Predicting chronic kidney disease progression with artificial intelligence.

Journal: BMC nephrology
PMID: 38671349

Abstract

BACKGROUND: The use of tools that allow estimation of the probability of progression of chronic kidney disease (CKD) to advanced stages has not yet achieved significant practical importance in clinical setting. This study aimed to develop and validate a machine learning-based model for predicting the need for renal replacement therapy (RRT) and disease progression for patients with stage 3-5 CKD.

Authors

  • Mario A Isaza-Ruget
    Pathology and clinical laboratory. INPAC research group. Clinica Colsanitas. Keralty group, Fundación Universitaria Sanitas, Bogotá, Colombia.
  • Nancy Yomayusa
    Specialist in Internal Medicine and Nephrology, Keralty Global Institute of Clinical Excellence, Unisanitas Translational Research Group, Bogotá, Colombia.
  • Camilo A González
    Specialist in Internal Medicine and Nephrology, Unisanitas Translational Research Group. Renal Unit. Clinica Colsanitas, Bogotá, Colombia.
  • Catherine Alvarado H
    Clinical pathologist. Clinica Colsanitas, Bogotá, Colombia.
  • Fabio A de Oro V
    Internal Medicine resident, Fundación Universitaria Sanitas, Bogotá, Colombia.
  • Andrés Cely
    Health Management Institute, Fundación Universitaria Sanitas, Bogotá, Colombia.
  • Jossie Murcia
    Fundación Universitaria Sanitas, Gerencia y Gestión Sanitaria Research Group, Instituto de Gerencia y Gestión Sanitaria (IGGS), Bogotá, Colombia.
  • Abel Gonzalez-Velez
    Adjunct Physician in Preventive Medicine and Public Health at the Maternal and Child, Insular University Hospital Complex, Las Palmas de Gran Canaria, Spain.
  • Adriana Robayo
    Specialist in Internal Medicine and Nephrology, Institute for Health Technology Assessment (IETS), Bogotá, Colombia.
  • Claudia C Colmenares-Mejía
    Clinical Epidemiology, Research Unit. INPAC research group, Fundación Universitaria Sanitas, Bogotá, Colombia. cccolmenaresm@unisanitas.edu.co.
  • Andrea Castillo
    Evaluation and Knowledge Management. EPS Sanitas, Bogotá, Colombia.
  • María I Conde
    Specialist in Medical Law and Global Health Diplomacy, MSc Public Health, EPS Sanitas, Bogotá, Colombia.

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