any event. The new publicly available interactive platform enables readers to scrutinize adverse events and their combinations as well as mortality trends as a gateway to better understand multimorbidity in CKD: incident rates per 1000 patient-years varied by event type, CKD etiology, and baseline characteristics. Incidence rates for the most frequent events and their recurrence were 113.6 (cardiovascular), 75.0 (kidney), and 66.0 (infection). Participants with diabetic kidney disease and men were more prone to experiencing events.
CONCLUSION CONCLUSIONS
This comprehensive explorative tool to visualize adverse events (https://gckd.diz.uk-erlangen.de/), their combination, mortality, and multimorbidity among persons with CKD may manifest as a valuable resource for patient care, identification of high-risk groups, health services, and public health policy planning.

Identifiants

pubmed: 38664006
pii: 7658453
doi: 10.1093/ndt/gfae092
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the ERA.

Auteurs

Inga Steinbrenner (I)

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Fruzsina Kotsis (F)

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Robin Kosch (R)

Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover Medical School, Hannover, Germany.
Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany.

Heike Meiselbach (H)

Department of Nephrology and Hypertension, Friedrich-Alexander-University Erlangen-Nürnberg, Germany.

Barbara Bärthlein (B)

Department of Nephrology and Hypertension, Friedrich-Alexander-University Erlangen-Nürnberg, Germany.

Helena Stockmann (H)

Department of Nephrology and Medical Intensive Care, Charité, Berlin, Germany.
Department of Nephrology, University Medical Center Regensburg, Regensburg, Germany.

Jan Lipovsek (J)

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Helena U Zacharias (HU)

Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover Medical School, Hannover, Germany.

Michael Altenbuchinger (M)

Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany.

Thomas Dienemann (T)

Department of Operative Intensive Care, University Hospital Regensburg, Regensburg, Germany.

Monika Wytopil (M)

Institute of Clinical and Molecular Virology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Helena Bächle (H)

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Claudia Sommerer (C)

Department of Nephrology, University Hospital Heidelberg, Renal Center, Heidelberg, Germany.

Stephanie Titze (S)

Department of Nephrology and Hypertension, Friedrich-Alexander-University Erlangen-Nürnberg, Germany.

Anke Weigel (A)

Department of Nephrology and Hypertension, Friedrich-Alexander-University Erlangen-Nürnberg, Germany.

Hansi Weissensteiner (H)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Austria.

Sebastian Schönherr (S)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Austria.

Lukas Forer (L)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Austria.

Nadine S Kurz (NS)

Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany.

Jan Menne (J)

Department of Nephrology, Rheumatology and Vascular Medicine, KRH Klinikum Siloah, Hannover, Germany.

Georg Schlieper (G)

Zentrum für Nieren-, Hochdruck- und Stoffwechselerkrankungen, Hannover, Germany.
Division of Nephrology and Clinical Immunology, University Hospital RWTH Aachen, Germany.

Markus P Schneider (MP)

Department of Nephrology and Hypertension, Friedrich-Alexander-University Erlangen-Nürnberg, Germany.

Elke Schäffner (E)

Institute of Public Health, Charité - Universitätsmedizin Berlin, Germany.

Jan T Kielstein (JT)

Medical Clinic V Nephrology, Rheumatology, Blood Purification - Academic Teaching Hospital Braunschweig, Braunschweig, Germany.

Thomas Sitter (T)

Department of Nephrology and Hypertension, Ludwig-Maximilians University, Munich, Germany.

Jürgen Floege (J)

Division of Nephrology and Clinical Immunology, University Hospital RWTH Aachen, Germany.

Christoph Wanner (C)

Department of Clinical Research and Epidemiology, German Heart Failure Center, University Hospital Würzburg, Germany.

Florian Kronenberg (F)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Austria.

Anna Köttgen (A)

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Martin Busch (M)

Department of Internal Medicine III, Nephrology, University Hospital Jena - Friedrich Schiller University Jena, Jena, Germany.

Vera Krane (V)

Department of Clinical Research and Epidemiology, German Heart Failure Center, University Hospital Würzburg, Germany.

Matthias Schmid (M)

Department of Medical Biometry, Informatics, and Epidemiology, University Hospital Bonn, Bonn, Germany.

Kai-Uwe Eckardt (KU)

Department of Nephrology and Hypertension, Friedrich-Alexander-University Erlangen-Nürnberg, Germany.
Department of Nephrology and Medical Intensive Care, Charité, Berlin, Germany.

Ulla T Schultheiss (UT)

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Classifications MeSH