Presentation, pathology and prognosis of renal disease in type 2 diabetes

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.

Design and methodology of the PRIMETIME 1 cohort study: PRecIsion MEdicine based on kidney TIssue Molecular interrogation in diabetic nEphropathy

Background

Clinical features of diabetic kidney disease alone cannot differentiate between the histopathology that defines diabetic nephropathy (DN) and non-diabetic nephropathy (NDN). A kidney biopsy is necessary to make the definitive diagnosis of DN. However, there is no consensus on when to perform a kidney biopsy in individuals with diabetes and kidney disease. Furthermore, the implications of NDN versus DN for management, morbidity and kidney prognosis are unclear. To address the gap in knowledge, we aimed to create a national retrospective cohort of people with diabetes and a performed kidney biopsy.

Methods

Adults diagnosed with diabetes in Denmark between 1996 and 2020 who had a kidney biopsy performed were included. The cohort was established by linking a nationwide diabetes registry with the Danish Pathology Registry. Data from 11 national registries and databases were compiled. The type of kidney disease was classified using a three-step analysis of Systematized Nomenclature of Medicine codes reported in relation to the histopathological examinations of kidney tissue. The final cohort and classification of kidney disease was as follows: out of 485 989 individuals with diabetes 2586 were included, 2259 of whom had type 2 diabetes. We were able to classify 599 (26.5%) with DN, 703 (31.1%) with NDN and 165 (7.3%) with mixed disease in individuals with type 2 diabetes. In individuals with type 1 diabetes, 132 (40.4%) had DN, 73 (22.3%) NDN and 39 (11.9%) mixed disease. The remaining could not be classified or had normal histology. The overall median (Q1-Q3) follow-up time was 3.8 (1.6-7.2) years.

Conclusions

This cohort is a novel platform based on high-quality registry data for important longitudinal studies of the impact of kidney disease diagnosis on prognosis. With regular updates of data from the Danish registries, the presented follow-up will increase over time and is only limited by emigration or death.

Rationale and design of a prospective, clinical study of kidney biopsies in people with type 2 diabetes and severely increased albuminuria (the PRIMETIME 2 study)

INTRODUCTION

Diabetic kidney disease is a severe complication of diabetes. The diagnosis is based on clinical characteristics such as persistently elevated albuminuria, hypertension and decline in kidney function, although this definition is not specific to kidney disease caused by diabetes. The only way to establish an accurate diagnosis-diabetic nephropathy-is by performing a kidney biopsy. The histological presentation of diabetic nephropathy can be associated with a heterogeneous range of histological features with many pathophysiological factors involved demonstrating the complexity of the condition. Current treatment strategies aim to slow disease progression and are not specific to the underlying pathological processes.This study will investigate the prevalence of diabetic nephropathy in individuals with type 2 diabetes (T2D) and severely elevated albuminuria. The deep molecular characterisation of the kidney biopsy and biological specimens may pave the way for improved diagnostic accuracy and a better understanding of the pathological processes involved and may also reveal new targets for individualised treatment.

METHODS AND ANALYSIS

In the PRecIsion MEdicine based on kidney TIssue Molecular interrogation in diabetic nEphropathy 2 study, research kidney biopsies will be performed in 300 participants with T2D, urine albumin/creatinine ratio ≥700 mg/g and estimated glomerular filtration ratio >30 mL/min/1.73 m2. Cutting-edge molecular technologies will be applied to the kidney, blood, urine, faeces and saliva samples for comprehensive multi-omics profiling. The associated disease course and clinical outcomes will be assessed by annual follow-up for 20 years.

ETHICS AND DISSEMINATION

The Danish Regional Committee on Health Research Ethics and the Knowledge Center on Data Protection (in the Capital Region of Denmark) have granted approval for the study. The results will be published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04916132.

