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

Spectrum of Nondiabetic Kidney Diseases in Patients with Type 2 Diabetes Mellitus Who Underwent Kidney Biopsy in Egypt

INTRODUCTION

Diabetic kidney disease (DKD) affects 30-40% of patients with diabetes. The prevalence of nondiabetic kidney disease (NDKD) in patients with type 2 diabetes mellitus (T2D) in Egypt is unknown. This study aimed to assess the prevalence of NDKD in patients with T2D in Egypt.

METHODS

In this cross-sectional study, we searched the data of patients with T2D who underwent a native kidney biopsy between January 2010 and December 2020 in a kidney pathology laboratory in Egypt.

RESULTS

Of 12,006 patients who underwent kidney biopsy, 677 patients had T2D. NDKD was found in 285 patients (42.7%), DKD in 220 patients (33%), and mixed DKD and NDKD in 162 patients (24.3%). The total prevalence of NDKD was 67% in patients with T2D in our study group. Membranous nephropathy was the most common histopathological disease in patients with NDKD (20.6%) followed by acute tubular injury (ATI) (19.2%) and focal segmental glomerulosclerosis (15.2%). The presence of ATI in a kidney biopsy was associated with a significantly higher mean serum creatine level (p < 0.001). Minimal change disease was associated with a significantly higher proteinuria level (p < 0.001). In binary logistic regression analysis, combining NDKD and mixed groups, the duration of diabetes was a negative predictor of NDKD, with a longer duration decreasing the likelihood of NDKD.

CONCLUSION

NDKD is prevalent among patients with T2D who underwent a kidney biopsy. Kidney biopsy remains the gold standard for diagnosing NDKD in patients with T2D.

Non-diabetic nephropathy in diabetic patients: incidence, HbA1c variability and other predictive factors, and implications

PURPOSE

Diabetes mellitus (DM) is the leading cause of chronic kidney disease (CKD) in the population. In patients with diabetes mellitus, the incidence of non-diabetic nephropathy (NDNP) has been estimated to range from 3% to 69.5%. Personal judgment is frequently employed while deciding whether or not to do a kidney biopsy (KB) on diabetic patients. NDNP alters the prognosis and course of treatment for people with DM. In our study, we examined the incidence of NDNP concurrent with the progression of diabetes mellitus, as well as the laboratory and clinical indicators that could be utilized to forecast it.

METHODS

A retrospective analysis of 76 diabetic patients who underwent KB was conducted. Based on the pathological diagnoses of these patients, they were categorized as DNP (diabetic nephropathy) or NDNP. The definition of HbA1c variability was determined by calculating the mean HbA1c and the average value of the HbA1c measurements, as well as the standard deviation (SD) for each participant.

RESULTS

NDNP was detected in 50% of 76 patients. Among patients with NDNP, 36.8% had focal segmental glomerulosclerosis (FSGS), 23.6% had membranous glomerulonephritis, and 7.8% had IgA nephritis. The NDNP group exhibited significantly higher rates of female gender, absence of diabetic retinopathy, shorter time to diagnosis of diabetes mellitus, chronic kidney disease, and proteinuria, less intensive medication for diabetes mellitus, presence of hematuria and leukociduria, immunological serological marker positivity, and non-HbA1C variability. Risk factors for predicting non-diabetic nephropathy, as determined by multivariate analysis, included female gender, the absence of diabetic retinopathy, non-HbA1c variability and a positive immunological serological test.

CONCLUSION

In this study, a significant number of diabetic patients with chronic kidney disease were diagnosed with NDNP. Identifying these patients allows for treatment of the specific underlying disease. Factors such as the absence of DR, non-HbA1c variability, female gender, and immunological serological test positivity can predict NDNP and guide the clinician's decision on kidney biopsy. Further prospective studies are warranted to validate the efficacy of potential predictive factors like HbA1c variability.

A retrospective cohort study of clinical characteristics and outcomes of type 2 diabetic patients with kidney disease

Background

Type 2 diabetes mellitus (T2DM) with chronic kidney disease (CKD) poses a serious health threat and becomes a new challenge. T2DM patients with CKD fall into three categories, diabetic nephropathy (DN), non-diabetic kidney disease (NDKD), and diabetic nephropathy plus non-diabetic kidney disease (DN + NDKD), according to kidney biopsy. The purpose of our study was to compare the clinical characteristics and kidney outcomes of DN, NDKD, and DN + NDKD patients.

Methods

Data on clinical characteristics, pathological findings, and prognosis were collected from June 2016 to July 2022 in patients with previously diagnosed T2DM and confirmed DN and or NDKD by kidney biopsy at Tongji Hospital in Wuhan, China. The endpoint was defined as kidney transplantation, dialysis, or a twofold increase in serum creatinine.

