Dysmorphic erythrocytes are superior to hematuria for indicating non-diabetic renal disease in type 2 diabetics

Assessment of the Added Value of Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging in Identifying Non-Diabetic Renal Disease in Patients With Type 2 Diabetes Mellitus

BACKGROUND

Identification of non-diabetic renal disease (NDRD) in patients with type 2 diabetes mellitus (T2DM) may help tailor treatment. Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) is a promising tool to evaluate renal function but its potential role in the clinical differentiation between diabetic nephropathy (DN) and NDRD remains unclear.

PURPOSE

To investigate the added role of IVIM-DWI in the differential diagnosis between DN and NDRD in patients with T2DM.

STUDY TYPE

Prospective.

POPULATION

Sixty-three patients with T2DM (ages: 22-69 years, 17 females) confirmed by renal biopsy divided into two subgroups (28 DN and 35 NDRD).

FIELD STRENGTH/SEQUENCE

3 T/ T2 weighted imaging (T2WI), and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI).

ASSESSMENT

The parameters derived from IVIM-DWI (true diffusion coefficient [D], pseudo-diffusion coefficient [D*], and pseudo-diffusion fraction [f]) were calculated for the cortex and medulla, respectively. The clinical indexes related to renal function (eg cystatin C, etc.) and diabetes (eg diabetic retinopathy [DR], fasting blood glucose, etc.) were measured and calculated within 1 week before MRI scanning. The clinical model based on clinical indexes and the IVIM-based model based on IVIM parameters and clinical indexes were established and evaluated, respectively.

STATISTICAL TESTS

Student's t-test; Mann-Whitney U test; Fisher's exact test; Chi-squared test; Intraclass correlation coefficient; Receiver operating characteristic analysis; Hosmer-Lemeshow test; DeLong's test. P < 0.05 was considered statistically significant.

RESULTS

The cortex D*, DR, and cystatin C values were identified as independent predictors of NDRD in multivariable analysis. The IVIM-based model, comprising DR, cystatin C, and cortex D*, significantly outperformed the clinical model containing only DR, and cystatin C (AUC = 0.934, 0.845, respectively).

DATA CONCLUSION

The IVIM parameters, especially the renal cortex D* value, might serve as novel indicators in the differential diagnosis between DN and NDRD in patients with T2DM.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Glomerular Hematuria and the Utility of Urine Microscopy: A Review

Evaluation of hematuria and microscopic examination of urine sediment are commonly used tools by nephrologists in their assessment of glomerular diseases. Certain morphological aspects of urine red blood cells (RBCs) seen by microscopy may help in identifying the source of hematuria as glomerular or not. Recognized signs of glomerular injury are RBC casts or dysmorphic RBCs, in particular acanthocytes (ring-shaped RBCs with protruding blebs). Despite being a highly operator-dependent test, urine sediment examination revealing these signs of glomerular hematuria has demonstrated specificities and positive predictive values ranging between 90%-100% for diagnosing glomerular disease, although sensitivity can be quite variable. Hematuria is a commonly used tool for diagnosing patients with proliferative glomerulonephritis such as IgA nephropathy, antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis, and lupus nephritis, sometimes even as a surrogate for kidney involvement. Studies examining the role for hematuria in monitoring and predicting adverse outcomes in these diseases have shown inconsistent results, possibly due to inconsistent definitions that often fail to consider specific markers of glomerular hematuria such as dysmorphic RBCs, acanthocytes, or RBC casts. A consensus definition of what constitutes glomerular hematuria would help standardize use in future studies and likely improve the diagnostic and prognostic value of hematuria as a marker of glomerulonephritis.

New Diagnostic Model for the Differentiation of Diabetic Nephropathy From Non-Diabetic Nephropathy in Chinese Patients

BACKGROUND

The disease pathology for diabetes mellitus patients with chronic kidney disease (CKD) may be diabetic nephropathy (DN), non-diabetic renal disease (NDRD), or DN combined with NDRD. Considering that the prognosis and treatment of DN and NDRD differ, their differential diagnosis is of significance. Renal pathological biopsy is the gold standard for diagnosing DN and NDRD. However, it is invasive and cannot be implemented in many patients due to contraindications. This article constructed a new noninvasive evaluation model for differentiating DN and NDRD.

