Reclassification of chronic kidney disease patients for end-stage renal disease risk by proteinuria indexed to estimated glomerular filtration rate: multicentre prospective study in nephrology clinics

Artificial intelligence in chronic kidney diseases: methodology and potential applications

Chronic kidney disease (CKD) represents a significant global health challenge, characterized by kidney damage and decreased function. Its prevalence has steadily increased, necessitating a comprehensive understanding of its epidemiology, risk factors, and management strategies. While traditional prognostic markers such as estimated glomerular filtration rate (eGFR) and albuminuria provide valuable insights, they may not fully capture the complexity of CKD progression and associated cardiovascular (CV) risks.This paper reviews the current state of renal and CV risk prediction in CKD, highlighting the limitations of traditional models and the potential for integrating artificial intelligence (AI) techniques. AI, particularly machine learning (ML) and deep learning (DL), offers a promising avenue for enhancing risk prediction by analyzing vast and diverse patient data, including genetic markers, biomarkers, and imaging. By identifying intricate patterns and relationships within datasets, AI algorithms can generate more comprehensive risk profiles, enabling personalized and nuanced risk assessments.Despite its potential, the integration of AI into clinical practice faces challenges such as the opacity of some algorithms and concerns regarding data quality, privacy, and bias. Efforts towards explainable AI (XAI) and rigorous data governance are essential to ensure transparency, interpretability, and trustworthiness in AI-driven predictions.

Experiences of adults living with a kidney transplant-Effects on physical activity, physical function, and quality of life: A descriptive phenomenological study

BACKGROUND

Although kidney transplantation is the best treatment for kidney failure, scarce research has examined its effects on physical activity, physical function and quality of life.

OBJECTIVES

To investigate the experiences of a group of adults living with advanced kidney disease focusing on quality of life, physical activity and function and to see how findings differ in a group of kidney transplant recipients.

APPROACH

Individual semi-structured interviews were conducted with adults with advanced kidney disease (n = 10; 70.5 ± 8.9 years) and adults who had received a kidney transplant (n = 10; 50.7 ± 11.5 years; transplant age: 42.7 ± 20.9 months). Interviews were transcribed verbatim, thematically analysed and composite vignettes developed.

FINDINGS

Individuals with advanced kidney disease described a sense of loss and alteration to their life plans. Kidney transplant recipients reported increased freedom, independence and a return to near normality, with improved quality of life, physical activity and function compared with their pre-transplant lives. However, transplant recipients also described living with anxiety about the health of their transplant and fear it may fail.

CONCLUSION

Whilst adults living with advanced kidney disease often experience a reduced quality of life, physical activity and function, kidney transplantation can help facilitate a return to pre-disease levels of physical activity, physical function and quality of life. However, transplant recipients also reported living with anxiety around their new kidney failing. This study demonstrates the variability in the lived experiences of adults living with advanced kidney disease or a kidney transplant and highlights the need for patient-centred care.

Precision Nephrology in Patients with Diabetes and Chronic Kidney Disease

Diabetes is the leading cause of kidney failure and specifically, diabetic kidney disease (DKD) occurs in up to 30% of all diabetic patients. Kidney disease attributed to diabetes is a major contributor to the global burden of the disease in terms of clinical and socio-economic impact, not only because of the risk of progression to End-Stage Kidney Disease (ESKD), but also because of the associated increase in cardiovascular (CV) risk. Despite the introduction of novel treatments that allow us to reduce the risk of future outcomes, a striking residual cardiorenal risk has been reported. This risk is explained by both the heterogeneity of DKD and the individual variability in response to nephroprotective treatments. Strategies that have been proposed to improve DKD patient care are to develop novel biomarkers that classify with greater accuracy patients with respect to their future risk (prognostic) and biomarkers that are able to predict the response to nephroprotective treatment (predictive). In this review, we summarize the principal prognostic biomarkers of type 1 and type 2 diabetes and the novel markers that help clinicians to individualize treatments and the basis of the characteristics that predict an optimal response.

