Predictive factors for non-diabetic nephropathy in diabetic patients. The utility of renal biopsy

Kidney Biopsy Findings Among Patients With Diabetes in the Cleveland Clinic Kidney Biopsy Epidemiology Project

Rationale & Objectives

Diabetic kidney disease (DKD) is a significant complication of diabetes mellitus, often leading to kidney failure. The absence of well-defined factors prevents distinguishing DKD from non-diabetic kidney disease (non-DKD; alternative primary diagnosis identified on kidney biopsy).

Study Design

Retrospective cohort study.

Setting & Participants

This study assessed 1,242 patients with a history of diabetes from the Cleveland Clinic Kidney Biopsy Epidemiology Project between January 2015 and September 2021.

Exposure

Proteinuria, retinopathy, A1c levels, and estimated glomerular filtration rate.

Outcomes

Non-DKD, defined as an alternative primary diagnosis identified on kidney biopsy other than DKD.

Analytical Approach

Multivariate logistic regression model with backward elimination method.

Results

At the time of biopsy, the median (IQR) age was 63 (53-71 years) years, and 58.8% were men. The median hemoglobin A1c value was 6.7% (6.0%-8.1%), and the median serum creatinine level was 2.5 (1.6-3.9 mg/dL) mg/dL. Among 1,242 patients, 462 (37.2%) had DKD alone, and 780 (62.8%) had non-DKD. Among those with non-DKD, the most common diagnoses were focal segmental glomerulosclerosis (24%), global glomerulosclerosis otherwise not specified (13%), acute tubular necrosis (9%), IgA nephropathy (8%), antineutrophil cytoplasmic antibody vasculitis (7%), and membranous nephropathy (5%). Factors associated with having non-DKD on biopsy were having no retinopathy (vs retinopathy) (adjusted odds ratio [aOR], 3.98; 95% CI, 2.69-5.90), lower A1c levels (<7% vs ≥7%) (aOR, 3.08; 95% CI, 2.16-4.39), higher estimated glomerular filtration rate (≥60 vs <60 mL/min/1.73 m2) (aOR, 2.39; 95% CI 1.28-4.45), microalbuminuria (<300 vs macroalbuminuria ≥300 [mg/g]) (aOR; 2.94; 95% CI, 1.84-4.72), and lower protein-creatinine ratio on random urine sample (<3 vs ≥3 mg/mg) (aOR; 1.80; 95% CI, 1.24-2.61).

Limitations

Selection bias of clinically indicated biopsies, not protocol biopsies, which likely represent a ceiling (maximum) for non-DKD.

Conclusions

Among patients with diabetes undergoing kidney biopsy, 63% have findings in addition to DKD on biopsy. We identified clinical parameters associated with non-DKD in the setting of diabetes. This provides valuable information for clinicians when kidney biopsy should be considered among patients with diabetes to capture all etiologies of proteinuria and kidney dysfunction.

Bacterial infection-related glomerulonephritis in patients with diabetes

AIM

Diabetic patients are prone to infections, thus making them a unique cohort at risk of developing bacterial infection-related glomerulonephritis (IRGN).

METHODS

In total, 1693 adult diabetic patients underwent kidney biopsy between 2005 and 2021 at our tertiary care hospital in South India. Of these, 121 consecutive cases which met criteria of bacterial IRGN were included in this study.

RESULTS

The mean age of the cohort was 53.1 ± 10.1 years and 83/121 (68.5%) were males. Majority (98.3%) had type 2 diabetes for a median duration of 6 (IQR, 2-12) years. The most common sites of infection were skin (47/121, 38.8%) and urinary tract (15/121, 12.4%). Fifty percent (58/121) of patients had underlying advanced diabetic kidney disease (DKD). Isolated C3 deposits (without immunoglobulin) occurred in 66/121 (54.5%) patients predominantly in advanced DKD patients. IgA-dominant glomerulonephritis occurred in only 9/121 (7.4%) patients. Short-course oral steroid was given to 86/121 (71.1%) patients. Steroid related dysglycemia and immunosuppression related infections occurred in 9/61 (14.8%) and 16/61 (26.2%) patients respectively. Of the 90 patients with follow up details >3 months, 46 (51.1%) progressed to kidney failure over a median period of 0.5 (IQR, 0-7.2) months. Patients diagnosed in the latter half of our study period (2013-2021) were older, less commonly presented with fever, had more pronounced hypocomplementemia and severe renal histology predominantly with a 'starry sky' immunofluorescence pattern.

