Background Symmetric dimethylarginine (SDMA) has been shown to be an accurate and precise biomarker for calculating estimated glomerular filtration rate (GFR) in humans, as well as a more sensitive biomarker than serum creatinine concentration (sCr) for assessing renal dysfunction. Objectives The purpose of this retrospective study was to report on the utility of measuring serum SDMA concentrations in cats for detection of chronic kidney disease (CKD) before diagnosis by conventional measurement of sCr. Animals Chronic kidney disease cats (n = 21) included those persistently azotemic for ≥3 months (n = 15), nonazotemic cats with GFR >30% decreased from median GFR of normal cats (n = 4), and nonazotemic cats with calcium oxalate kidney stones (n = 2). Healthy geriatric cats (n = 21) were selected from the same colony. Methods Symmetric dimethylarginine concentrations (liquid chromatography‐mass spectroscopy) and sCr (enzymatic colorimetry) were determined retrospectively from historical data or banked serum samples in azotemic cats or at the time GFR (iohexol clearance) was measured in nonazotemic cats. Results Serum SDMA (r = −0.79) and sCr (r = −0.77) concentrations were significantly correlated to GFR (both P < .0001). Symmetric dimethylarginine became increased before sCr in 17/21 cats (mean, 17.0 months; range, 1.5–48 months). Serum SDMA had higher sensitivity (100%) compared with sCr (17%), but lower specificity (91% versus 100%) and positive predictive value (86% versus 100%). Conclusion and Clinical Importance Using serum SDMA as a biomarker for CKD allows earlier detection of CKD in cats compared with sCr, which may be desirable for initiating renoprotective interventions that slow progression of CKD.

Background: Symmetric dimethylarginine (SDMA) is an accurate and precise biomarker for estimating glomerular filtration rate (GFR) in humans and cats. Serum creatinine (sCr) also correlates with GFR, but has limitations as a biomarker of renal function because nonrenal factors can influence its concentration. Hypothesis: Differences in lean body mass (LBM) influence sCr, but not serum SDMA concentrations. Animals: Forty-one healthy Beagles, mean age 9.9 years (range: 3.1–14.8 years), were studied over a 6 month period. Methods: Serum biomarkers of renal function were measured prospectively at baseline, and 1, 3, and 6 months. SDMA concentrations were measured by liquid chromatography-mass spectroscopy and sCr concentrations by enzymatic colorimetry. Body composition was determined by dual energy x-ray absorptiometry. Results: LBM (P < .001) and age (P = .006) were significant explanatory variables for sCr concentration (R2 = 0.38), but not SDMA concentration. Time on food was the only significant explanatory variable for SDMA concentration (R2 = 0.49). SDMA concentrations decreased across time (P < .001). LBM was affected by sex (males > females; P = .02). Mature adult dogs (<8 years) had greater LBM compared with geriatric dogs (≥8 years; P < .001). Conclusion and Clinical Importance: sCr concentrations, but not SDMA concentrations, are influenced by LBM, which limits sCr utility as a biomarker for monitoring renal function in dogs with decreased LBM. Reductions in LBM can lower sCr concentration and overestimate GFR. SDMA concentrations, but not sCr concentrations were influenced by time on food. SDMA could have clinical advantages over sCr in monitoring response to nutritional interventions.

Background Serum concentrations of symmetric dimethylarginine (SDMA) detected chronic kidney disease (CKD) in cats an average of 17.0 months before serum creatinine (Cr) concentrations increased above the reference interval. Objectives To report on the utility of measuring serum SDMA concentrations in dogs for detection of CKD before diagnosis by measurement of serum Cr. Animals CKD dogs (n = 19) included those persistently azotemic for ≥3 months (n = 5), dogs that were azotemic at the time of death (n = 4), and nonazotemic dogs (n = 10). CKD dogs were compared with healthy control dogs (n = 20). Methods Retrospective study, whereby serum Cr concentrations were determined by enzymatic colorimetry and serum SDMA concentrations were determined by liquid chromatography‐mass spectrometry in dogs with necropsy confirmed CKD. Results Serum SDMA increased before serum Cr in 17 of 19 dogs (mean, 9.8 months; range, 2.2–27.0 months). Duration of elevations in serum SDMA concentrations before the dog developed azotemia (N = 1) or before the dog died (N = 1) was not determined. Serum SDMA and Cr concentrations were linearly related (r = 0.84; P < .001). Serum SDMA (r = −0.80) and serum Cr (r = −0.89) concentrations were significantly related to glomerular filtration rate (both P < .001). Conclusion and Clinical Importance Using serum SDMA as a biomarker for CKD allows earlier detection of kidney dysfunction in dogs than does measurement of serum Cr. Earlier detection might be desirable for initiating renoprotective interventions that slow progression of kidney disease.

Because animal studies are labor intensive, predictive equations are used extensively for calculating metabolizable energy (ME) concentrations of dog and cat pet foods. The objective of this retrospective review of digestibility studies, which were conducted over a 7-year period and based upon Association of American Feed Control Officials (AAFCO) feeding protocols, was to compare the accuracy and precision of equations developed from these animal feeding studies to commonly used predictive equations. Feeding studies in dogs and cats (331 and 227 studies, respectively) showed that equations using modified Atwater factors accurately predict ME concentrations in dog and cat pet foods (r² = 0.97 and 0.98, respectively). The National Research Council (NRC) equations also accurately predicted ME concentrations in pet foods (r² = 0.97 for dog and cat foods). For dogs, these equations resulted in an average estimate of ME within 0.16% and 2.24% of the actual ME measured (equations using modified Atwater factors and NRC equations, respectively); for cats these equations resulted in an average estimate of ME within 1.57% and 1.80% of the actual ME measured. However, better predictions of dietary ME in dog and cat pet foods were achieved using equations based on analysis of gross energy (GE) and new factors for moisture, protein, fat and fiber. When this was done there was less than 0.01% difference between the measured ME and the average predicted ME (r² = 0.99 and 1.00 in dogs and cats, respectively) whereas the absolute value of the difference between measured and predicted was reduced by approximately 50% in dogs and 60% in cats. Stool quality, which was measured by stool score, was influenced positively when dietary protein digestibility was high and fiber digestibility was low. In conclusion, using GE improves predictive equations for ME content of dog and cat pet foods. Nondigestible protein and fiber content of diets predicts stool quality.