METHODS

We retrospectively screened 1,030 patients with type 2 diabetes who has undergone kidney biopsy from January 2005 to March 2017 in a single center. Variables were ranked according to importance, and the machine learning methods (random forest, RF, and support vector machine, SVM) were then used to construct the model. The final model was validated with an external group (338 patients, April 2017-April 2019).

RESULTS

In total, 929 patients were assigned. Ten variables were selected for model development. The areas under the receiver operating characteristic curves (AUCROCs) for the RF and SVM methods were 0.953 and 0.947, respectively. Additionally, 329 patients were analyzed for external validation. The AUCROCs for the external validation of the RF and SVM methods were 0.920 and 0.911, respectively.

CONCLUSION

We successfully constructed a predictive model for DN and NDRD using machine learning methods, which were better than our regression methods.

CLINICAL TRIAL REGISTRATION

ClinicalTrial.gov, NCT03865914.

Evaluation of Renal Microperfusion in Diabetic Patients With Kidney Injury by Contrast-Enhanced Ultrasound

OBJECTIVES

To conduct a quantitative analysis of renal microvascular perfusion in diabetic patients with kidney injury using contrast-enhanced ultrasound (CEUS).

METHODS

A total of 172 patients with type 2 diabetes mellitus and kidney injury were recruited from May 2017 to November 2019. After collection of clinical characteristics, a CEUS examination was performed after injection of the contrast agent SonoVue (Bracco SpA, Milan, Italy). Time-intensity curves and renal perfusion parameters were analyzed. Ultrasound-guided renal biopsy was performed. The patients were divided into a diabetic nephropathy (DN) group and a nondiabetic renal disease (NDRD) group according to renal pathologic results. The discrimination of perfusion parameters between the groups was analyzed statistically with SPSS version 19.0 software (IBM Corporation, Armonk, NY). Receiver operating characteristic curves were used to illustrate the diagnostic performance of indicators.

RESULTS

Ninety-eight patients, including 45 with DN (29 male; mean age ± SD, 57.76 ± 10.47 years) and 53 with NDRD (40 male; mean age, 48.7 ± 13.88 years) were included in this study. The peak enhancement (PE), wash-in the area under the curve (AUC), wash-in rate, wash-in perfusion index, wash-out AUC, wash-in and wash-out AUC, and wash-out rate were significantly different between the groups (P < .05). There were no differences in time-related parameters between the DN and NDRD groups (P > .05). The receiver operating characteristic curve analysis showed that the AUC for PE was 0.727, and PE lower than 7712.426 had diagnostic potential, with sensitivity of 81% and specificity of 40% in discriminating between NDRD and DN.

CONCLUSIONS

The quantification of CEUS parameters can discriminate DN in diabetic patients with kidney injury. The PE and AUC may be feasible parameters.

Kidney Biopsy in Type 2 Diabetic Patients: Critical Reflections on Present Indications and Diagnostic Alternatives

Roughly 3% of patients worldwide with a new diagnosis of type 2 diabetes mellitus (T2DM) already have an overt nephropathy at diagnosis and about 20-30% of the remaining ones develop a complication of this kind later in life. The early identification of kidney disease in diabetic patients is important as it slows its progression, which is important not only because this reduces the need for renal replacement therapy, but also because it decreases the high rate of mortality and morbidity associated with a reduction in kidney function. The increasing prevalence of type 2 diabetes and the consequent greater probability of finding different types of kidney diseases in diabetic patients frequently gives rise to overlapping diagnoses, a definition encompassing the differential diagnosis between diabetic and non-diabetic kidney disease. The issue is made more complex by the acknowledgement of the increasing frequency of presentations of what is termed "diabetic kidney disease" without relevant proteinuria, in particular in T2DM patients. Distinguishing between diabetes related and non-diabetes related forms of kidney disease in diabetic patients is not only a semantic question, as different diseases require different clinical management. However, while the urologic and macrovascular complications of diabetes, as well as overlapping parenchymal damage, can be diagnosed by means of imaging studies, often only a kidney biopsy will make a differential diagnosis possible. In fact, the coexistence of typical diabetic lesions, such as nodular glomerulopathy or glomerulosclerosis, with different glomerular, vascular and tubulo-interstitial alterations has been extensively described, and an analysis of the dominant histological pattern can contribute to determining what therapeutic approach should be adopted. However, due to the high frequency of kidney diseases, and to the fact that T2DM patients are often affected by multiple comorbidities, a kidney biopsy is not generally performed in T2DM patients. What follows is a review aiming to discuss the diagnostic work-up, on the base of clinical, laboratory and imaging criteria, and evaluate the present indications and alternatives to renal biopsy.