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

Low performance of prognostic tools for predicting death before dialysis in older patients with advanced CKD

INTRODUCTION

Chronic kidney disease (CKD) is a disease which is spreading worldwide, especially among older patients. Several prognostic scores have been developed to predict death in older CKD patients, but they have not been validated. We aimed to evaluate the existing risk scores for predicting death before dialysis start, identified via an in-depth review, in a cohort of elderly patients with advanced CKD.

METHODS

We performed a review to identify scores predicting death, developed in and applicable to CKD patients. Each score was evaluated with an absolute risk calculation from the patients' baseline characteristics. We used a French prospective multicentre cohort of elderly patients (> 75 years) with advanced CKD [estimated glomerular filtration rate (eGFR) < 20 mL/min/1.73 m²], recruited from nephrological centres, with a 5-year follow-up. The outcome considered was death before initiating dialysis. Discrimination [area under curve (AUC)], calibration and Brier score were calculated for each score at its time frame.

RESULTS

Our review found 6 equations predicting death before dialysis in CKD patients. Four of these (GOLDFARB, BANSAL, GRAMS 2 and 4 years) were evaluated. The validation cohort (Parcours de Soins des Personnes Âgées Parcours de Soins des Personnes Âgées, PSPA) included 573 patients, with a median age of 82 years and a median eGFR of 13 mL/min/1.73 m². At the end of follow-up, 287 (50%) patients had started dialysis and 238 (41%) patients had died before dialysis. The four equations evaluated showed average discrimination (AUC 0.61-0.70) and, concerning calibration, a global overestimation of the risk of death.

DISCUSSION

The available scores predicting death before dialysis showed low performance among older patients with advanced CKD in a French multicentre cohort, indicating the need to upgrade them or develop new scores for this population.

The experience of being a mother with end stage renal disease: A qualitative study of women receiving treatment at an ambulatory dialysis unit

Background

End-stage kidney disease (ESKD) has considerable effects on the quality of life, impairing daily activities and leading to lifestyle changes. The purpose of this study was therefore to explore the experience of motherhood and taking care of children in women with ESKD.

Methods

A qualitative exploratory study was conducted based on an interpretive framework. Participants were recruited using non-probabilistic purposeful sampling. In total, 14 women with ESKD were included, who were treated at the dialysis unit of a Spanish hospital. In-depth interviews (unstructured and semi-structured interviews) and researchers’ field notes were used to collect the data. A systematic text condensation analysis was performed. The techniques performed and application procedures used to control trustworthiness were credibility, transferability, dependability, and confirmability.

Results

Three themes emerged from the data. “Coping with being a mother” described how women are faced with the decision to become mothers and assess the risks of pregnancy. The second theme, called “Children and the experience of illness”, highlighted the women’s struggle to prevent the disease from affecting their children emotionally or disrupting their lives. The third theme, “Fear of genetic transmission”, was based on the women’s fear of passing the disease on to their children.

Conclusions

Deciding to become a mother and taking care of children represents a challenge for women with ESKD, coupled with the losses in their lives caused by the disease. These findings are only relevant to women on dialysis.

Association between Inguinal Hernia and Arterial Disease: A Preliminary Report

Simple Summary

While the association between venous disease and inguinal hernia has been well demonstrated, there is less evidence concerning the association between arterial diseases (AD), such as carotid stenosis, peripheral artery disease and abdominal aortic aneurysms, and inguinal hernia. We surprisingly found that the prevalence of AD is large, being higher than 40% in our study cohort. Moreover, patients with AD as compared to those without AD are characterized by additional other comorbidities such as greater albuminuria, higher frequency of a smoking habit and older age. Hence, we provided a characterization of patients with inguinal hernia with respect to concomitant presence of AD.

