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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, METHODS, RESULTS. Meshes: Adult, Age Factors, Aged, Aged, 80 and over, Body Height, Body Weight, Chronic Disease, Female, Glomerular Filtration Rate, Humans, Kidney Diseases, Male, Middle Aged, Muscle, Skeletal, Regression Analysis, Sex Factors.
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Is the relationship between estimated glomerular filtration rate , demographic and anthropometric variables mediated by muscle mass in non-diabetic patients with chronic kidney disease? Context: 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. 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. (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).
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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. Final Decision: yes