Ultrasound Renal Score to Predict the Renal Disease Prognosis in Patients with Diabetic Kidney Disease: An Investigative Study

Renal disease associated with type 2 diabetes mellitus (T2DM) has become the leading cause of chronic kidney disease (CKD). Renal ultrasonography is an imaging examination required in the work-up of renal disease. This study aimed to identify the differences in renal ultrasonographic findings between patients with and without DM, and to evaluate the relationship between renal ultrasound findings and renal prognosis in patients with DM. A total of 252 patients who underwent renal ultrasonography at Chungnam National University Hospital were included. Kidney disease progression was defined as a ≥10% decline in the annual estimated glomerular filtration rate (eGFR), which, in this paper, is referred to as ΔeGFR/year, or the initiation of renal replacement therapy after follow-up. The renal scoring system was evaluated by summing up the following items: the value of renal parenchymal echogenicity (0: normal; 1: mildly increased; and 2: increased) and the shape of the cortical margin (0: normal and 1: irregular; right kidney length/height (RH-0 or 1), mean cortical thickness/renal length/height (CKH-0 or 1), and cortical thickness/parenchymal thickness (CK/PK-0 or 1) based on the median: 0-above median, and 1-below median). Patients with DM had thicker renal PKH than those without, despite having lower eGFRs (0.91 ± 0.15, 0.86 ± 0.14, p = 0.006). In the progression group, the renal scores were significantly higher than those from the non-progression group. In the multivariate logistic regression analysis, the higher renal scores, presence of DM, and younger age were independently predicted for renal disease progression after adjusting for confounding variables, such as the presence of hypertension, serum hemoglobin and albumin levels, and UPCR. In conclusion, patients with high renal scores were significantly associated with renal disease progression. Our results suggest that renal ultrasonography at the time of diagnosis provides useful prognostic information in patients with kidney disease.

Ethnic differences in 25-year risk of incident chronic kidney disease among people with type 2 diabetes in New Zealand

INTRODUCTION

Insights into ethnic differences in the natural history of chronic kidney disease (CKD) among people with type 2 diabetes mellitus (T2DM) might inform clinical strategies to address disparities in hospitalization and mortality. Risks of CKD II-V stages over a 25-year period between New Zealand Europeans (NZEs), Māori and Pasifika, and with T2DM in Auckland, New Zealand (NZ) were compared.

RESEARCH DESIGN AND METHODS

As a primary care audit program in Auckland, the Diabetes Care Support Service was linked with national registration databases. People with existing CKD II-V were ruled out. To balance potential confounders, we applied a tapered matching method . 'Quasi-trial'-matched cohorts were set up separately between Māori and NZE and between Pasifika and NZE. Ethnic population differences in risk of any and each stage of CKD over 1994-2018 were examined by weighted Cox regression model.

RESULTS

The HRs for developing any CKD, CKD stages II-V for Māori (n=2215) versus NZE (n=2028) were 1.18 (95% CI 0.99 to 1.41), 1.10 (95% CI 0.91 to 1.32), 1.70 (95% CI 1.19 to 2.43), 3.93 (95% CI 2.16 to 7.14), and 3.74 (95% CI 1.74 to 8.05), respectively. Compared with NZE (n=2474), the HRs for developing any CKD, CKD stages II-V for Pasifika (n=3101) were 1.31 (95% CI 1.09 to 1.57), 1.26 (95% CI 1.05 to 1.52), 1.71 (95% CI 1.14 to 2.57), 3.75 (95% CI 1.40 to 10.05), and 4.96 (95% CI 1.56 to 15.75), respectively.

CONCLUSIONS

Among people with T2DM in NZ, significant ethnic differences exist in the risk of progressing to each stage of CKD (stage V in particular). Mechanism studies underlying these differences, as well as the need for identification of biomarkers to predict the early onset renal lesion, are warranted.

