Estimation of glomerular filtration rate from skeletal muscle mass. A new equation independent from age, weight, gender, and ethnicity.
Adult
Aged
Aged, 80 and over
Biomarkers
/ blood
Body Composition
Creatinine
/ blood
Electric Impedance
Glomerular Filtration Rate
Healthy Volunteers
Humans
Kidney
/ physiology
Male
Middle Aged
Models, Biological
Muscle, Skeletal
/ physiology
Organ Size
Predictive Value of Tests
Reproducibility of Results
Time Factors
24h urinary creatinine excretion
CKD-EPI equation
Cockcroft–Gault equation
GFR
MDRD Study equation
Skeletal muscle mass
Journal
Nutrition, metabolism, and cardiovascular diseases : NMCD
ISSN: 1590-3729
Titre abrégé: Nutr Metab Cardiovasc Dis
Pays: Netherlands
ID NLM: 9111474
Informations de publication
Date de publication:
27 11 2020
27 11 2020
Historique:
received:
10
02
2020
revised:
02
07
2020
accepted:
17
07
2020
pubmed:
12
9
2020
medline:
15
12
2020
entrez:
11
9
2020
Statut:
ppublish
Résumé
The most used indicator for the renal function is the glomerular filtration rate (GFR). Current used predictive GFR equations were calibrated on patients with chronic kidney disease. Thus, they are not very precise in healthy individuals. The estimation of skeletal muscle mass (SMM) allows the prediction of the daily urinary creatinine excretion (24hUCrE). This study proposes an equation for the estimation of GFR based on SMM (eGFRMuscle) and serum creatinine (SCr). Four hundred sixty-six free-living men underwent a bioelectrical impedance analysis for the evaluation of SMM (kg), a blood withdrawal for the measurement of SCr (mg/dL), and a 24-h urinary collection for the assessment of 24hUCrE (g/24 h). The linear regression analysis between SMM and 24hUCrE and the measurement of SCr allowed developing a predictive equation of eGFRMuscle. The equation predicting eGFRMuscle (ml/min/1.73 m The equation presented in this study results in age, weight, gender, and ethnicity independent because it arises directly from SMM estimation. Therefore, the proposed equation could allow evaluating the GFR also in healthy people with low, average, or high weight, and in older people, regardless of GFR and SCr levels.
Sections du résumé
BACKGROUND AND AIMS
The most used indicator for the renal function is the glomerular filtration rate (GFR). Current used predictive GFR equations were calibrated on patients with chronic kidney disease. Thus, they are not very precise in healthy individuals. The estimation of skeletal muscle mass (SMM) allows the prediction of the daily urinary creatinine excretion (24hUCrE). This study proposes an equation for the estimation of GFR based on SMM (eGFRMuscle) and serum creatinine (SCr).
METHODS AND RESULTS
Four hundred sixty-six free-living men underwent a bioelectrical impedance analysis for the evaluation of SMM (kg), a blood withdrawal for the measurement of SCr (mg/dL), and a 24-h urinary collection for the assessment of 24hUCrE (g/24 h). The linear regression analysis between SMM and 24hUCrE and the measurement of SCr allowed developing a predictive equation of eGFRMuscle. The equation predicting eGFRMuscle (ml/min/1.73 m
CONCLUSIONS
The equation presented in this study results in age, weight, gender, and ethnicity independent because it arises directly from SMM estimation. Therefore, the proposed equation could allow evaluating the GFR also in healthy people with low, average, or high weight, and in older people, regardless of GFR and SCr levels.
Identifiants
pubmed: 32912783
pii: S0939-4753(20)30302-1
doi: 10.1016/j.numecd.2020.07.027
pii:
doi:
Substances chimiques
Biomarkers
0
Creatinine
AYI8EX34EU
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2312-2319Informations de copyright
Copyright © 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest None declared.