Comparison between the EKFC-equation and machine learning models to predict Glomerular Filtration Rate

Autor: Felipe Kenji Nakano, Anna Åkesson, Jasper de Boer, Klest Dedja, Robbe D’hondt, Fateme Nateghi Haredasht, Jonas Björk, Marie Courbebaisse, Lionel Couzi, Natalie Ebert, Björn O. Eriksen, R. Neil Dalton, Laurence Derain-Dubourg, Francois Gaillard, Cyril Garrouste, Anders Grubb, Lola Jacquemont, Magnus Hansson, Nassim Kamar, Christophe Legendre, Karin Littmann, Christophe Mariat, Toralf Melsom, Lionel Rostaing, Andrew D. Rule, Elke Schaeffner, Per-Ola Sundin, Arend Bökenkamp, Ulla Berg, Kajsa Åsling-Monemi, Luciano Selistre, Anders Larsson, Ulf Nyman, Antoine Lanot, Hans Pottel, Pierre Delanaye, Celine Vens
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Druh dokumentu: article
ISSN: 2045-2322
DOI: 10.1038/s41598-024-77618-w
Popis: Abstract In clinical practice, the glomerular filtration rate (GFR), a measurement of kidney functioning, is normally calculated using equations, such as the European Kidney Function Consortium (EKFC) equation. Despite being the most general equation, EKFC, just like previously proposed approaches, can still struggle to achieve satisfactory performance, limiting its clinical applicability. As a possible solution, recently machine learning (ML) has been investigated to improve GFR prediction, nonetheless the literature still lacks a general and multi-center study. Using a dataset with 19,629 patients from 13 cohorts, we investigate if ML can improve GFR prediction in comparison to EKFC. More specifically, we compare diverse ML methods, which were allowed to use age, sex, serum creatinine, cystatin C, height, weight and BMI as features, in internal and external cohorts against EKFC. The results show that the most performing ML method, random forest (RF), and EKFC are very competitive where RF and EKFC achieved respectively P10 and P30 values of 0.45 (95% CI 0.44;0.46) and 0.89 (95% CI 0.88;0.90), whereas EKFC yielded 0.44 (95% CI 0.43; 0.44) and 0.89 (95% CI 0.88; 0.90), considering the entire cohort. Small differences were, however, observed in patients younger than 12 years where RF slightly outperformed EKFC.
Databáze: Directory of Open Access Journals
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