Prediction of the Short-Term Risk of New-Onset Renal Dysfunction in Patients with Type 2 Diabetes: A Longitudinal Observational Study

Background

Studies in the past decade have reported many novel biomarkers for predicting the new-onset or progression risk of renal dysfunction in patients with type 2 diabetes (T2D) based on the genomic, metabolomic, and proteomic technologies. These novel predictive markers, however, are difficult to be widely used in clinical practice over the short term due to their high technology content, instability, and high cost. This study was aimed at evaluating the associations of clinical features and six traditional renal markers with the short-term risk of new-onset renal dysfunction in patients with T2D.

Methods

This study involved 213 participants with T2D and normal renal function at baseline. The baseline levels of the albumin-to-creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), alpha-1-microglobulin-to-creatinine ratio (A1MCR), neutrophil gelatinase-associated lipocalin-to-creatinine ratio, transferrin-to-creatinine ratio (UTRF/Cr), and retinol-binding protein-to-creatinine ratio (URBP/Cr) were analyzed. Multivariate logistic models were established and validated.

Results

During the two-year follow-up period, 23.01% participants progressed to renal dysfunction. The basal levels of ACR, A1MCR, UTRF/Cr, and URBP/Cr were the independent risk factors of new-onset renal dysfunction (P < 0.05). Several logistic models incorporating clinical characteristics and these renal markers were constructed for predicting the short-term risk of new-onset renal dysfunction. Comparatively, the model including age, glycated hemoglobin (HbA1c), hypertension, ACR, A1MCR, UTRF/Cr, and URBP/Cr levels at baseline had the highest potential (C − index = 0.785, P < 0.001). This model was validated using the K-fold cross-validation method; the accuracy was 0.815 ± 0.013 in training sets and 0.784 ± 0.019 in validation sets, indicating a good consistency for predicting the new-onset renal dysfunction risk. Finally, a nomogram based on this model was constructed to provide a quantitative tool to assess the individualized risk of short-term new-onset renal dysfunction.

Conclusion

The model incorporating these markers and clinical features may have a high potential to predict the short-term risk of new-onset renal dysfunction.

Socioeconomic status and risk factors for complications in young people with type 1 or type 2 diabetes: a cross-sectional study

INTRODUCTION

Young people with type 2 diabetes (T2D) develop complications earlier than those with type 1 diabetes (T1D) of comparable duration, but it is unclear why. This apparent difference in phenotype could relate to relative inequality.

RESEARCH DESIGN AND METHODS

Cross-sectional study of young people referred to secondary diabetes services in Auckland, Aotearoa-New Zealand (NZ): 731 with T1D and 1350 with T2D currently aged <40 years, and diagnosed between 15 and 30 years. Outcome measures were risk factors for complications (glycemic control, urine albumin/creatinine ratio (ACR), cardiovascular disease (CVD) risk) in relation to a validated national index of deprivation (New Zealand Deprivation Index (NZDep)).

RESULTS

Young people with T2D were an average 3 years older than those with T1D but had a similar duration of diabetes. 71% of those with T2D were of Māori or Pasifika descent, compared with 24% with T1D (p<0.001). T1D cases were distributed evenly across NZDep categories. 78% of T2D cases were living in the lowest four NZDep categories (p<0.001). In both diabetes types, body mass index (BMI) increased progressively across the NZDep spectrum (p<0.002), as did mean glycated hemoglobin (HbA_1c) (p<0.001), the prevalence of macroalbuminuria (p≤0.01), and CVD risk (p<0.001). Adjusting for BMI, diabetes type, and duration and age, multiple logistic regression revealed deprivation was the strongest risk factor for poorly controlled diabetes (defined as HbA_1c >64 mmol/mol, >8%); OR 1.17, 95% CI 1.13 to 1.22, p<0.0001. Ordinal logistic regression showed each decile increase in NZDep increased the odds of a higher ACR by 11% (OR 1.11, 95% CI 1.06 to 1.16, p<0.001) following adjustment for BMI, blood pressure, diabetes type and duration, HbA_1c, and smoking status. Multiple linear regression indicated a 4% increase in CVD risk for every decile increase in NZDep, regardless of diabetes type.