Results

In our 6-year retrospective cohort research, a total of 268 diabetic patients were admitted and categorized into three groups by kidney biopsy. The 268 patients were assigned to DN (n = 74), NDKD (n = 109), and DN + NDKD (n = 85) groups. The most frequent NDKD was membranous nephropathy (MN) (n = 45,41.28%). Hypertensive nephropathy was the most common subtype in the DN+NDKD group (n = 34,40%). A total of 34 patients (12.7%) reached the endpoint. The difference between the Kaplan-Meier survival curves of the DN, NDKD, and DN + NDKD groups was significant (p < 0.05). Multifactorial analysis showed that increased SBP [HR (95% CI): 1.018(1.002-1.035), p = 0.025], lower Hb [HR(95% CI): 0.979(0.961-0.997), p = 0.023], higher glycosylated hemoglobin [HR(95% CI): 1.338(1.080-1.658), p = 0.008] and reduced serum ALB [HR(95% CI): 0.952(0.910-0.996), p = 0.032] were risk factors for outcomes in the T2DM patients with CKD.

Conclusions

This research based on a Chinese cohort demonstrated that the risk of endpoint events differed among DN, NDKD, and DN+NDKD patients. In T2DM patients with CKD, DN patients displayed worse kidney prognosis than those with NDKD or DN + NDKD. Increased SBP, higher glycosylated hemoglobin, lower Hb, and decreased serum ALB may be correlated with adverse kidney outcomes in T2DM patients.

Developing screening tools to estimate the risk of diabetic kidney disease in patients with type 2 diabetes mellitus

BACKGROUND

Diabetic kidney disease (DKD) is an important microvascular complication of diabetes mellitus (DM).

OBJECTIVE

This study aimed to develop predictive nomograms to estimate the risk of DKD in patients with type 2 diabetes mellitus (T2DM).

METHODS

The medical records of patients with T2DM in our hospital from March 2022 to March 2023 were retrospectively reviewed. The enrolled patients were randomly selected for training and validation sets in a 7:3 ratio. The models for predicting risk of DKD were virtualized by the nomograms using logistic regression analysis.

RESULTS

Among the enrolled 597 patients, 418 were assigned to the training set, while 179 were assigned to the validation set. Using the predictors included glycated hemoglobin A1c (HbA1c), high density lipoprotein cholesterol (HDL-C), presence of diabetic retinopathy (DR) and duration of diabetes (DD), we constructed a full model (model 1) for predicting DKD. And using the laboratory indexes of HbA1c, HDL-C, and cystatin C (Cys-C), we developed a laboratory-based model (model 2). The C-indexes were 0.897 for model 1 and 0.867 for model 2, respectively. The calibration curves demonstrated a good agreement between prediction and observation in the two models. The decision curve analysis (DCA) curves showed that the two models achieved a net benefit across all threshold probabilities.

CONCLUSION

We successfully constructed two prediction models to evaluate the risk of DKD in patients with T2DM. The two models exhibited good predictive performance and could be recommended for DKD screening and early detection.

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.

Analysis of clinical predictors of kidney diseases in type 2 diabetes patients based on machine learning

BACKGROUND

The heterogeneity of Type 2 Diabetes Mellitus (T2DM) complicated with renal diseases has not been fully understood in clinical practice. The purpose of the study was to propose potential predictive factors to identify diabetic kidney disease (DKD), nondiabetic kidney disease (NDKD), and DKD superimposed on NDKD (DKD + NDKD) in T2DM patients noninvasively and accurately.

METHODS

Two hundred forty-one eligible patients confirmed by renal biopsy were enrolled in this retrospective, analytical study. The features composed of clinical and biochemical data prior to renal biopsy were extracted from patients' electronic medical records. Machine learning algorithms were used to distinguish among different kidney diseases pairwise. Feature variables selected in the developed model were evaluated.

RESULTS

Logistic regression model achieved an accuracy of 0.8306 ± 0.0057 for DKD and NDKD classification. Hematocrit, diabetic retinopathy (DR), hematuria, platelet distribution width and history of hypertension were identified as important risk factors. Then SVM model allowed us to differentiate NDKD from DKD + NDKD with accuracy 0.8686 ± 0.052 where hematuria, diabetes duration, international normalized ratio (INR), D-Dimer, high-density lipoprotein cholesterol were the top risk factors. Finally, the logistic regression model indicated that DD-dimer, hematuria, INR, systolic pressure, DR were likely to be predictive factors to identify DKD with DKD + NDKD.

CONCLUSION

Predictive factors were successfully identified among different renal diseases in type 2 diabetes patients via machine learning methods. More attention should be paid on the coagulation factors in the DKD + NDKD patients, which might indicate a hypercoagulable state and an increased risk of thrombosis.

Renoprotective Impacts of Inonotus obliquus Ethanol-Ethyl Acetate Extract on Combined Streptozotocin and Unilateral Nephrectomy-Induced Diabetic Nephropathy in Mice

Diabetes nephropathy (DN) is one of the most common causes of end stage renal disease (ESRD) globally. Medication options to stop or slow the progression of chronic renal disease (CKD) are limited, and patients with DN remain at a high risk of developing renal failure. Inonotus obliquus extracts (IOEs) of Chaga mushroom have been shown to have anti-glycemic, anti-hyperlipidemia, antioxidant, and anti-inflammatory effects against diabetes. In this study, we examined the potential renal protective role of an ethyl acetate layer after water-ethyl acetate separation from Inonotus obliquus ethanol crude extract (EtCE-EA) from Chaga mushrooms in diabetic nephropathy mice after preparation with 1/3 NT + STZ. Our data showed that treatment with EtCE-EA can effectively regulate blood glucose, albumin-creatinine ratio, serum creatinine, and blood urea nitrogen (BUN) levels, and it can improve the renal damage in 1/3 NT + STZ-induced CRF mice with an increase in concentration (100, 300, and 500 mg/kg). In the immunohistochemical staining test, EtCE-EA can effectively reduce the expression of TGF-β and α-SMA after induction according to the increase in the concentration (100 mg/kg, 300 mg/kg), thereby slowing down the degree of kidney damage. Our findings demonstrate that EtCE-EA could provide renal protection in diabetes nephropathy, possibly due to the decreased expression of transforming growth factor-β1 and α-smooth muscle actin.