Abstract

Background: Inguinal hernia (IH) is a major problem in general surgery and its prevalence is increasing. The presence of hernias has been associated with a wide spectrum of venous diseases, with the involvement of imbalances in collagen and extracellular matrix deposition and metalloproteinases dysfunction. We aimed to evaluate whether the association between IH and vascular diseases is also present with respect to arterial diseases. Methods: We designed a cross-sectional observational study enrolling consecutive patients undergoing surgical repair of IH. Arterial diseases (AD) considered were carotid stenosis, peripheral artery disease and abdominal aortic aneurysms. Results: Study population consisted of 70 patients. Mean age was 63.2 ± 4.7 years. Prevalence of AD was 42.9% in the whole cohort. AD patients were older (p = 0.015), and more frequently had hypertension (p = 0.001) and active smoking habits (p = 0.001) than the no-AD group. Albumin-to-creatinine ratio (ACR) was higher in AD than in no-AD patients (p < 0.001). At multivariable analysis, increased ACR (odds ratio, OR: 1.14, p < 0.001), old age (OR: 1.25, p = 0.001) and a smoking habit (OR: 3.20, p = 0.001) were significant correlates for the presence of AD. Conclusions: Prevalence of AD in patients with IH is non-negligible. Old age, a smoking habit and an abnormal excretion of urine albumin are associated with the presence of AD in these patients. Future studies are needed to gain more insights into the pathogenic mechanisms underlying this association, exploring also the specific role of metalloproteinases.

The Impact of Chronic Kidney Disease on Peripheral Artery Disease and Peripheral Revascularization

Chronic kidney disease (CKD) is a clinical condition characterized by high morbidity and mortality. Globally, CKD is also increasing in prevalence and incidence. The two principal kidney measures namely estimated glomerular filtration rate (eGFR) and albuminuria have been found to be predictors of renal and cardiovascular (CV) endpoints including peripheral artery disease (PAD). The prevalence of PAD was increased in CKD patients and, particularly, in patients with more severe CKD stages. Despite the fact that revascularization strategies are suitable in CKD patients in similar fashion to non-CKD patients, few CKD patients underwent these procedures. In fact, if it is true that revascularization improves prognosis in PAD patients irrespective of baseline eGFR, it was also demonstrated that CKD patients, who underwent revascularization, were at higher risk for amputations, mortality, re-intervention and perioperative complications. With the present review article, we have examined the association between CKD, PAD and peripheral revascularization highlighting data about epidemiology, pathophysiologic mechanisms, and results from previous observational and intervention studies. We have also examined the future perspectives and challenges of research around the association between CKD and PAD.

15-year-change of phenotype and prognosis in non-dialysis CKD patients referred to a nephrology clinic

PURPOSE

Changes over time of phenotype and prognosis in CKD patients starting nephrology care are undefined. This information is critical to correctly plan and optimize healthcare resources and clinical management in tertiary care.

METHODS

We performed a long-term observational cohort study including 2,866 non-dialysis CKD patients newly referred to our nephrology clinic from 2004 to 2018. Three cohorts were constituted based on 5-year calendar intervals (2004-2008, 2009-2013, and 2014-2018). The changes over time of main demographic, clinical and laboratory characteristics were compared among the three cohorts. We also compared between cohorts the risk of renal death (combined endpoint of renal replacement therapy-RRT, or death before RRT) as well as of the single components (RRT or death).

RESULTS

Across the three cohorts, we detected a significant increase in the prevalence of age ≥ 75 years (from 22.0 to 28.4%), male gender (from 53.1 to 62.1%), diabetes (from 32.6 to 39.5%), severe proteinuria ≥ 500 mg/24 h (from 46.9 to 52.4%). Mean eGFR at referral declined from 56.8 ± 27.0 to 49.6 ± 26.1 mL/min/1.73m². Incidence of renal death significantly declined over time (5.36, 3.22 and 4.54/100 pts-year in 2004-2008, 2009-2013 and 2014-2018 cohorts, respectively). As compared with patients referred in 2004-2008, adjusted risk of renal death was lower in patients referred in 2009-2013 (HR 0.49, 95%CI 0.34-0.69) and 2014-2018 (HR 0.61, 95%CI 0.45-0.84). Similar results were obtained for RRT, while mortality did not change over time.