CONCLUSIONS

The apparent more aggressive phenotype of young-onset T2D is at least in part explicable by relative deprivation.

Predictive model and risk analysis for diabetic retinopathy using machine learning: a retrospective cohort study in China

OBJECTIVE

Aiming to investigate diabetic retinopathy (DR) risk factors and predictive models by machine learning using a large sample dataset.

DESIGN

Retrospective study based on a large sample and a high dimensional database.

SETTING

A Chinese central tertiary hospital in Beijing.

PARTICIPANTS

Information on 32 452 inpatients with type-2 diabetes mellitus (T2DM) were retrieved from the electronic medical record system from 1 January 2013 to 31 December 2017.

METHODS

Sixty variables (including demography information, physical and laboratory measurements, system diseases and insulin treatments) were retained for baseline analysis. The optimal 17 variables were selected by recursive feature elimination. The prediction model was built based on XGBoost algorithm, and it was compared with three other popular machine learning techniques: logistic regression, random forest and support vector machine. In order to explain the results of XGBoost model more visually, the Shapley Additive exPlanation (SHAP) method was used.

RESULTS

DR occurred in 2038 (6.28%) T2DM patients. The XGBoost model was identified as the best prediction model with the highest AUC (area under the curve value, 0.90) and showed that an HbA1c value greater than 8%, nephropathy, a serum creatinine value greater than 100 µmol/L, insulin treatment and diabetic lower extremity arterial disease were associated with an increased risk of DR. A patient's age over 65 was associated with a decreased risk of DR.

CONCLUSIONS

With better comprehensive performance, XGBoost model had high reliability to assess risk indicators of DR. The most critical risk factors of DR and the cut-off of risk factors can be found by SHAP method to render the output of the XGBoost model clinically interpretable.

Kidney disease in diabetes: From mechanisms to clinical presentation and treatment strategies

Metabolic and haemodynamic perturbations and their interaction drive the development of diabetic kidney disease (DKD) and its progression towards end stage renal disease (ESRD). Increased mitochondrial oxidative stress has been proposed as the central mechanism in the pathophysiology of DKD, but other mechanisms have been implicated. In parallel to increased oxidative stress, inflammation, cell apoptosis and tissue fibrosis drive the relentless progressive loss of kidney function affecting both the glomerular filtration barrier and the renal tubulointerstitium. Alteration of glomerular capillary autoregulation is at the basis of glomerular hypertension, an important pathogenetic mechanism for DKD. Clinical presentation of DKD can vary. Its classical presentation, often seen in patients with type 1 diabetes (T1DM), features hyperfiltration and albuminuria followed by progressive fall in renal function. Patients can often also present with atypical features characterised by progressive reduction in renal function without albuminuria, others in conjunction with non-diabetes related pathologies making the diagnosis, at times, challenging. Metabolic, lipid and blood pressure control with lifestyle interventions are crucial in reducing the progressive renal function decline seen in DKD. The prevention and management of DKD (and parallel cardiovascular disease) is a huge global challenge and therapies that target haemodynamic perturbations, such as inhibitors of the renin-angiotensin-aldosterone system (RAAS) and SGLT2 inhibitors, have been most successful.

Morbidity and mortality after recognition of macroalbuminuria in Pasifika people with type 2 diabetes in a primary health-care practice