Potential Role of the Renal Arterial Resistance Index in the Differential Diagnosis of Diabetic Kidney Disease

AIMS

To investigate the potential role of renal arterial resistance index (RI) in the differential diagnosis between diabetic kidney disease (DKD) and non-diabetic kidney disease (NDKD) and establish a better-quantified differential diagnostic model.

MATERIALS AND METHODS

We consecutively reviewed 469 type 2 diabetes patients who underwent renal biopsy in our center. According to the renal biopsy results, eligible patients were classified into the DKD group and the NDKD group. The diagnostic significance of RI was evaluated by receiver operating characteristic (ROC) curve analysis. Logistic regression analysis was used to search for independent risk factors associated with DKD. Then a novel diagnostic model was established using multivariate logistic regression analysis.

RESULTS

A total of 332 DKD and 137 NDKD patients were enrolled for analysis. RI was significantly higher in the DKD group compared with those in the NDKD group (0.70 vs. 0.63, p< 0.001). The optimum cutoff value of RI for predicting DKD was 0.66 with sensitivity (69.2%) and specificity (80.9%). Diabetic retinopathy, diabetes duration ≥ 60 months, HbA1c ≥ 7.0(%), RI ≥ 0.66, and body mass index showed statistical significance in the multivariate logistic regression analysis. Then, we constructed a new diagnostic model based on these results. And the validation tests indicated that the new model had good sensitivity (81.5%) and specificity (78.6%).

CONCLUSIONS

RI has a potential role in discriminating DKD from NDKD. The RI-based predicting model can be helpful for differential diagnosis of DKD and NDKD.

The association of hematuria on kidney clinicopathologic features and renal outcome in patients with diabetic nephropathy: a biopsy-based study

PURPOSE

To investigate the relationships between hematuria, clinicopathological features and renal outcomes in patients with biopsy-proven diabetic nephropathy (DN).

METHODS

This cohort study included 261 patients with DN. Participants were divided into two groups according to number of red blood cells per high-power field (RBC/hpf) in urine sediment: the hematuria (-) group (≤ 3 RBC/hpf) and the hematuria (+) group (> 3 RBC/hpf). Basic clinical parameters were measured at the time of renal biopsy; relationships between hematuria and clinicopathological features and renal outcomes were analyzed.

RESULTS

Patients in the hematuria (+) group often had overt proteinuria. Interstitial inflammation was more severe in the hematuria (+) group than in the hematuria (-) group. Glomerular arteriolar hyalinosis, interstitial fibrosis and tubular atrophy were comparable between groups. For patients with early DN (eGFR ≥ 60 ml/min/1.73 m²), urinary RBC/hpf at baseline was positively correlated with glomerular classification, interstitial fibrosis/tubular atrophy scores and interstitial inflammation scores. In prognostic analysis, hematuria was associated with a higher risk of progression to end-stage renal disease. Hematuria remained an independent predictor after adjustment for confounding factors such as sex, age, duration of diabetes, serum glucose level, hypertension, cholesterol, eGFR and urine protein excretion, especially in patients with early DN and in male patients.

CONCLUSION

In this study, hematuria was associated with more severe renal pathologic lesions in patients with DN. The presence of hematuria could be an independent predictor of renal outcome in patients with early DN.

Timing of kidney biopsy in type 2 diabetic patients: a stepwise approach

BACKGROUND

Diabetic nephropathy (DN) is the most prevalent cause of renal disease in type 2 diabetic patients and is usually diagnosed clinically. A kidney biopsy is considered when non-diabetic renal disease (NDRD) is suspected, such as rapid progression in renal function impairment and severe proteinuria. Still, there is yet no consensus on the timing of kidney biopsy in type 2 diabetic patients. This study aims to identify markers that can help differentiate between DN and NDRD and guide the decision of kidney biopsy.