CONCLUSION

Superimposed bacterial IRGN on underlying DKD is associated with poor renal outcomes. Use of short course steroid was associated with significant toxicity.

Serum anti-phospholipase A2 receptor antibody in pathological diagnosis of type 2 diabetes mellitus patients with proteinuria

Patients with diabetes mellitus complicated with proteinuria can be diabetic nephropathy (DN), diabetic complicated with non-diabetic kidney disease (NDKD), or DN with NDKD. Among these membranous nephropathy accounted for a large proportion of DN with NDRD. At present, serum anti-phospholipase A2 receptor (PLA2R) antibody is widely used in the diagnosis and evaluation of therapy in idiopathic membranous nephropathy, our study aimed to investigate the diagnostic significance of anti-PLA2R antibody in type 2 diabetes mellitus (T2DM) patients with proteinuria, providing a method for patients with contraindications of kidney biopsy. Eighty-seven T2DM patients with proteinuria who went on kidney biopsy were divided into the DN group, idiopathic membranous nephropathy (IMN) group, and others group according to their pathological results. In our study, 52.87% and 28.74% of patients were found to have IMN and diabetic nephropathy respectively. The levels of anti-PLA2R antibody, total cholesterol, triglyceride, and estimated glomerular filtration rate (eGFR) were higher in the IMN group, while the prevalence of diabetic retinopathy (DR), systolic blood pressure (SBP) and HbA1c were higher in the DN group. For T2DM patients with proteinuria, anti-PLA2R antibody (AUC = 0.904, 95%CI 0.838-0.970) has a high diagnostic value for IMN. The duration of diabetes (OR = 0.798, P = 0.030), eGFR level (OR = 1.030, P = 0.024), and positive anti-PLA2R antibody (OR = 72.727, P < 0.001) favor the diagnosis of IMN, while DR (OR = 50.234, P < 0.001), SBP (OR = 1.041, P = 0.030), and negative anti-PLA2R antibody (OR = 0.008, P  = 0.001) is beneficial to the diagnosis of DN. Our study found that NDKD is not uncommon in patients with T2DM and proteinuria, and IMN was the main pathological type. Positive anti-PLA2R antibody has a strong accuracy in the diagnosis of IMN in patients with T2DM and proteinuria.

A dynamic nomogram for predicting survival among diabetic patients on maintenance hemodialysis

INTRODUCTION

Among maintenance hemodialysis (MHD) patients, ones with diabetes mellitus (DM) are known to have the worst outcome.

METHODS

A total of 263 MHD patients were included, a dynamic nomogram was established based on multivariable Cox regression analysis.

RESULTS

The median overall survival (OS) time was 46 months. The 1-, 3-, and 5-year OS rates were 90.9%, 70.5% and 53.9%, respectively. The multivariable Cox regression analysis indicated that DM duration, cardiovascular complication, baseline values before starting MHD for estimated glomerular filtration rate and serum phosphate were independent risk factors. The C-index of the dynamic nomogram was 0.745 and the calibration curves showed optimal agreement between the model prediction and actual observation for predicting survival probabilities.

CONCLUSIONS

Our study was the first to establish dynamic nomogram among diabetic MHD patients, the fast and convenient online tool can be used for individual risk estimation at the point of prognosis prediction.

When to Suspect Non-diabetic Kidney Disease in a Diabetic Patient?