INTRODUCTION Macroalbuminuria in people with type 2 diabetes is common among Pasifika peoples and is associated with end-stage kidney disease and major cardiovascular disease. AIM In a primary care practice catering for Pasifika people, to determine the time after first recognition of macroalbuminuria to the occurrence of major cardiovascular and renal events, and to examine the relationship with retinopathy status. METHODS In a retrospective observational cohort study, we documented the occurrence of major cardiovascular events and amputations, end-stage kidney disease and death in 115 people with type 2 diabetes reviewed by a specialist diabetes physician at the Langimalie Tongan Health practice between 2005 and 2018. The follow up was 1-19 (median 9.5) years from the first recognition of macroalbuminuria (albumin:creatinine ratio of >30 g/mol). Survival was described by using Kaplan-Meier analysis. RESULTS Macroalbuminuria was detected a mean of 9 years after the diagnosis of diabetes, at a mean age of 52 (standard deviation 12) years. Within 6 years of macroalbuminuria detection, 4% of people had died, 15% had reached end-stage kidney disease, 15% had cardiovascular events or amputations and 30% had the composite outcome of any of these. Within 12 years, the respective proportions were: 24%, 29%, 20% and 48%. The composite outcome was less frequent (P < 0.002) in patients without retinopathy at the time macroalbuminuria was recognised. Compared to patients with retinopathy, this group were younger (P = 0.025), more obese (P < 0.0001), had better baseline renal function (P = 0.018) and a shorter interval between the diagnosis of diabetes and recognition of macroalbuminuria (P < 0.0001). DISCUSSION In this Pasifika population, macroalbuminuria was a marker for serious adverse cardiovascular and renal disease, and mortality, but in the 29% of patients without retinopathy at the time of recognition of macroalbuminuria, the natural history was more benign. The management of such comorbid patients is a substantial challenge for primary health-care services.

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.

Prognosis in pathology: Are we "prognosticating" or only establishing correlations between independent variables and survival? A study with various analytics cautions about the overinterpretation of statistical results

Survival data from 225 patients with resected pulmonary typical carcinoids were analyzed with Kaplan-Meier statistics (K-M) and "deep learning" methods to illustrate the difference between establishing "correlations" and "prognostications". Cases were stratified into G1 and G2 classes using a ≤5% Ki-67% cut-point. Overall survival, number of patients at risk and 95% confidence intervals (CI) were estimated for the two classes. Seven neural network models (NN) were developed with GMDH Shell 3.8.2 and Statgraphics Centurion 18.1 software, using variable prior probabilities and different numbers of training vs testing cases. The NNs used age, sex, and pTNM, G1 and G2 as input neurons and "alive" and "dead" as output neurons. Areas under the curve (AUC) and other performance measures were evaluated for all models. Log-rank test showed a significant difference in overall survival between G1 and G2 (p < 0.001). However, 95% CI estimates showed considerable variability in survival at different time intervals. Including the number of patients at risk at different time intervals showed that most G2 patients had been censored by 100 weeks. The NN models provided variable "prognostications", with AUC ranging from 0.5 to 1 and variability in the sensitivity, specificity, and other performance measures. The results illustrate the limitations of survival statistics and NNs in predicting the prognosis of individual patients. The need for pathologists not to overinterpret the finding of significant correlations as "prognostic" or "predictive" for individual patients is discussed.

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.

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.

Time to acute kidney injury and its predictors among newly diagnosed Type 2 diabetic patients at government hospitals in Harari Region, East Ethiopia

BACKGROUND

Incidence of Acute Kidney Injury (AKI) among Type 2 diabetic patients is significantly increasing. But, earlier studies has focused on the admitted patients which may hide the true nature of the Acute Kidney Injury among Type 2 Diabetic (T2D) patients. So, this study was conducted to determine the time to Acute Kidney Injury and its predictors among Type 2 Diabetic patients in Harari Region, East Ethiopia.

METHODS

We conducted a retrospective cohort study among type 2 diabetic patients who had been receiving treatment at government hospitals of Harari region, Ethiopia from 2013 to 2017. We extracted data from patients' medical records. We estimated incidence rate and compared survival curves between different exposure groups using Kaplan-Meier and log-rank test. Weibull regression model was fitted to the data to identify the predictor variables. Variables with p-value <0.05 were considered statistically significant.