Heterogeneity in Kidney Histology and Its Clinical Indicators in Type 2 Diabetes Mellitus: A Retrospective Study

The heterogeneous spectrum of kidney disease in diabetes ranges from albuminuric or non-albuminuric diabetic kidney disease to non-diabetic kidney diseases. Presumptive clinical diagnosis of diabetic kidney disease may lead to an erroneous diagnosis.

MATERIAL AND METHOD

We analyzed the clinical profile and kidney biopsy of a total of 66 type 2 diabetes patients. Based on kidney histology, they were divided into-Class I (Diabetic Nephropathy), Class II (Non-diabetic kidney disease), and Class III (Mixed lesion). Demographic data, clinical presentation, and laboratory values were collected and analyzed. This study tried to examine the heterogeneity in kidney disease, its clinical indicator, and the role of kidney biopsy in the diagnosis of kidney disease in diabetes.

RESULTS

Class I consisted of 36(54.5%), class II 17(25.8%), and class III 13(19.7%) patients. The commonest clinical presentation was nephrotic syndrome 33(50%) followed by chronic kidney disease 16(24.4%) and asymptomatic urinary abnormality 8(12.1%). Diabetic retinopathy (DR) was present in 27(41%) cases. DR was significantly higher in the class I patients (p < 0.05). Specificity and positive predictive values of DR for DN were 0.83 and 0.81, respectively (sensitivity 0.61; negative predictive values 0.64). The Association of the duration of diabetes and the level of proteinuria with DN was statistically not significant (p > 0.05). Idiopathic MN (6) and Amyloidosis (2) were the most common isolated NDKD; whereas diffuse proliferative glomerulonephritis (DPGN) (7) was the commonest NDKD in mixed disease. Another common form of NDKD in mixed disease was Thrombotic Microangiopathy (2) and IgA nephropathy (2). NDKD was observed in 5(18.5%) cases in presence of DR. We noted biopsy-proven DN even in 14(35.9%) cases without DR, in 4(50%) cases with microalbuminuria and 14(38.9%) cases with a short duration of diabetes.

CONCLUSION

Almost half (45%) of cases with atypical presentation have non-diabetic kidney disease (NDKD), though even among these cases with atypical presentation diabetic nephropathy (either alone or in mixed form) is commonly seen in 74.2% of cases. DN has been seen in a subset of cases without DR, with microalbuminuria, and with a short duration of diabetes. Clinical indicators were insensitive in distinguishing DN Vs NDKD. Hence, a kidney biopsy may be a potential tool for the accurate diagnosis of kidney disease.

Machine Learning Models to Predict the Risk of Rapidly Progressive Kidney Disease and the Need for Nephrology Referral in Adult Patients with Type 2 Diabetes

Early detection of rapidly progressive kidney disease is key to improving the renal outcome and reducing complications in adult patients with type 2 diabetes mellitus (T2DM). We aimed to construct a 6-month machine learning (ML) predictive model for the risk of rapidly progressive kidney disease and the need for nephrology referral in adult patients with T2DM and an initial estimated glomerular filtration rate (eGFR) ≥ 60 mL/min/1.73 m2. We extracted patients and medical features from the electronic medical records (EMR), and the cohort was divided into a training/validation and testing data set to develop and validate the models on the basis of three algorithms: logistic regression (LR), random forest (RF), and extreme gradient boosting (XGBoost). We also applied an ensemble approach using soft voting classifier to classify the referral group. We used the area under the receiver operating characteristic curve (AUROC), precision, recall, and accuracy as the metrics to evaluate the performance. Shapley additive explanations (SHAP) values were used to evaluate the feature importance. The XGB model had higher accuracy and relatively higher precision in the referral group as compared with the LR and RF models, but LR and RF models had higher recall in the referral group. In general, the ensemble voting classifier had relatively higher accuracy, higher AUROC, and higher recall in the referral group as compared with the other three models. In addition, we found a more specific definition of the target improved the model performance in our study. In conclusion, we built a 6-month ML predictive model for the risk of rapidly progressive kidney disease. Early detection and then nephrology referral may facilitate appropriate management.

Development and validation of a novel nomogram to predict diabetic kidney disease in patients with type 2 diabetic mellitus and proteinuric kidney disease

PURPOSE

Differentiating between diabetic kidney disease (DKD) and non-diabetic kidney disease (NDKD) in patients with Type 2 diabetes mellitus (T2DM) is important due to implications on treatment and prognosis. Clinical methods to accurately distinguish DKD from NDKD are lacking. We aimed to develop and validate a novel nomogram to predict DKD in patients with T2DM and proteinuric kidney disease to guide decision for kidney biopsy.