The diagnosis of non-diabetic kidney disease (NDKD) in a diabetic patient has significant therapeutic and prognostic implications. There are certain proven clinical predictors of NDKD, which, when present in an appropriate clinical setting, would warrant a kidney biopsy. Herein, we describe four cases of NDKD diagnosed in rather unusual clinical settings, which add to the list of clinical predictors of NDKD. The first case was a “parainfectious glomerulonephritis” diagnosed in a 50-year-old diabetic woman who presented with persistent renal dysfunction despite successful treatment of urinary tract infection. The second case was “membranous nephropathy” diagnosed in a 43-year-old man with long-standing type 1 diabetes, which was associated with other microvascular complications. In this case, the only predictor was disproportionately low serum albumin. The third case was “amyloid light chain (AL) amyloidosis” diagnosed in an elderly diabetic who presented with progressive anasarca over six months. In this case, the only clinical predictor was a disassociation observed between urine dipstick and 24-hour protein estimation. In the fourth case, an elderly diabetic woman without underlying diabetic retinopathy presented with sudden onset nephrotic syndrome. A kidney biopsy was suggestive of diffuse nodular glomerulosclerosis. Immunofluorescence and electron microscopic evaluation were diagnostic of “gamma heavy chain deposition disease.” In all four cases, diagnosis of NDKD led to major therapeutic changes and attainment of renal remission. We have extensively reviewed all major biopsy cohorts of NDKD and have formulated an approach to the diagnosis of NDKD.

Salivary Glycopatterns as Potential Non-Invasive Biomarkers for Diagnosing and Reflecting Severity and Prognosis of Diabetic Nephropathy

Discriminating between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) can help provide more specific treatments. However, there are no ideal biomarkers for their differentiation. Thus, the aim of this study was to identify biomarkers for diagnosing and predicting the progression of DN by investigating different salivary glycopatterns. Lectin microarrays were used to screen different glycopatterns in patients with DN or NDRD. The results were validated by lectin blotting. Logistic regression and artificial neural network analyses were used to construct diagnostic models and were validated in in another cohort. Pearson's correlation analysis, Cox regression, and Kaplan-Meier survival curves were used to analyse the correlation between lectins, and disease severity and progression. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analyses were used to identify corresponding glycoproteins and predict their function. Both the logistic regression model and the artificial neural network model achieved high diagnostic accuracy. The levels of Aleuria aurantia lectin (AAL), Lycopersicon esculentum lectin (LEL), Lens culinaris lectin (LCA), Vicia villosa lectin (VVA), and Narcissus pseudonarcissus lectin (NPA) were significantly correlated with the clinical and pathological parameters related to DN severity. A high level of LCA and a low level of LEL were associated with a higher risk of progression to end-stage renal disease. Glycopatterns in the saliva could be a non-invasive tool for distinguishing between DN and NDRD. The AAL, LEL, LCA, VVA, and NPA levels could reflect the severity of DN, and the LEL and LCA levels could indicate the prognosis of DN.

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.

Characterizing predictors of non-diabetic kidney disease (NDKD) in diabetic patients

BACKGROUND

Diabetic kidney disease (DKD) is the chief cause of renal involvement in diabetic patients. It is primarily a clinical diagnosis. Non-diabetic kidney disease (NDKD) may be missed if they are not biopsied. In this study, we describe the spectrum of NDKD and evaluate the predictors considered for planning a biopsy in diabetic patients with kidney disease.

METHODS

In a retrospective cohort study, diabetic patients who underwent kidney biopsy at our centre between May 2006 and July 2019 were evaluated for NDKD.

RESULTS

321 diabetic patients who underwent kidney biopsy were analyzed. Mean age was 49.3 ± 12.4 years and 71% were males. 75.8% patients had hypertension and 25.2% had diabetic retinopathy. Based on the kidney biopsy, patients were classified as DKD-127 (39.6%), NDKD-179(55.8%) and combined DKD + NDKD-15(4.7%). Overall, the most commonly diagnosed pathology was membranous nephropathy-MN (17%), followed by IgA nephropathy (16.0%) and focal segmental glomerulosclerosis-FSGS (14.9%). In patients with DKD + NDKD, IgA nephropathy (53.3%) was predominant. 165 (51.4%) patients had a diagnosis potentially amenable to a specific therapy. On multivariate analysis, female gender [OR 2.07 (1.08-3.97), p = 0.02], absence of diabetic retinopathy [OR 7.47 (3.71-15), p < 0.001] absence of hypertension [OR 3.17 (1.56-6.45), p = 0.001] and duration of diabetes ≤ 24 months [OR 3.67(1.97-6.84), p < 0.001], were independent predictors for NDKD while the absence of nephrotic range proteinuria [OR 1.73 (0.98-3.05), p 0.05] showed a trend towards significance.

