title: The relationship between estimated glomerular filtration rate, demographic and anthropometric variables is mediated by muscle mass in non-diabetic patients with chronic kidney disease.
abstract: BACKGROUND
  In this study (the first of two related papers), we report whether the relationship between the demographic and anthropometric variables (DA, i.e. age, gender, height and weight) employed in current creatinin (Cr)-based glomerular filtration rate (GFR) estimation equations and actual GFR is mediated by muscle mass.
  
  
  METHODS
  We studied 77 patients (mean age +/- SD, 65.1 +/- 11.9 years) with chronic kidney disease (mean GFR 45.7 +/- 28.6 ml/min/1.73 m2). Actual GFR was measured by the renal clearance of inulin (GFR(inu)). Appendicular lean mass (ALM) and its index (ALMI) by dual energy X-ray absorptiometry provided markers of muscle mass. Multiple regression analyses identified variables explaining variance in (i) GFR, (ii) ALM and (iii) Cr.
  
  
  RESULTS
  (i) The DA variables used in the abbreviated modification of diet in renal disease (MDRD) equation accounted for only 59.6% (P < 0.001) of the variance in GFR(inu), whilst adding ALMI explained an additional 10.4% variance (P < 0.001). If ALMI was entered first, the relationship between DA variables and GFR(inu) was reduced (for weight) or completely abolished (for age, gender and height). (ii) After inputting all the commonly used DA variables, 17.2% of the variance in ALM was unexplained. (iii) All the DA variables explained only 60.6% (P < 0.001) of the variance in Cr, whilst adding ALM explained an additional 4.2% variance (P < 0.005).
  
  
  CONCLUSIONS
  Muscle mass explained more variance in GFR(inu) than MDRD DA variables and mediated the relationship between GFR(inu) and DA variables. Furthermore, DA variables failed to account for individual differences in muscle mass or Cr. Consequently, there is a need to validate simpler, clinically obtainable measures of muscle mass and determine whether these measures will improve GFR estimation.
authors.affiliation: Health and Exercise Sciences, University of Wales, Bangor, George Building, Bangor, Gwynedd LL57 2PZ, UK. j.h.macdonald@bangor.ac.uk
authors.forename: Jamie Hugo
authors.initials: JH
authors.lastname: Macdonald
authors.forename: Samuele Maria
authors.initials: SM
authors.lastname: Marcora
authors.forename: Mick John
authors.initials: MJ
authors.lastname: Kumwenda
authors.forename: Mahdi
authors.initials: M
authors.lastname: Jibani
authors.forename: Gareth
authors.initials: G
authors.lastname: Roberts
authors.forename: Ruth
authors.initials: R
authors.lastname: Glover
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Barron
authors.forename: Andrew Bruce
authors.initials: AB
authors.lastname: Lemmey
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001827:Body Height; D001835:Body Weight; D002908:Chronic Disease; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007674:Kidney Diseases / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000033:anatomy & histology*; D012044:Regression Analysis; D012737:Sex Factors