METHODS

A hundred and two patients with Type 2 Diabetes Mellitus (T2DM) who underwent kidney biopsy from 1st January 2007 to 31st December 2016 were analysed. Univariate and multivariate analyses were performed to identify predictive variables and construct a nomogram. The discriminative ability of the nomogram was assessed by calculating the area under the receiver operating characteristic curve (AUROC), while calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test and calibration plot. Internal validation of the nomogram was assessed using bootstrap resampling.

RESULTS

Duration of T2DM, HbA1c, absence of hematuria, presence of diabetic retinopathy and absence of positive systemic biomarkers were found to be independent predictors of DKD in multivariate analysis and were represented as a nomogram. The nomogram showed excellent discrimination, with a bootstrap-corrected C statistic of 0.886 (95% CI 0.815-0.956). Both the calibration curve and the Hosmer-Lemeshow goodness-of-fit test (p = 0.242) showed high degree of agreement between the prediction and actual outcome, with the bootstrap bias-corrected curve similarly indicating excellent calibration.

CONCLUSIONS

A novel nomogram incorporating 5 clinical parameters is useful in predicting DKD in type 2 diabetes mellitus patients with proteinuric kidney disease.

The analysis of risk factors for diabetic kidney disease progression: a single-centre and cross-sectional experiment in Shanghai

OBJECTIVE

To identify the risk factors for diabetic kidney disease (DKD) development, especially the difference between patients with different courses.

PATIENTS AND METHODS

791 patients were considered to be eligible and were enrolled in the cross-sectional study from Shanghai Tongren Hospital Inpatient Department. 36 variables were initially screened by univariate analysis. The risk factors affecting progression of DKD were determined by logistics regression analysis. Subgroups were grouped according to the course of diabetes disease, and multivariate logistics regression analysis was performed to find out the different risk factors in two subgroups. Finally, the receiver operating characteristics curve is used to verify the result.

RESULTS

The logistic regression model indicated age (OR=1.020, p=0.017, 95% CI 1.004 to 1.040), systolic blood pressure (OR=1.013, p=0.006, 95% CI 1.004 to 1.022), waist circumference (OR=1.021, p=0.015, 95% CI 1.004 to 1.038), white blood cells (WBC, OR=1.185, p=0.001, 95% CI 1.085 to 1.295) and triglycerides (TG, OR=1.110, p=0.047, 95% CI 1.001 to 1.230) were risk factors for DKD, while free triiodothyronine (fT3, OR=0.711, p=0.011, 95% CI 0.547 to 0.926) was a protective factor for DKD in patients with type 2 diabetes mellitus (T2DM). Subgroup analysis revealed that in patients with a short duration of diabetes (<8 years), WBC (OR=1.306, p<0.001, 95% CI 1.157 to 1.475) and TG (OR=1.188, p=0.033, 95% CI 1.014 to 1.393) were risk factors for DKD,fT3 (OR=0.544, p=0.002, 95% CI 0.367 to 0.804) was a protective factor for DKD; whereas for patients with disease course more than 8 years, age (OR=1.026, Pp=0.012, 95%CI=95% CI[ 1.006- to 1.048]) was identified as the only risk factor for DKD and fT3 (OR=0.036, Pp=0.017, 95%CI=95% CI[ 0.439- to 0.922]) was a protective factor for DKD.

CONCLUSION

The focus of attention should especially be on patients with a prolonged course of T2DM, and those with comorbid hypertension and hypertriglyceridaemia waist phenotype. More potential clinical indexes such as thyroid function and inflammatory indicators might be considered as early warning factors for DKD in T2DM. Women should pay attention to controlling inflammation and TGs, and men should strictly control blood pressure. Avoiding abdominal obesity in both men and women will bring great benefits.

Non-diabetic Kidney Disease in Diabetic Population: A Single-Center Study From South India

Introduction: Diabetic kidney disease (DKD) is the commonest cause of chronic kidney disease and end-stage kidney disease worldwide, consequently it has become an important productive implication to the healthcare system. This study was conducted to assess the prevalence of non-DKD (NDKD) in diabetic patients from south India.

Objective: To assess the prevalence of NDKD in type 2 diabetes mellitus patients presenting to a tertiary care hospital from south India and also to analyze clinical clues to establish a diagnosis of NDKD.

Patient and methods: It is a retrospective observational study of analyzing patient characteristics and renal biopsies. All Diabetic patients with a clinical suspicion of non-diabetic kidney disease who underwent renal biopsy during the study period between January 2012 and June 2017 were included. Based on the biopsy findings, the patients were classified into three groups (isolated diabetic nephropathy, isolated NDKD, and NDKD with underlying diabetic nephropathy) and patients’ characteristics were compared between the groups for analysis.

Results: A total of 236 renal biopsies were analyzed for the study. Of that, 114 had features of DKD, 78 NDKD with diabetic nephropathy (DN) and 44 had isolated NDKD. Acute interstitial nephritis was the most common cause of NDKD.

Conclusion: From the current study, the long duration of diabetes mellitus beyond five years and hypertension beyond two years reasonably predict DKD.