RESULTS

Overall, 14.5% (95%CI: 11.7-17.9) of the study population developed acute kidney injury, with median survival time of 57 months. The significant predictors were physical activity [Adjusted Time Ratio (ATR):95%CI; 0.6 (0.49-0.75)], congestive heart failure [ATR:95%CI; 0.84 (0.71-0.99)], chronic kidney disease [ATR:95%CI; 0.77(0.65-0.91)], hypertension [ATR:95%CI; 0.78(0.65-0.91)], obesity [ATR:95%CI; 0.84(0.74-0.96)], diabetic nephropathy [ATR:95%CI; 0.80(0.65-0.98)], diuretics & beta blockers [ATR:95%CI; 0.85(0.74-0.97)], and delay of follow-up [ATR:95%CI; 0.97(0.96-0.98)].

CONCLUSIONS

Incidence of acute kidney injury was high in our study area. Hence, identification and controlling of comorbidities along with regular monitoring of kidney function are needed to prevent or delay the risk of acute kidney injury in type 2 diabetic patients.

Nephrotoxicity induced by intravitreal vascular endothelial growth factor inhibitors: emerging evidence

Vascular endothelial growth factor (VEGF) inhibitors have emerged as powerful tools to treat malignant neoplasms and ocular diseases by virtue of their ability to inhibit angiogenesis. Recent data indicate that intravitreal injections of VEGF inhibitors can lead to significant systemic absorption as well as a measurable reduction of plasma VEGF activity. There is increasing evidence showing that vitreal absorption of these drugs is associated with cases of accelerated hypertension, worsening proteinuria, glomerular disease, thrombotic microangiopathy, and possible chronic renal function decline. In this review, the 3 most commonly used anti-VEGF agents-bevacizumab, ranibizumab, and aflibercept-are discussed, highlighting their intravitreal absorption and associated effects on the kidney as a target organ system. We provide clinical suggestions for clinicians to both better manage patients receiving anti-VEGF agents intravitreally and detect any putative systemic renal effects of these agents. While acknowledging the risks of aberrant retinal angiogenesis, it is important for clinicians to be aware of the potential for adverse renal risks with use of these agents.

Prevalence of Diabetic Retinopathy and Associated Mortality Among Diabetic Adults With and Without Chronic Kidney Disease

PURPOSE

To estimate prevalence and severity of diabetic retinopathy (DR) among U.S. adults with diabetes and with or without chronic kidney disease (CKD), and assess associated risk of mortality.

DESIGN

Cross-sectional study with national survey data.

METHODS

The cohort included adults ≥40 years old with diabetes in the National Health and Nutrition Examination Surveys (NHANES) 2005-2008. Vital status was determined through December 31, 2011. We defined diabetes as hemoglobin A1c ≥6.5% or self-report and CKD by urinary albumin/creatinine ≥30 mg/g or glomerular filtration rate <60 mL/min/1.73 m². The main outcomes were DR and mortality.

RESULTS

Prevalence of DR was 27.8% (95% CI 24.3-31.7), 36.2% (95%CI 30.1-42.7), and 23.4% (95% CI 19.2-28.1), overall, with and without CKD. Prevalence of vision-threatening DR was 4.2% (95% CI 3.2-5.5), 8.2% (95% CI 5.4-12.2), and 2.0% (95% CI 1.2-3.5), respectively. In a multivariable adjusted model, DR was positively but nonsignificantly associated with CKD (OR = 1.1, 95% CI 0.7-1.7), was 40% higher per 1% increase in hemoglobin A1c (OR = 1.4, 95% CI 1.1-1.6), was 30% higher per 5 years additional diabetes duration (OR = 1.3, 95% CI 1.1-1.5), was 30% higher per 10 mm Hg increase in systolic blood pressure (OR = 1.3, 95% CI 1.1-1.5), and was 6-fold higher with insulin treatment (OR = 6.2, 95% CI 2.6-14.8). Compared with diabetic participants with neither DR nor CKD, those with DR and CKD had a 3.6-fold (95% CI 1.5-9.1) increased adjusted risk for all-cause mortality.