METHODS

We retrospectively reviewed patients with type 2 diabetes who received kidney biopsy from 2008 to 2017 at Taipei Veterans General Hospital. Ophthalmologist consultation and outpatient records, diagnosis of kidney biopsy, laboratory data, and clinical characteristics were collected.

RESULTS

This study enrolled 160 type 2 diabetic patients, among which 120 (75%) had isolated DN and 40 (25%) had NDRD ± DN (26 had isolated NDRD, and 14 had NDRD superimposed on DN). In multivariate logistic regression analysis, DM duration (odds ratio [OR]: 0.907; 95% confidence interval [CI]: 0.842-0.977; P = 0.01), diabetic retinopathy (OR: 0.196; 95% CI: 0.061-0.627; P = 0.006), and urinary RBC (OR: 1.068; 95% CI: 1.024-1.115; P = 0.002) were independent predictors of NDRD. In patients with diabetic retinopathy (n = 112, 70%), the presence of proliferative diabetic retinopathy, pan-retinal photocoagulation, and hematuria were factors predicting NDRD; and in patients without diabetic retinopathy (n = 48, 30%), short DM duration and hematuria were factors predicting NDRD.

CONCLUSIONS

Using diabetic retinopathy, DM duration, and hematuria, we developed a 3-step approach to stratify patients into three categories with the different likelihoods of having NDRD. Then different strategies could be taken accordingly. Our stepwise approach is easy to follow and may serve as an appropriate and useful tool to help clinicians in making decisions of kidney biopsy in type 2 DM patients presenting with kidney diseases.

Design and validation of a scoring model for differential diagnosis of diabetic nephropathy and nondiabetic renal diseases in type 2 diabetic patients

BACKGROUND

We aim to design a scoring model for differential diagnosis between diabetic nephropathy (DN) and nondiabetic renal disease (NDRD) in type 2 diabetic patients through a combination of clinical variables.

METHODS

A total of 170 patients with type 2 diabetes who underwent kidney biopsies were included and divided into three groups according to pathological findings: DN group (n = 46), MIX group (DN + NDRD, n = 54), NDRD group (n = 70). Clinical characteristics and laboratory data were collected and compared among groups. Variables with a significant statistical difference between DN and NDRD patients were analyzed by logistic regression to predict the presence of NDRD; then a scoring model was established based on the regression coefficient and further validated in an independent cohort of 67 patients prospectively.

RESULTS

On biopsy, 72.9% of patients had NDRD, and the most common pathological type was membranous nephropathy. The established scoring model for predicting NDRD included five predictors: age, systolic blood pressure, hemoglobin, duration of diabetes, and absence of diabetic retinopathy. The model demonstrated good discrimination and calibration (area under curve [AUC] 0.863, 95% CI, 0.800-0.925; Hosmer-Lemeshow [H-L] P = .062). Furthermore, high prediction accuracy (AUC = 0.900; 95% CI, 0.815-0.985) in the validation cohort proved the stability of the model.

CONCLUSIONS

We present a simple, robust scoring model for predicting the presence of NDRD with high accuracy (0.85) for the first time. This decision support tool provides a noninvasive method for differential diagnosis of DN and NDRD, which may help clinicians assess the risk-benefit ratio of kidney biopsy for type 2 diabetic patients with renal impairment.

Serum levels of immunoglobulin G and complement 3 differentiate non-diabetic renal disease from diabetic nephropathy in patients with type 2 diabetes mellitus

AIMS

Heavy proteinuria caused by non-diabetic renal disease (NDRD) is common in type 2 diabetes mellitus (T2DM). The aim of this study was to investigate specific predictors for NDRD in addition to traditional indicators in T2DM.

METHODS

A total of 341 patients with T2DM who underwent renal biopsy were retrospectively included. Eligible patients were divided into a nephrotic-range group (n = 194) and a non-nephrotic-range group (n = 147) based on proteinuria level. Risk factors for NDRD were evaluated using logistic regression, and the diagnostic implications of these variables were assessed by subgroup.