Advancements in nanomedicines for the detection and treatment of diabetic kidney disease

In the diabetic kidneys, morbidities such as accelerated ageing, hypertension and hyperglycaemia create a pro-inflammatory microenvironment characterised by extensive fibrogenesis. Radiological techniques are not yet optimised generating inconsistent and non-reproducible data. The gold standard procedure to assess renal fibrosis is kidney biopsy, followed by histopathological assessment. However, this method is risky, invasive, subjective and examines less than 0.01% of kidney tissue resulting in diagnostic errors. As such, less than 10% of patients undergo kidney biopsy, limiting the accuracy of the current diabetic kidney disease (DKD) staging method. Standard treatments suppress the renin-angiotensin system to control hypertension and use of pharmaceuticals aimed at controlling diabetes have shown promise but can cause hypoglycaemia, diuresis and malnutrition as a result of low caloric intake. New approaches to both diagnosis and treatment are required. Nanoparticles (NPs) are an attractive candidate for managing DKD due to their ability to act as theranostic tools that can carry drugs and enhance image contrast. NP-based point-of-care systems can provide physiological information previously considered unattainable and provide control over the rate and location of drug release. Here we discuss the use of nanotechnology in renal disease, its application to both the treatment and diagnosis of DKD. Finally, we propose a new method of NP-based DKD classification that overcomes the current systems limitations.

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.

Prevalence of Nondiabetic Renal Disease in Patients with Type 2 Diabetes Mellitus with Clinicopathological Correlation: A Study from a Tertiary Care Center of Assam, India

Diabetes mellitus is the most common cause of chronic kidney disease worldwide. The prevalence of nondiabetic renal disease (NDRD) among patients with type 2 diabetes mellitus (T2DM) varies widely. This study aimed to evaluate the renal biopsies performed on type 2 diabetic patients for suspicion of NDRD and to correlate clinicopathological findings. All T2DM patients aged > 18 years were included in this study, who had renal biopsy performed for the following reasons: recent-onset nephrotic syndrome, unexplained rapid deterioration of renal function, proteinuria not accompanied by retinopathy, and unexplained hematuria. Renal biopsy was analyzed by light microscopy and immunofluorescence. Based on biopsy findings, the patients were grouped into three: (i) isolated NDRD, (ii) NDRD ± diabetic nephropathy (DN), and (iii) isolated DN. A total of 140 patients were enrolled in this study. Recent-onset nephrotic syndrome was the most common indication for biopsy, followed by the presence of active urine sediment. Forty-two percent of the patients had isolated DN, while NDRD was seen in 34% and DN ± NDRD in 24%. Focal segmental glomerulosclerosis (FSGS) and IgA nephropathy were the most common causes of isolated NDRD, while chronic tubulointerstitial nephritis (CTIN) was common in NDRD plus DN. Short duration of diabetes, absence of diabetic retinopathy, and lower glycated hemoglobin were predictive of NDRD. NDRD was seen in 58% of the patients with atypical presentations. FSGS and CTIN were common in NDRD diseases. Judicious use of biopsy in diabetic patients with atypical presentation may help in the diagnosis of NDRD.

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.

Anemia in Diabetic Patients Reflects Severe Tubulointerstitial Injury and Aids in Clinically Predicting a Diagnosis of Diabetic Nephropathy

Objective A kidney biopsy is generally performed in diabetic patients to discriminate between diabetic nephropathy (DN) and non-diabetic kidney disease (NDKD) and to provide more specific treatments. This study investigated the impact of anemia on the renal pathology and the clinical course in patients who underwent a kidney biopsy. Methods We reviewed 81 patients with type 2 diabetes who underwent a percutaneous kidney biopsy. Patients were classified into two groups: isolated DN (DN group, n=30) and NDKD alone or concurrent DN (NDKD group, n=51) groups. The laboratory and pathological findings and clinical courses were investigated. Results In the NDKD group, membranous nephropathy was the most common finding (23.5%), followed by IgA nephropathy (17.6%) and crescentic glomerulonephritis (13.7%). In the logistic regression analysis, the absence of severe hematuria and presence of anemia were significantly associated with a diagnosis of DN. Akaike's information criterion (AIC) and net reclassification improvement (NRI) analyses revealed improved predictive performance by adding anemia to the conventional factors (AIC 100.152 to 91.844; NRI 27.0%). The tissues of patients in the DN group demonstrated more severe interstitial fibrosis and tubular atrophy (IF/TA) than those in the NDKD group (p<0.05) regardless of the rate of global glomerulosclerosis, and IF/TA was related to the prevalence of anemia (odds ratio: 7.31, 95% confidence interval: 2.33-23.00, p<0.01) according to a multivariable regression analysis. Furthermore, the isolated DN group demonstrated a poorer prognosis than the NDKD group. Conclusion DN is associated with anemia because of severe IF/TA regardless of the renal function, and anemia helps clinician discriminate clinically between isolated DN and NDKD.

Kidney Biopsy in Type 2 Diabetes: A Multicenter Cross-Sectional Study

INTRODUCTION

Kidney biopsies (KBs) are performed in patients with type 2 diabetes (T2D) to diagnose non-diabetic or hypertensive kidney disease (NDHKD) potentially requiring specific management compared to diabetic and or hypertensive nephropathy (absence of NDHKD). Indications for KB are based on the presence of atypical features compared to the typical course of diabetic nephropathy. In this study, we assessed the association of different patterns of atypical features, or KB indications, with NDHKD.