CONCLUSIONS

Over one third of persons with diabetes and CKD had DR. The risk of death was higher with than without CKD and DR. Many of the studied risk factors associated with DR are modifiable.

Effect of New-Onset Diabetes Mellitus on Renal Outcomes and Mortality in Patients with Chronic Kidney Disease

Background: The incidence rates of diabetes mellitus (DM) and chronic kidney disease (CKD) are increasing worldwide and their coexistence can have a large negative impact on clinical outcomes. However, it is unclear how incident DM affects CKD patients. Methods: Incident CKD patients between 2000 and 2013 were identified from the National Health Insurance Research Database of Taiwan; they were classified as non-DM (n = 10,356), pre-existing DM (n = 6982), and incident DM (n = 1103). Non-DM cases were patients who did not develop DM before the end of the observation period. The outcomes of interest were end-stage renal disease (ESRD), mortality, and composite outcome (ESRD or death). The association between the DM groups and clinical outcomes was estimated using the inverse probability of group-weighted (IPW) multivariate-adjusted time-dependent Cox regression models. Results: During the study period of 14 years, 1735 (16.6%) patients in the non-DM group reached ESRD compared with 2168 (31.05%) in the pre-existing DM group and 111 (11.03%) in the incident DM group (p < 0.001). Moreover, 2219 (21.43%) patients in the non-DM group died compared with 1895 (27.14%) in the pre-existing DM group and 303 (27.47%) in the incident DM group (p < 0.001). Compared with the non-DM group, the pre-existing DM group was associated with a higher risk of ESRD [hazard ratio (HR) 2.54; 95% confidence interval (CI 2.43–2.65), death (HR 2.23; 95% CI 2.14–2.33), and a composite outcome (HR 2.29; 95% CI 2.21–2.36). Similarly, incident DM was also associated with a higher risk of ESRD (HR 1.12; 95% CI 1.06–1.19), death (HR 2.48; 95% CI 2.37–2.60), and a composite outcome (HR 1.77; 95% CI 1.70–1.84) compared with the non-DM group. Factors contributing to incident DM included old age, low monthly income, and having hypertension, hyperlipidemia, and ischemic heart disease, while pentoxifylline reduced the risk of incident DM. Conclusion: Similarly to pre-existing DM, CKD patients with incident DM carried a higher risk of ESRD, mortality, and a composite outcome compared with those with non-DM. For those at risk of incident DM, strict monitoring and intervention strategies must be adopted to help improve their clinical outcomes.

Validation of Plasma Biomarker Candidates for the Prediction of eGFR Decline in Patients With Type 2 Diabetes

OBJECTIVE

The decline of estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes is variable, and early interventions would likely be cost-effective. We elucidated the contribution of 17 plasma biomarkers to the prediction of eGFR loss on top of clinical risk factors.

RESEARCH DESIGN AND METHODS

We studied participants in PROVALID (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers), a prospective multinational cohort study of patients with type 2 diabetes and a follow-up of more than 24 months (n = 2,560; baseline median eGFR, 84 mL/min/1.73 m²; urine albumin-to-creatinine ratio, 8.1 mg/g). The 17 biomarkers were measured at baseline in 481 samples using Luminex and ELISA. The prediction of eGFR decline was evaluated by linear mixed modeling.

RESULTS

In univariable analyses, 9 of the 17 markers showed significant differences in median concentration between stable and fast-progressing patients. A linear mixed model for eGFR obtained by variable selection exhibited an adjusted R² of 62%. A panel of 12 biomarkers was selected by the procedure and accounted for 34% of the total explained variability, of which 32% was due to 5 markers. The individual contribution of each biomarker to the prediction of eGFR decline on top of clinical predictors was generally low. When included into the model, baseline eGFR exhibited the largest explained variability of eGFR decline (R² of 79%), and the contribution of each biomarker dropped below 1%.