RESULTS

Multivariate logistic regression indicated that serum IgG level (OR, 0.762; 95% CI, 0.628-0.924; p = 0.006) was an independent predictor of NDRD in the nephrotic-range group. However, in the non-nephrotic-range group, increased C3 level was an independent risk factor for NDRD (OR, 1.313; 95% CI, 1.028-1.678; p = 0.029). In the nephrotic-range group, the optimal cutoff value of IgG for predicting NDRD was 734.0 mg/dl, with 67.8% sensitivity and 74.8% specificity, and IgG ≤ 734.0 mg/dl was the best predictor of NDRD. In the non-nephrotic-range group, the optimal cutoff value of C3 for predicting NDRD was 122.0 mg/dl with low sensitivity (30.9%) but high specificity (97.8%).

CONCLUSIONS

At different levels of proteinuria, reduced IgG and increased C3 levels were independent indicators of NDRD in T2DM. Insights into these factors will help to advance the clinical management of NDRD.

Clinicopathological Features of Nondiabetic Renal Diseases from Different Age Groups: An Observational Cross-sectional Study

Background

Diabetes mellitus (DM) has become the leading cause of chronic kidney disease (CKD). Nondiabetic renal diseases (NDRDs) have different clinicopathological features and prognosis from those of diabetic nephropathy. Our study sought to analyze the clinical and pathological features of NDRDs, in different age groups through a cross-sectional study.

Methods

All patients with type 2 DM at our center who underwent renal biopsy between March 1997 and March 2017 were screened and divided into three groups by age: Group 1 (youth group), 18-44 years old; Group 2 (middle-aged group), 45-59 years old; and Group 3 (elderly group), ≥60 years old. We analyzed the clinicopathological data and risk factors by univariate and multivariate logistic regression for NDRD of the patients to identify the features of NDRD in different age groups.

Results

We included 982 patients in the final analysis. Patients with NDRD accounted for 64.4% of all patients. IgA nephropathy (IgAN) was the most common pathological pattern in young patients with NDRD, accounting for 26.3%. In the middle-aged group, the two most common pathological patterns were IgAN and membranous nephropathy. Membranous nephropathy was the most common pathological pattern in elderly patients with NDRD, accounting for 29.3%. Consistent with pathological features, glomerular hematuria is a risk factor for NDRD in Group 1 (odds ratio [OR], 26.514; 95% confidence interval [CI], 2.503-280.910; P = 0.006). On the other hand, rapidly increasing proteinuria or nephrotic syndrome is a risk factor for NDRD in Group 2 (OR, 5.921; 95% CI, 2.061-17.013; P = 0.001) and Group 3 (OR, 90.409; 95% CI, 6.198-1318.826; P = 0.001).

Conclusions

This single-center study showed that the proportion and composition of NDRD differ among different age groups. Consistent with pathological features, some clinical indices such as hematuria and proteinuria showed different features among different age groups.

Accuracy of hematuria for predicting non-diabetic renal disease in patients with diabetes and kidney disease: A systematic review and meta-analysis

AIMS

To clarify the predictive value of hematuria in patients with diabetes and non-diabetic renal disease (NDRD).

METHODS

The databases of Medline, Embase and the Cochrane Library were searched up to November 22, 2017. The pooled sensitivity, specificity, positive and negative likelihood ratio (PLR, NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic (SROC) curve (AUC) were calculated using a bivariate mixed-effects regression model.

RESULTS

Thirty-eight articles were eligible, of which 35 articles with 4005 patients investigated hematuria. The pooled sensitivity and specificity of hematuria to predict NDRD were 0.42 (95% CI 0.35-0.49) and 0.72 (95% CI 0.64-0.79), respectively. The pooled PLR and NLR were 1.49 (95% CI 1.28-1.75) and 0.81 (95% CI 0.75-0.87), respectively. The DOR was 1.85 (95% CI 1.49-2.30). The pooled AUC was 0.59 (95% CI 0.54-0.63). For dysmorphic erythrocytes, the pooled sensitivity was 0.27 (95% CI 0.23-0.32), while the specificity was 0.94 (95% CI 0.91-0.97). There was heterogeneity among studies (p < 0.001), and no publication bias was identified.

CONCLUSIONS

Type 2 diabetes patients presenting with hematuria are slightly more likely to develop NDRD. Dysmorphic erythrocytes may be more useful than microhematuria in diagnosing for NDRD in type 2 diabetes with proteinuria.