METHODS

Native KBs performed in patients with T2D were analyzed. Data were collected from the patients' records. KB indications were determined according to the presence of different atypical features considered sequentially: (1) presence of any feature suggesting NDHKD which is not among the following ones, (2) recent onset of nephrotic syndrome, (3) low or rapidly declining estimated glomerular filtration rate (eGFR), (4) rapid increase in proteinuria, (5) short duration of diabetes, (6) presence of hematuria, or (7) normal retinal examination.

RESULTS

Among the 463 KBs analyzed, NDHKD was diagnosed in 40% of the total population and 54, 40, 24, and 7% of the KBs performed for indications 1-4 respectively. Conversely, no patient who underwent KB for indications 5-7 displayed NDHKD. Logistic regression analyses identified eGFRCKD-EPI >15 mL/min/1.73 m2, urinary protein-to-Cr ratio <0.3 g/mmol, hematuria, HbA1c <7%, and diabetes duration <5 years as predictors of NDHKD, independently from the indication group.

CONCLUSION

NDHKD is frequent in T2D. Despite the association of hematuria with NDHKD, our results suggest that presence of hematuria and absence of DR are insufficient to indicate KB in the absence of concurrent atypical features. Conversely, rapid progression of proteinuria and rapid deterioration of eGFR are major signals of NDHKD.

The unique molecular mechanism of diabetic nephropathy: a bioinformatics analysis of over 250 microarray datasets

Background/Aims

Diabetic nephropathy (DN) is one of the main causes of end-stage kidney disease worldwide. Emerging studies have suggested that its pathogenesis is distinct from nondiabetic renal diseases in many aspects. However, it still lacks a comprehensive understanding of the unique molecular mechanism of DN.

Methods

A total of 255 Affymetrix U133 microarray datasets (Affymetrix, Santa Calra, CA, USA) of human glomerular and tubulointerstitial tissues were collected. The 22 215 Affymetrix identifiers shared by the Human Genome U133 Plus 2.0 and U133A Array were extracted to facilitate dataset pooling. Next, a linear model was constructed and the empirical Bayes method was used to select the differentially expressed genes (DEGs) of each kidney disease. Based on these DEG sets, the unique DEGs of DN were identified and further analyzed using gene ontology and pathway enrichment analysis. Finally, the protein–protein interaction networks (PINs) were constructed and hub genes were selected to further refine the results.

Results

A total of 129 and 1251 unique DEGs were identified in the diabetic glomerulus (upregulated n = 83 and downregulated n = 203) and the diabetic tubulointerstitium (upregulated n = 399 and downregulated n = 874), respectively. Enrichment analysis revealed that the DEGs in the diabetic glomerulus were significantly associated with the extracellular matrix, cell growth, regulation of blood coagulation, cholesterol homeostasis, intrinsic apoptotic signaling pathway and renal filtration cell differentiation. In the diabetic tubulointerstitium, the significantly enriched biological processes and pathways included metabolism, the advanced glycation end products–receptor for advanced glycation end products signaling pathway in diabetic complications, the epidermal growth factor receptor (EGFR) signaling pathway, the FoxO signaling pathway, autophagy and ferroptosis. By constructing PINs, several nodes, such as AGR2, CSNK2A1, EGFR and HSPD1, were identified as hub genes, which might play key roles in regulating the development of DN.

Conclusions

Our study not only reveals the unique molecular mechanism of DN but also provides a valuable resource for biomarker and therapeutic target discovery. Some of our findings are promising and should be explored in future work.

Primary glomerulonephritis in diabetic patients

BACKGROUND

Primary glomerulonephritis (PGN) has a significant part in non-diabetic kidney disease (NDKD) in diabetes mellitus (DM) patients. In our study, we compared the clinical, demographic and laboratory features of patients with biopsy-proven diabetic nephropathy (DN) and PGN with type 2 DM.

METHODS

In our retrospective study, type 2 DM patients who underwent kidney biopsy between 2011 and 2019 were included. Demographic, clinical and laboratory characteristics of DN and PGN patients were compared.

RESULTS

Seventy patients with a mean age of 55.7 ± 9.4 and 43 (61.4%) males were included. About 38 (54.3%) of the patients had DN and 32 (45.7%) had PGN. In the PGN, membranous GN (20, 62.5%) was most common. In DN patients, diabetes duration was longer; complications such as retinopathy, neuropathy, hypertension, coronary artery disease, heart failure were more frequent. At the time of renal biopsy, blood sugar, HbA1C, blood pressure, serum albumin and proteinuria values were similar in two groups. The pathological damage findings of kidney biopsy in DN patients were more severe. In the first year after kidney biopsy decrease in eGFR was higher in DN patients, whereas eGFR did not change in PGN patients.

CONCLUSION

In a diabetic patient, fasting blood sugar, hbA1C, serum albumin and proteinuria did not differ in the differential diagnosis of DN and PGN, whereas complications of DM (retinopathy, neuropathy, hypertension, coronary artery disease) were more characteristic in differentiation. Detection of PGN in a diabetic patient is crucial for the success of the treatment, according to DN.

