Objectives The objective of this paper was to evaluate correlations between kidney biopsy indexes (activity and chronicity) and urinary sediment findings; the secondary objective was to find which components of urinary sediment can discriminate proliferative from other classes of lupus nephritis. Methods Lupus nephritis patients scheduled for a kidney biopsy were included in our study. The morning before the kidney biopsy, we took urine samples from each patient. Receiver operating characteristic (ROC) curves were plotted to determine the area under the curve (AUC) of each test for detecting proliferative lupus nephritis; a classification tree was calculated to select a set of values that best-predicted lupus nephritis classes. Results We included 51 patients, 36 of whom were women (70.6%). Correlations of lupus nephritis activity index with the counts in the urinary sediment of erythrocytes (isomorphic and dysmorphic), acanthocytes, and leukocytes were 0.65 ( p < 0.0001) 0.62 ( p < 0.0001) and 0.22 ( p = 0.1228), respectively. Correlations of lupus nephritis chronicity index with the counts of erythrocytes, acanthocytes, and leukocytes were 0.60 ( p ≤ 0.0001), 0.52 ( p = 0.0001) and 0.17 ( p = 0.2300), respectively. Our classification tree had an accuracy of 84.3%. Conclusions Evaluation of urine sediment reflects lupus nephritis histology.

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra‐fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross‐sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty‐one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty‐eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2‐propenal, 2‐propanol, butane‐ 2,3‐dione and 2‐methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.

Introduction: Lupus nephritis requires antinuclear antibodies as classification criteria. There is a group of patients with nephrotic syndrome and conclusive histopathological findings for lupus nephritis, without classification criteria for systemic lupus erythematosus (SLE) or extrarenal manifestations. These groups of patients have been described as “lupus-like” nephritis or “renal-limited lupus nephritis”. Methods: Renal biopsy with histopathological evaluation with “full-house” immune-reactants in patients with negative antinuclear antibodies. Results: We report four cases with nephrotic syndrome and one with hematuria-proteinuria syndrome: two with impaired glomerular filtration rate and three with preserved renal function; urinary sediment with hematuria without dysmorphia and without extrarenal manifestations for autoimmune disease, negative antinuclear antibodies (ANA) and anti-double stranded DNA (anti-dsDNA); normal C3 and C4 complement levels. Renal biopsy in all cases was consistent for lupus nephritis class V. All patients received treatment as lupus nephritis protocol; only one case received induction with cyclophosphamide and methylprednisolone boluses, the rest received mycophenolic acid and prednisone as induction and maintenance. Two of the cases induced with mycophenolic acid relapsed, requiring cyclophosphamide for 6 months, achieving complete remission. All patients received renin-angiotensin-aldosterone system blockade and hydroxychloroquine. At follow-up, 4 cases still have negative antibodies and are without extrarenal manifestations for SLE classification criteria. The other case, during pregnancy several years after initial diagnosis, had preeclampsia with nephrotic proteinuria and a new determination of positive ANA and anti-dsDNA antibodies, complement levels below normal limits. Conclusion: The follow-up of patients with membranous glomerulopathy must be close; lupus like nephritis may be the first manifestation of the disease.

Few studies have evaluated the glomerular filtration rate (GFR) in patients with systemic lupus erythematosus (SLE). Even though the National Kidney Foundation (NKF) suggests using the equations to estimate GFR, rheumatologists continue using creatinine clearance (CCl). The main objective of our study was the assessment of different equations to estimate GFR in patients with SLE: Simplified MDRD study equation (sMDRD), CCl, Cockcroft Gault (CG), CG calculated with ideal weight (CGi), Mayo Clinic Quadratic (MCQ), and Chronic Kidney Disease Epidemiology Collaboration Equation (CKD-EPI). CKD-EPI was considered as the reference standard, and it was compared with the other equations to evaluate bias, correlation (r), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), percentage of measurement of GFR between 70-130% of GFR measured through CKD-EPI (P30) and to compute the ROC curves. Adequacy of the 24-h urine collection was evaluated. To classify patients into GFR < 60 ml/min/1.73 m(2), the best sensitivity and NVP were obtained with sMDRD: the best PPV and specificity with MCQ. P30 was 99.3% with sMDRD, 77.5% CCl, 91.7% CG, 96.7% CGi, and 77.2% with MCQ. The lowest bias was for sMDRD and the highest for CCl. Only 159 (52.6%) urine collections were considered adequate, and when these patients were re-evaluated, the statistical results improved for CCl. CGi was better in general than CG. CCl should not be considered as an adequate GFR estimation. Ideal weight is better than real weight to calculate GFR through CG in patients with SLE.