CONCLUSION

Astute use of kidney biopsy can detect potentially treatable NDKD in a large number of diabetic patients with glomerular diseases being the predominant diagnosis. A combination of risk factors needs to be considered to guide the need for kidney biopsy in diabetic patients.

Urinary sediment microRNAs can be used as potential noninvasive biomarkers for diagnosis, reflecting the severity and prognosis of diabetic nephropathy

BACKGROUND

Patients with both diabetes mellitus (DM) and kidney disease could have diabetic nephropathy (DN) or non-diabetic renal disease (NDRD). IgA nephropathy (IgAN) and membranous nephropathy (MN) are the major types of NDRD. No ideal noninvasive diagnostic model exists for differentiating them. Our study sought to construct diagnostic models for these diseases and to identify noninvasive biomarkers that can reflect the severity and prognosis of DN.

METHODS

The diagnostic models were constructed using logistic regression analysis and were validated in an external cohort by receiver operating characteristic curve analysis method. The associations between these microRNAs and disease severity and prognosis were explored using Pearson correlation analysis, Cox regression, Kaplan-Meier survival curves, and log-rank tests.

RESULTS

Our diagnostic models showed that miR-95-3p, miR-185-5p, miR-1246, and miR-631 could serve as simple and noninvasive tools to distinguish patients with DM, DN, DM with IgAN, and DM with MN. The areas under the curve of the diagnostic models for the four diseases were 0.995, 0.863, 0.859, and 0.792, respectively. The miR-95-3p level was positively correlated with the estimated glomerular filtration rate (p < 0.001) but was negatively correlated with serum creatinine (p < 0.01), classes of glomerular lesions (p < 0.05), and scores of interstitial and vascular lesions (p < 0.05). However, the miR-631 level was positively correlated with proteinuria (p < 0.001). A low miR-95-3p level and a high miR-631 level increased the risk of progression to end-stage renal disease (p = 0.002, p = 0.011).

CONCLUSIONS

These four microRNAs could be noninvasive tools for distinguishing patients with DN and NDRD. The levels of miR-95-3p and miR-631 could reflect the severity and prognosis of DN.

Indications for renal biopsy in patients with diabetes. Joint position statement of the Italian Society of Nephrology and the Italian Diabetes Society

AIMS

This joint document of the Italian Society of Nephrology and the Italian Diabetes Society reviews the main indications to perform a renal biopsy in diabetic patients, according to the recommendations of a panel of experts based on all available scientific evidence.

DATA SYNTHESIS

Renal biopsy has a pivotal role in assessing the nature and severity of renal injury in patients with diabetic kidney disease (DKD). The procedure is mandatory in the presence of one of more of the following features: rapid onset or progression of albuminuria or sudden onset of nephrotic syndrome, rapid GFR decline with or without albuminuria, hematuria, active urine sediment, clinical and/or laboratory suspicion of other systemic diseases, and, in patients with type 1 diabetes, short diabetes duration and absence of retinopathy. Indeed, ~40% of diabetic individuals with kidney injury undergoing renal biopsy are affected by a non-diabetic renal disease (NDRD). Furthermore, the histological evaluation of patients with suspected classical diabetic nephropathy allows to define the extent of glomerular, tubulo-interstitial and vascular lesions, thus providing important prognostic (and potentially therapeutic) data. In the future, the indications for renal biopsy might be extended to the definition of the histological lesions underlying the "nonalbuminuric" DKD phenotypes, as well as to the evaluation of the response to treatment with the new anti-hyperglycemic drugs that provide cardiorenal protection.

CONCLUSIONS

In view of the heterogeneous clinical presentation and course of DKD and of the related heterogeneous histopathological patterns, a more extensive use of renal biopsy may be crucial to provide valuable information with important pathogenic, diagnostic, prognostic, and therapeutic implications.