Insights into the Role of Renal Biopsy in Patients with T2DM: A Literature Review of Global Renal Biopsy Results

INTRODUCTION

Renal biopsy performed in patients with type 2 diabetes mellitus (T2DM) for atypical or suspected diabetic kidney disease (DKD) reveals one of three possibilities: diabetic nephropathy (DN, pathological diagnosis of DKD), nondiabetic kidney disease (NDKD) and DN plus NDKD (mixed form). NDKD (including the mixed form) is increasingly being recognized worldwide. With the emerging concept of DKD and the complexity of routine application of renal biopsy, the identification of "clinical indicators" to differentiate DKD from NDKD has been an area of active research.

METHODS

The PubMed database was searched for relevant articles mainly according to the keyword search method. We reviewed prevalence of the three types of DKD and different pathological lesions of NDKD. We also reviewed the clinical indicators used to identify DKD and NDKD.

RESULTS

The literature search identified 40 studies (5304 data) worldwide between 1977 and 2019 that looked at global renal biopsy and pathological NDKD lesions. The overall prevalence rate of DN, NDKD and DN plus NDKD is reported to be 41.3, 40.6 and 18.1%, respectively. In Asia, Africa (specifically Morocco and Tunisia) and Europe, the most common isolated NDKD pathological type is membranous nephropathy, representing 24.1, 15.1 and 22.6% of cases, respectively. In contrast, focal segmental glomerulosclerosis is reported to be the primary pathological type in North America (specifically the USA) and Oceania (specifically New Zealand), representing 22% and 63.9% of cases, respectively. Tubulointerstitial disease accounts for a high rate in the mixed group (21.7%), with acute interstitial nephritis being the most prevalent (9.3%), followed by acute tubular necrosis (9.0%). Regarding clinical indicators to differentiate DKD from NDKD, a total of 14 indicators were identified included in 42 studies. Among these, the most commonly studied indicators included diabetic retinopathy, duration of diabetes, proteinuria and hematuria. Regrettably, indicators with high sensitivity and specificity have not yet been identified.

CONCLUSION

To date, renal biopsy is still the gold standard to diagnose diabetes complicated with renal disease, especially when T2DM patients present atypical DKD symptoms (e.g. absence of diabetic retinopathy, shorter duration of diabetes, microscopic hematuria, sub-nephrotic range proteinuria, lower glycated hemoglobin, lower fasting blood glucose). We conclude that renal biopsy as early as possible is of great significance to enable personalized treatment to T2DM patients.

Optimizing the timing of nephrology referral for patients with diabetic kidney disease

Age-standardized rates of diabetes mellitus (DM)-related complications, such as acute myocardial infarction, stroke or amputations, have decreased in recent years, but this was not associated with a clear reduction of the incidence of advanced chronic kidney disease (CKD) requiring renal replacement therapy. The early detection of diabetic kidney disease (DKD) is a key to reduce complications, morbidity and mortality. Consensus documents and clinical practice guidelines recommend referral of DM patients to nephrology when the estimated glomerular filtration rate falls below 30 mL/min/1.73 m² or when albuminuria exceeds 300 mg/g urinary creatinine. Conceptually, it strikes as odd that patients with CKD are referred to the specialist caring for the prevention and treatment of CKD only when >70% of the functioning kidney mass has been lost. The increasing global health burden of CKD, driven in large part by DKD, the suboptimal impact of routine care on DKD outcomes as compared with other DM complications, the realization that successful therapy of CKD requires early diagnosis and intervention, the advances in earlier diagnosis of kidney injury and the recent availability of antidiabetic drugs with a renal mechanism of action and lack of hypoglycaemia risk, which additionally are cardio- and nephroprotective, all point towards a paradigm shift in the care for DM patients in which they should be referred earlier to nephrology as part of a coordinated and integrated care approach.

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.

Incidence, Risk Factors, and Outcomes of Transition of Acute Kidney Injury to Chronic Kidney Disease in Cirrhosis: A Prospective Cohort Study

Transition to chronic kidney disease (CKD) after an episode of acute kidney injury (AKI) is known in patients without cirrhosis. We studied the incidence and risk factors for development of CKD in patients with cirrhosis. Competing risk analysis was performed to identify risk factors for CKD development. Of 818 patients with cirrhosis (age, 50.4 ± 11.8 years; 84% males; Model for End-Stage Liver Disease [MELD], 19.9 ± 9.9), 36% had AKI at enrollment, 27% had previous AKI, and 61% developed new episodes of AKI during the follow-up period. CKD developed in 269 (33%) patients. Serum cystatin C (CysC; subdistribution hazard ratio [SHR], 1.58; 1.07-2.33), episodes of previous AKI (SHR, 1.26; 1.02-1.56), and AKI stage at enrollment (no AKI [SHR, 1] vs. stage 1 [SHR, 3.28; 1.30-8.25] vs. stage 2 [SHR, 4.33; 1.76-10.66] vs. stage 3 [SHR, 4.5; 1.59-12.73]) were identified as baseline risk factors for CKD development. On time-varying competing risk analysis, MELD (SHR, 1.01; 1.00-1.03), number of AKI episodes (SHR, 1.25; 1.15-1.37), and CysC (SHR, 1.38; 1.01-1.89) predicted CKD development. Development of CKD was associated with higher risk of death. Reduction in glomerular filtration rate (GFR) not meeting CKD criteria was observed in 66% of patients with cirrhosis, more so in those with previous AKI episodes and a high CysC level and MELD score. Renal histology, available in 55 patients, showed tubulointerstitial injury in 86%, cholemic nephrosis in 29%, and glomerular changes in 38%. Conclusion: Almost two-thirds of patients with cirrhosis develop episodes of AKI and reduction in GFR; one-third progress to CKD, resulting in adverse outcomes. Higher MELD and CysC levels and number of AKI episodes predict development of CKD in patients with cirrhosis.