Hematuria as a risk factor for progression of chronic kidney disease and death: findings from the Chronic Renal Insufficiency Cohort (CRIC) Study

BACKGROUND

Hematuria is associated with chronic kidney disease (CKD), but has rarely been examined as a risk factor for CKD progression. We explored whether individuals with hematuria had worse outcomes compared to those without hematuria in the CRIC Study.

METHODS

Participants were a racially and ethnically diverse group of adults (21 to 74 years), with moderate CKD. Presence of hematuria (positive dipstick) from a single urine sample was the primary predictor. Outcomes included a 50% or greater reduction in eGFR from baseline, ESRD, and death, over a median follow-up of 7.3 years, analyzed using Cox Proportional Hazards models. Net reclassification indices (NRI) and C statistics were calculated to evaluate their predictive performance.

RESULTS

Hematuria was observed in 1145 (29%) of a total of 3272 participants at baseline. Individuals with hematuria were more likely to be Hispanic (22% vs. 9.5%, respectively), have diabetes (56% vs. 48%), lower mean eGFR (40.2 vs. 45.3 ml/min/1.73 m2), and higher levels of urinary albumin > 1.0 g/day (36% vs. 10%). In multivariable-adjusted analysis, individuals with hematuria had a greater risk for all outcomes during the first 2 years of follow-up: Halving of eGFR or ESRD (HR Year 1: 1.68, Year 2: 1.36), ESRD (Year 1: 1.71, Year 2: 1.39) and death (Year 1:1.92, Year 2: 1.77), and these associations were attenuated, thereafter. Based on NRIs and C-statistics, no clear improvement in the ability to improve prediction of study outcomes was observed when hematuria was included in multivariable models.

CONCLUSION

In a large adult cohort with CKD, hematuria was associated with a significantly higher risk of CKD progression and death in the first 2 years of follow-up but did not improve risk prediction.

The modern spectrum of biopsy-proven renal disease in Chinese diabetic patients-a retrospective descriptive study

Background

Renal biopsies performed in diabetic patients are increasing and becoming more complex. Comprehensive data on modern spectrum of biopsy-proven renal disease in Chinese diabetic patients are lacking.

Methods

In a nationwide renal biopsy survey including 71,151 native biopsies from 2004 to 2014, diabetic patients were identified according to the clinical diagnosis from referral records. The clinical data were extracted from referral records and pathological reports.

Results

A total of 1,604 diabetic patients, including 61 patients with T1DM, were analyzed in this study. The median age is 51.39 ± 11.37 years. Male patients accounted for 58% of the population. We found that only 44.7% of diabetic patients had the isolated pathological diagnosis of diabetic nephropathy (DN), while 49.1% had non-diabetic renal disease (NDRD) alone, and 6.2% had NDRD superimposed on DN. Nephrotic syndrome (n = 824, 51.4%) was the most common clinical indication for renal biopsy. Among 887 patients with NDRD, membranous nephropathy (n = 357) was the leading diagnosis, followed by IgA nephropathy (n = 179). Hypertensive renal disease (n = 32), tubulointerstitial nephropathy (n = 27) and acute tubular necrosis (n = 16) accounted for 3.5%, 2.9%, 1.7% of the NDRD cases respectively. Nearly a half (49.2%) of patients with T1DM had NDRD.

Discussion

Over 55% diabetic patients with kidney disease were diagnosed as non-diabetic renal disease, among which MN and IgAN were the most common two pathological types.

Clinical predictors differentiating non-diabetic renal diseases from diabetic nephropathy in a large population of type 2 diabetes patients

AIMS

Non-diabetic renal diseases (NDRDs) are associated with better renal outcomes than diabetic nephropathy (DN). This study was conducted to determine the common clinical markers predicting NDRDs in type 2 diabetes patients.

METHODS

Patients with type 2 diabetes mellitus who underwent a renal biopsy were screened. Eligible patients were categorized into two groups: DN group and NDRD group. Patient's clinical characteristics and laboratory data were collected. Logistic regression analysis was performed to identify risk factors for NDRD development, and the diagnostic performance of these variables was evaluated.