Non-diabetic glomerular lesions in diabetic kidney disease: clinical predictors and outcome in an Eastern European cohort

PURPOSE

Since patients' prognosis depends on the lesions identified by kidney biopsy (KB), we aimed to evaluate predictors of non-diabetic kidney disease (NDKD) in diabetic subjects and to assess their kidney outcome as compared to diabetic nephropathy (DN).

METHODS

180 adults diagnosed by KB with DN (n = 120) or NDKD (n = 60), over a 10 year time-span, were retrospectively included and followed for a mean of 48.1 (95% CI 43.1-53.1) months. Patients with superimposed specific lesions over DN and with steroid-induced diabetes were excluded. The primary endpoint was renal replacement therapy (RRT) initiation. Only subjects who were alive at the end of follow-up (73 with DN and 38 with NDKD) entered the kidney survival analysis.

RESULTS

Membranous nephropathy (9%) was the most common NDKD. Predictors for NDKD were shorter duration of diabetes (OR 0.88; 95% CI 0.81-0.96, p = 0.004), absence of diabetic retinopathy (OR 0.08; 95% CI 0.01-0.44, p = 0.003), and nephrotic syndrome at presentation (OR 3.55; 95% CI 1.39-9.04, p = 0.008). Subjects with NDKD needed RRT later as those with DN [82 (95% CI 67-97.1) vs. 45 (95% CI 34-56.5) months, p = 0.001]. In an adjusted Cox model, biopsy diagnosed DN independently predicted RRT (OR 4.43; 95% CI 1.54-12.7, p = 0.006). Other predictors were lower eGFR, higher proteinuria, and absence of renin-angiotensin inhibitor therapy.

CONCLUSION

As one-third of the investigated subjects had NDKD, and NDKD was associated with a better kidney survival, independently predicted by the type of glomerular lesion, KB appears the most reliable tool to guide therapy and to assess outcome in patients with diabetic kidney disease.

Risk factors for non-diabetic renal disease in diabetic patients

BACKGROUND

Diabetic patients with kidney disease have a high prevalence of non-diabetic renal disease (NDRD). Renal and patient survival regarding the diagnosis of diabetic nephropathy (DN) or NDRD have not been widely studied. The aim of our study is to evaluate the prevalence of NDRD in patients with diabetes and to determine the capacity of clinical and analytical data in the prediction of NDRD. In addition, we will study renal and patient prognosis according to the renal biopsy findings in patients with diabetes.

METHODS

Retrospective multicentre observational study of renal biopsies performed in patients with diabetes from 2002 to 2014.

RESULTS

In total, 832 patients were included: 621 men (74.6%), mean age of 61.7 ± 12.8 years, creatinine was 2.8 ± 2.2 mg/dL and proteinuria 2.7 (interquartile range: 1.2-5.4) g/24 h. About 39.5% (n = 329) of patients had DN, 49.6% (n = 413) NDRD and 10.8% (n = 90) mixed forms. The most frequent NDRD was nephroangiosclerosis (NAS) (n = 87, 9.3%). In the multivariate logistic regression analysis, older age [odds ratio (OR) = 1.03, 95% CI: 1.02-1.05, P < 0.001], microhaematuria (OR = 1.51, 95% CI: 1.03-2.21, P = 0.033) and absence of diabetic retinopathy (DR) (OR = 0.28, 95% CI: 0.19-0.42, P < 0.001) were independently associated with NDRD. Kaplan-Meier analysis showed that patients with DN or mixed forms presented worse renal prognosis than NDRD (P < 0.001) and higher mortality (P = 0.029). In multivariate Cox analyses, older age (P < 0.001), higher serum creatinine (P < 0.001), higher proteinuria (P < 0.001), DR (P = 0.007) and DN (P < 0.001) were independent risk factors for renal replacement therapy. In addition, older age (P < 0.001), peripheral vascular disease (P = 0.002), higher creatinine (P = 0.01) and DN (P = 0.015) were independent risk factors for mortality.