CONCLUSIONS

In the last 15 years, phenotype of newly referred CKD patients has remarkably changed with increasing frequency of older patients and more severe disease; however, renal survival improved suggesting greater efficacy of nephrology care.

Diabetic kidney disease: new clinical and therapeutic issues. Joint position statement of the Italian Diabetes Society and the Italian Society of Nephrology on "The natural history of diabetic kidney disease and treatment of hyperglycemia in patients with type 2 diabetes and impaired renal function"

Aims

This joint document of the Italian Diabetes Society and the Italian Society of Nephrology reviews the natural history of diabetic kidney disease (DKD) in the light of the recent epidemiological literature and provides updated recommendations on anti-hyperglycemic treatment with non-insulin agents.

Data Synthesis

Recent epidemiological studies have disclosed a wide heterogeneity of DKD. In addition to the classical albuminuric phenotype, two new albuminuria-independent phenotypes have emerged, i.e., “nonalbuminuric renal impairment” and “progressive renal decline”, suggesting that DKD progression toward end-stage kidney disease (ESKD) may occur through two distinct pathways, albuminuric and nonalbuminuric. Several biomarkers have been associated with decline of estimated glomerular filtration rate (eGFR) independent of albuminuria and other clinical variables, thus possibly improving ESKD prediction. However, the pathogenesis and anatomical correlates of these phenotypes are still unclear. Also the management of hyperglycemia in patients with type 2 diabetes and impaired renal function has profoundly changed during the last two decades. New anti-hyperglycemic drugs, which do not cause hypoglycemia and weight gain and, in some cases, seem to provide cardiorenal protection, have become available for treatment of these individuals. In addition, the lowest eGFR safety thresholds for some of the old agents, particularly metformin and insulin secretagogues, have been reconsidered.

Conclusions

The heterogeneity in the clinical presentation and course of DKD has important implications for the diagnosis, prognosis, and possibly treatment of this complication. The therapeutic options for patients with type 2 diabetes and impaired renal function have substantially increased, thus allowing a better management of these individuals.

Long-term blood pressure behavior and progression to end-stage renal disease in patients with immunoglobulin A nephropathy: a single-center observational study in Italy

BACKGROUND

Antihypertensive treatment by the use of RAAS inhibitors (RAAS-is) is of paramount importance in the management of slowly progressive IgA nephropathy (IgAN). With the aim of better understanding the relationship between BP behavior and progression, we looked at time-averaged SBP and time-averaged proteinuria and renal outcome in a single-center cohort of IgAN patients.

METHODS

Among 248 consecutive patients referred to the Clinic of Nephrology of San Martino Hospital from 1996 to 2018 for native renal biopsy with a diagnosis of IgAN, we retrospectively analyzed 145 with available data at baseline and during follow-up. All patients received Supportive Care, 39% were on RAAS-is alone, 45% plus steroids, and 16% plus steroids and immunosuppressors. Renal replacing treatment (RRT) was the primary endpoint.

RESULTS

During a mean follow-up of 67 ± 6 months, 23% of study patients (n = 33) progressed to RRT and 6% (n = 9) died. Patients who reached the renal endpoint, had lower baseline eGFR and higher proteinuria and proteinuria indexed at baseline. Moreover, they had higher TA-SBP (139 ± 17 vs. 130 ± 13, P = 0.0016). The incidence of RRT was higher in IgAN patients in the highest time-averaged SBP tertile as compared with the others (32 vs. 23 vs. 9%, χ 6.8, P = 0.033). After adjusting for baseline SBP, baseline and time-averaged proteinuria indexed, MEST-C score, and treatment, the association between TA-SBP and RRT persisted.