CONCLUSIONS

In this longitudinal study of patients with type 2 diabetes and maintained eGFR at baseline, 12 of the 17 candidate biomarkers were associated with eGFR decline, but their predictive power was low.

Prevalence and risk factors for chronic kidney disease in primary health care in the southern region of New Zealand

AIM

While the prevalence of end stage kidney disease in New Zealand (NZ) is well defined, the prevalence of chronic kidney disease (CKD) in NZ is unknown. To estimate the prevalence of and risk factors for CKD in the southern region of New Zealand.

METHODS

A retrospective electronic health record cohort study using data from the Southern Primary Care register covering 94% of the population. Patients, 20 years or older were identified and linked to laboratory results for serum creatinine and urinary albumin excretion. Chronic kidney disease was defined as an estimated glomerular filtration rate of less than 60 mL/min per 1.73 m² (G3-5) or the presence of albuminuria of greater than 3 mg/mmol (A2-3). Diabetes was identified from a national virtual diabetes database. From this, we estimated the prevalence of CKD by age, gender, ethnicity, deprivation and the presence of diabetes mellitus.

RESULTS

Of a total adult population of 211 980, 159 799 had a serum creatinine checked and 27 905 had an estimate of albuminuria. The estimated prevalence of CKD was 11.8%. 6.3% of total population had CKD stage G3a, 2.4% G3b, 0.8% G4, 0.2% G5, 1.8% A2 albuminuria and 0.3% A3 albuminuria. Increasing age, female sex, ethnic group, social deprivation and diabetes mellitus were associated with an increased risk of CKD. 11 351 patients had a diagnosis of diabetes mellitus and were almost universally tested (99.3%) for CKD. The presence of albuminuria was strongly correlated with ethnic group, male sex and living in a deprived area. The retrospective electronic health record study with associated selection and testing bias are potential limitations of the present study.

CONCLUSION

Chronic kidney disease prevalence in this region appears to be similar to other reported populations. The majority of those at risk for CKD were tested for reduced eGFR. The presence of albuminuria, an integral component of CKD diagnostic criteria, was under utilized in the non-diabetic population.

Type 2 diabetes in young adults in Central Auckland: demography and complications

BACKGROUND

Type 2 diabetes (T2D) in young adults is associated with a high risk of diabetes complications.

AIMS

To investigated the demography and the emergence of complications of young adults with T2D in the central Auckland region where there has been substantial immigration.

METHODS

In total, 310 young adults with T2D (<40 years) were registered with the Auckland Diabetes Centre in 2015. We documented demographic, anthropometric and metabolic variables and prevalence and the emergence of complications.

RESULTS

Three demographic groups accounted for 243 participants (78%): 135 (44%) were migrants of Asian or Pacific Island origin, diagnosed a median 9 years after migration at a mean age of 28 ± 6 years; 88 (29%) were New Zealand-born Pāsifika descent, with a high prevalence of morbid obesity and 37 (12%) had major mental illness or intellectual disability. At diagnosis, the median HbA1c was 80 mmol/mol, and in 28%, it was ≥100 mmol/mol. A median 6 years after diagnosis, 56% had some degree of retinopathy, with the prevalence related both to the duration of diabetes and glycaemic control (P = 0.001). Forty-four percent of subjects had abnormal albuminuria at diagnosis (12% with macroalbuminuria). Increased albuminuria was strongly associated with obesity (P = 0.002). The development of CKD stages 4-5 was related both to the severity of retinopathy and degree of albuminuria at diagnosis (P = 0.0001). Major cardiovascular events were related to the severity of retinopathy at diagnosis (P = 0.0001).

CONCLUSIONS

New migrants, New Zealand-born Pāsifika and patients with mental illness or an intellectual disability comprise the bulk of young onset T2D. The disease is aggressive, and by the age of 40, patients are already developing advanced complications.