Diabetic Kidney Disease: Past and Present

Diabetes mellitus (DM) afflicting humans has been recognized as a disease for >3000 years. However, very little was known about its etiology and pathogenesis until about a century ago when increasing knowledge about anatomy and physiology of the human body gradually led to our understanding that the hormone insulin produced by the Islets of Langerhans in the pancreas plays a crucial role in the metabolism of glucose and maintaining the blood sugar level within a normal range. DM is caused by inadequate insulin production (type 1) or insulin resistance (type 2). For thousands of years, DM has been considered as a disease of the kidney; however, with the understanding of the pathogenesis of DM, it became clear that diabetic kidney disease (DKD) is a complication and not a cause of DM. DKD is associated with increased matrix expansion that manifests morphologically as a diffuse or nodular expansion of the mesangium and diffuse thickening of the glomerular and tubular basement membranes. Hyperglycemia plays a crucial role in the development of pathologic changes within the kidney. Once established, DKD usually undergoes a slow but relentless progression to end-stage renal disease. However, recent studies have shown that its progression can be slowed or even reversed by strict control of hyperglycemia. Morphologically, DKD may resemble several other glomerular diseases that must be ruled out before a definitive diagnosis. Patients with DM may also develop nondiabetic glomerular or interstitial diseases with or without DKD. The findings in nephrectomy specimens and the differential diagnoses are presented in detail.

[Criteria to indicate kidney biopsy in type 2 diabetic patients with proteinuria: Survey among French nephrologists]

Diabetic nephropathy is usually a presumptive diagnosis based on clinical and biological evidence. Renal biopsies are performed in diabetic patients with atypical findings evoking non-diabetic renal disease who could benefit from specific therapies. French speaking nephrologists were asked which criteria they retain to indicate renal biopsy in patients with type 2 diabetes and albuminuria>0.5g/day or equivalent through an online anonymous questionnaire. Among the suggested criteria were absence of diabetic retinopathy, hematuria, rapid decrease in GFR, short diabetes duration or rapid raise of proteinuria. 188 people answered the poll among whom interns (12%), fellows (13%), university hospital practitioners (26%), general hospital practitioners (24%), practitioners in a non-profit organization (13%), practitioners on private activity (10%), multi-modal practitioners (3%) and people without clinical activity (2%). Increasing proteinuria was retained as an indication criterion for renal biopsy by 51% of respondents, nephrotic syndrome by 56% of respondents, absence of diabetic retinopathy by 57% of respondents, short diabetes duration by 65% of respondents, rapid GFR decline by 75% of respondents and hematuria by 78% of respondents. These data highlight the high diversity of opinions on this topic and their discrepancies with guidelines and current literature regarding the association between non-diabetic renal disease and clinical and biological features. The lack of adhesion of nephrologists to guidelines was especially noteworthy regarding the absence of diabetic retinopathy. These results emphasize the need for studies focusing on biopsy indication criteria in patients with type 2 diabetes.

Identification of clinical predictors of diabetic nephropathy and non-diabetic renal disease in Chinese patients with type 2 diabetes, with reference to disease course and outcome

AIMS

To determine the prevalence of diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) in patients with type 2 diabetes mellitus (T2DM), and the important clinical predictors of renal outcome and clinical course.

METHODS

We conducted a retrospective analysis of clinical, laboratory, and histopathologic data from T2DM patients with renal involvement confirmed by renal biopsy (n = 505). The outcome was defined as the progression to end-stage renal disease (ESRD).

RESULTS

Renal biopsy revealed that 302 patients (59.8%) had DN, 174 (34.5%) had NDRD, and 29 (5.7%) had NDRD superimposed on DN. In multivariate analysis, the absence of diabetic retinopathy (DR) (odds ratio (OR) 4.171, 95% confidence interval (CI) 1.810-9.612; P = 0.001), absence of hypertension (OR 2.412, 95% CI 1.095-5.315; P = 0.029), shorter duration of diabetes (OR 1.015, 95% CI 1.008-1.022; P < 0.001), lower-risk chronic kidney disease (CKD) heat map category (green, yellow and orange) (OR 3.885, 95% CI 1.289-11.707; P = 0.016) and lower glycated hemoglobin (HbA1c) (OR 1.339, 95% CI 1.114-1.610; P = 0.002) were significant clinical predictors of NDRD. Patients with DN had a poorer 5-year renal outcome than those with NDRD, and multivariate analysis identified DN as an independent risk factor for progression to ESRD, when adjusted for important clinical variables (P < 0.05).

CONCLUSIONS

This study has identified the absence of DR and hypertension, lower-risk CKD heat map category, shorter duration of diabetes, and lower HbA1c as useful clinical predictors of NDRD. Renal biopsy is recommended for patients with T2DM and renal disease to obtain an accurate diagnosis and determine timely disease-specific treatment, which should increase the chance of a good renal outcome.

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.