CONCLUSIONS

The most frequent cause of NDRD is NAS. Elderly patients with microhaematuria and the absence of DR are the ones at risk for NDRD. Patients with DN presented worse renal prognosis and higher mortality than those with NDRD. These results suggest that in some patients with diabetes, kidney biopsy may be useful for an accurate renal diagnosis and subsequently treatment and prognosis.

When to perform renal biopsy in patients with type2 diabetes mellitus? Predictive model of non-diabetic renal disease

INTRODUCTION

Diabetic nephropathy (DN) is one of the most frequent complications in patients with diabetes mellitus (DM) and its diagnosis is usually established on clinical grounds. However, kidney involvement in some diabetic patients can be due to other causes, and renal biopsy might be needed to exclude them. The aim of our study was to establish the clinical and analytical data that predict DN and no-diabetic renal disease (NDRD), and to develop a predictive model (score) to confirm or dismiss DN.

MATERIAL AND METHODS

We conducted a transversal, observational and retrospective study, including renal biopsies performed in type2 DM patients, between 2000 and 2018.

RESULTS

Two hundred seven DM patients were included in our study. The mean age was 64.5±10.6 years and 74% were male. DN was found in 126 (61%) of the biopsies and NDRD in 81 (39%). Diabetic retinopathy was presented in 58% of DN patients, but only in 6% of NDRD patients (P<.001). Patients with NDRD were diagnosed of primary glomerulopathies (52%), nephroangiosclerosis (16%), inmunoallergic interstitial nephritis (15%) and vasculitis (8.5%). In the multivariate analysis, retinopathy (OR26.7; 95%CI: 6.8-104.5), chronic ischaemia of lower limbs (OR4,37; 95%CI: 1.33-14.3), insulin therapy (OR3.05; 95%CI: 1.13-8.25), time course of DM ≥10years (OR2.71; 95%CI: 1.1-6.62) and nephrotic range proteinuria (OR2.91; 95%CI: 1.2-7.1) were independent predictors for DN. Microhaematuria defined as ≥10 red blood cells per high-power field (OR0.032; 95%CI: 0.01-0.11) and overweight (OR0.21; 95%CI: 0.08-0.5) were independent predictors of NDRD. According to the predictive model based on the multivariate analysis, all patients with a score >3 had DN and 94% of cases with a score ≤1 had NDRD (score ranked from -6 to 8points).

CONCLUSIONS

NDRD is common in DM patients (39%), being primary glomerulonephritis the most frequent ethology. The absence of retinopathy and the presence of microhematuria are highly suggestive of NDRD. The use of our predictive model could facilitate the indication of performing a renal biopsy in DM patients.

Diagnostic Performance of Retinopathy in the Detection of Diabetic Nephropathy in Type 2 Diabetes: A Systematic Review and Meta-Analysis of 45 Studies

AIMS

To conduct an evidence-based evaluation of diabetic retinopathy (DR) for the diagnosis of diabetic nephropathy (DN) in type 2 diabetics with kidney disease.

METHODS

We systematically searched PubMed, EMBASE, and the Cochrane Library from inception to June 27, 2018, including the reference lists of identified primary studies. A study was included if it (1) used DR as a diagnostic test for DN; and (2) used histological evaluation of renal tissues as the reference standard.

RESULTS

The analysis included 45 studies (4,561 patients). A bivariate analysis yielded a sensitivity of 0.67 (95% CI 0.61-0.74) and a specificity of 0.78 (95% CI 0.73-0.82). The summary receiver operating characteristic curve analysis provided an area under the curve (AUC) of 0.79 (95% CI 0.76-0.83). In a setting of 41% prevalence of DN, the probability of DN would be 68% if the test of DR was positive, and the probability of DN would be 23% if it was negative. In addition, although the mean specificity of proliferative DR for the detection of DN was 0.99 (95% CI 0.45-1.00), the mean sensitivity was 0.34 (95% CI 0.24-0.44), and the AUC was 0.58 (95% CI 0.53-0.62).

CONCLUSIONS

DR is helpful in diagnosing DN in persons with type 2 diabetes and kidney disease, but the severity of DR may not parallel the presence of DN.