RESULTS

The study included 248 patients, 96 (38.71%) in the DN group and 152 (61.29%) in the NDRD group. Patients in the NDRD group had a shorter duration of DM and higher hemoglobin, estimated glomerular filtration rate, and urine osmotic pressure values as well as a higher incidence of glomerular hematuria than patients in the DN group. In the NDRD patients, the most common pathological type was membranous nephropathy (55, 36.18%). Absence of retinopathy (OR, 44.696, 95% CI, 15.91-125.566), glomerular hematuria (OR, 9.587, 95% CI, 2.027-45.333), and DM history ⩽5years (OR, 4.636, 95% CI, 1.721-12.486) were significant and independent risk factors for the development of NDRD (P<0.01). Absence of retinopathy achieved the overall highest diagnostic efficiency with a sensitivity of 92.11% and specificity of 82.29%. Glomerular hematuria had the highest specificity (93.75%).

CONCLUSION

Shorter duration of diabetes (⩽5years), absence of retinopathy, and presence of glomerular hematuria were independent indicators associated with NDRDs, indicating the need for renal biopsy.

Clinicopathological characteristics of non-diabetic renal disease in patients with type 2 diabetes mellitus in a northeastern Chinese medical center: a retrospective analysis of 273 cases

OBJECTIVE

To investigate the clinical and histopathological features of non-diabetic renal disease (NDRD) superimposed on diabetic nephropathy (DN) in northeastern Chinese patients with type 2 diabetes mellitus (T2D), and compare the changes with those of pure DN and isolated NDRD.

METHODS

Single-center retrospective analysis based on medical records of 273 patients (172 men, mean age: 51.1 ± 12.4 years) with T2D who underwent renal biopsy between February 2000 and October 2015. All patients were diagnosed as cases of pure DN, isolated NDRD or NDRD superimposed on DN.

RESULTS

Out of the 273 T2D patients, 68 (24.9 %) had DN, 175 (64.1 %) had NDRD, and 30 (11.0 %) had NDRD superimposed on DN. Idiopathic membranous nephropathy (IMN, 29.7 %) was the most common NDRD followed by IgA nephropathy (IgAN, 22.9 %), and hypertensive renal arteriolar sclerosis was the most common lesion in patients diagnosed as NDRD superimposed on DN. Patients with NDRD had a shorter duration of diabetes and lower frequencies of diabetic retinopathy (DR, 6.9 %) and renal failure (28.0 %), which is consistent with higher estimated glomerular filtration rates (eGFR) and lower systolic blood pressure (SBP). No significant between-group differences were observed with respect to proteinuria and hematuria.

CONCLUSION

Renal biopsy is strongly recommended for T2D patients to distinguish DN, NDRD and NDRD superimposed on DN, especially in patients with no signs of DR. This approach may help in early diagnosis and treatment of NDRD and improve renal outcomes in northeastern Chinese T2D patients.

Dysmorphic erythrocytes are superior to hematuria for indicating non-diabetic renal disease in type 2 diabetics

AIMS/INTRODUCTION

There are sparse and limited studies on erythrocyte morphology in renal biopsy identifying nephropathic patients among type 2 diabetics. The present study sought to clarify the predictive value of dysmorphic erythrocytes in type 2 diabetics with non-diabetic renal disease and influences on hematuria.

MATERIALS AND METHODS

We examined 198 patients with type 2 diabetes who underwent kidney biopsies between 2012 and 2013. Hematuria was defined as >3 or >10 red blood cells per high-power field (RBCs/hpf) in urine sediment. If >80% of the erythrocytes were dysmorphic, glomerular hematuria was diagnosed. Clinical findings and predictive value of dysmorphic erythrocytes were compared between patients with hematuria (n = 19) and those without (n = 61). The potential risk factors for hematuria among diabetic nephropathy patients were also screened.

RESULTS

There was a statistically significant difference between the diabetic nephropathy group and the non-diabetic renal disease group (6.6 vs 16.8%; P = 0.04) when the demarcation point of hematuria was 10 RBCs/hpf. When the definition of hematuria was based on an examination of urinary erythrocyte morphology, a marked difference was seen (3.3 vs 24.8%; P < 0.001). Glomerular hematuria showed high specificity and a positive predictive value (0.97 and 0.94, respectively) in non-diabetic renal disease. A multivariate analysis showed that nephrotic syndrome was significantly associated with hematuria (odds ratio 3.636; P = 0.034).

CONCLUSIONS

Dysmorphic erythrocytes were superior to hematuria for indicating non-diabetic renal disease in type 2 diabetics. Nephrotic syndrome was an independent risk factor for hematuria.