Meta-Analysis of Diagnostic Accuracy of Retinopathy for the Detection of Diabetic Kidney Disease in Adults With Type 2 Diabetes

OBJECTIVES

The study aimed to explore whether diabetic retinopathy (DR) could distinguish diabetic kidney disease (DKD) from nondiabetic renal diseases (NDRDs) in patients with type 2 diabetes mellitus and renal disease.

METHODS

We searched PubMed, Embase, Cochrane, MEDLINE and China National Knowledge Internet for articles that enrolled patients with DKD and NDRD. The results were summarized as sensitivity, specificity and the area under the curve of summary receiver operating characteristic curve with their 95% confidence intervals (CIs).

RESULTS

A total of 51 studies that included 4,990 participants were collected for evaluation. The overall pooled sensitivity, specificity and area under the curve with their 95% CIs were 0.67 (95% CI 0.61, 0.73), 0.77 (95% CI 0.72, 0.81) and 0.78 (95% CI 0.75 to 0.82), respectively. If the test for DR is negative, the probability of DKD would decrease to 10%, but if the test for DR is positive, the probability would increase only to 42%. In addition, although the mean specificity of proliferative DR for detection of DKD was 0.98 (95% CI 0.92 to 1.00), the mean sensitivity was 0.25 (95% CI 0.16, 0.35).

CONCLUSIONS

DR may lack adequate evidence either to verify DKD or to exclude NDRD, and the severity of DR may not parallel the presence of DKD.

Clinical and pathological characteristics of non-diabetic renal disease in type 2 diabetes patients

Background

Renal involvement in type 2 diabetes is mainly due to diabetic nephropathy (DN). Nevertheless, a sizable proportion of diabetic patients could actually have nondiabetic renal diseases (NDRDs) or DN plus NDRDs. This study aimed to explore the pathological features of NDRD in diabetic patients and to assess the predictability of diagnosing NDRD (±DN) versus isolated DN on the basis of clinical parameters.

Methods

Medical records of type 2 diabetes patients who underwent renal biopsy under suspicion of NDRD from January 2011 through November 2015 were analyzed retrospectively.

Results

A total of 101 patients were enrolled in this study. The most frequent indication for renal biopsy was recent onset of nephrotic syndrome (41%), followed by rapidly progressive renal failure (29%) and active urinary sediment (21%). On renal biopsy, 51% of patients had isolated DN, 20% had isolated NDRD and 29% had DN plus NDRD. IgA nephropathy was the most common cause of isolated NDRD, whereas acute tubular necrosis (39%) and acute interstitial nephritis (33%) were the main causes of NDRD superimposed on DN. Male gender, short-duration diabetes (<8 years), lower glycated hemoglobin and active urinary sediment (≥10 red and white blood cells per high-power field) were independent predictors of NDRD according to multiple logistic regression analysis.

Conclusions

Judicious use of renal biopsy revealed NDRD (±DN) in nearly half of type 2 diabetes patients with atypical renal presentation, especially in male patients with well-controlled diabetes, those who have had diabetes for a short duration and those with active urinary sediment.

Diagnosis and Management of Type 2 Diabetic Kidney Disease

Type 2 diabetic kidney disease (DKD) is the most common cause of CKD and ESRD worldwide, and carries with it enormous human and societal costs. The goal of this review is to provide an update on the diagnosis and management of DKD based on a comprehensive review of the medical literature. Topics addressed include the evolving presentation of DKD, clinical differentiation of DKD from non-DKD, a state-of-the-art evaluation of current treatment strategies, and promising emerging treatments. It is expected that the review will help clinicians to diagnose and manage patients with DKD.

The large spectrum of renal disease in diabetic patients

The prevalence of diabetic nephropathy (DN) among diabetic patients seems to be overestimated. Recent studies with renal biopsies show that the incidence of non-diabetic nephropathy (NDN) among diabetic patients is higher than expected. Renal impairment of diabetic patients is frequently attributed to DN without meeting the KDOQI criteria or performing renal biopsy to exclude NDN. In this editorial, we update the spectrum of renal disease in diabetic patients and the impact on diagnosis, prognosis and therapy.