CONCLUSION

Time-averaged low BP values were independently associated to a decreased risk of renal progression in IgAN with no evidence of a J-curve relationship even at SBP levels below 125 mmHg.

Role of Albuminuria in Detecting Cardio-Renal Risk and Outcome in Diabetic Subjects

The clinical significance of albuminuria in diabetic subjects and the impact of its reduction on the main cardiorenal outcomes by different drug classes are among the most interesting research focuses of recent years. Although nephrologists and cardiologists have been paying attention to the study of proteinuria for years, currently among diabetics, increased urine albumin excretion ascertains the highest cardio-renal risk. In fact, diabetes is a condition by itself associated with a high-risk of both micro/macrovascular complications. Moreover, proteinuria reduction in diabetic subjects by several treatments lowers both renal and cardiovascular disease progression. The 2019 joint ESC-EASD guidelines on diabetes, prediabetes and cardiovascular (CV) disease assign to proteinuria a crucial role in defining CV risk level in the diabetic patient. In fact, proteinuria by itself allows the diabetic patient to be staged at very high CV risk, thus affecting the choice of anti-hyperglycemic drug class. The purpose of this review is to present a clear update on the role of albuminuria as a cardio-renal risk marker, starting from pathophysiological mechanisms in support of this role. Besides this, we will show the prognostic value in observational studies, as well as randomized clinical trials (RCTs) demonstrating the potential improvement of cardio-renal outcomes in diabetic patients by reducing proteinuria.

Aortic Aneurysms, Chronic Kidney Disease and Metalloproteinases

Metalloproteinases (MPs) are proteolytic enzymes involved in extracellular matrix deposition, regulation of cellular signals of inflammation, proliferation, and apoptosis. Metalloproteinases are classified into three families: Matrix-MPs (MMPs), A-Disintegrin-and-Metalloprotease (ADAMs), and the A-Disintegrin-and-Metalloproteinase-with-Thrombospondin-1-like-Domains (ADAMTS). Previous studies showed that MPs are involved in the development of aortic aneurysms (AA) and, concomitantly, in the onset of chronic kidney disease (CKD). CKD has been, per se, associated with an increased risk for AA. The aim of this review is to examine the pathways that may associate MPs with CKD and AA. Several MMPs, such as MMP-2, -8, -9, and TIMP-1 have been shown to damage the AA wall and to have a toxic effect on renal tubular cells, leading to fibrosis. Similarly, ADAM10 and 17 have been shown to degrade collagen in the AA wall and to worsen kidney function via pro-inflammatory stimuli, the impairment of the Renin-Angiotensin-Aldosterone System, and the degradation of structural proteins. Moreover, MMP-2 and -9 inhibitors reduced aneurysm growth and albuminuria in experimental and human studies. It would be important, in the future, to expand research on MPs from both a prognostic, namely, to refine risk stratification in CKD patients, and a predictive perspective, likely to improve prognosis in response to targeted treatments.

Cardiovascular disease-related mortality risk in end stage renal disease and type 2 diabetes: A systematic review

Background

Patients with uncontrolled type 2 diabetes can have microvascular and macrovascular complications, including renal impairment and cardiovascular diseases. However, it is unknown how diabetes and renal disease could influence cardiovascular mortality.

Objective

This study aims at examining the medical literature to evaluate the risk of cardiovascular death in concomitant end stage renal disease with type 2 diabetes.

Method

Medical literature was reviewed through Medline, PubMed, Embase, and Ovid database in the duration between 2009 and 2019. Searching terms included were a combination of "type 2 diabetes mellitus" AND "end-stage renal disease" AND "cardiovascular mortality". Following this, results were filtered to include only original research articles investigating cardiovascular mortality in concomitant diabetes and end-stage renal disease. Selected trials mentioned diabetes control as well as the follow-up duration of the included patients.

Result

A total of 1508 articles were retrieved. Following the exclusion of articles on animals and including only trials on humans, 32 articles appeared. A total of eight articles were identified as eligible, covering a total of 2,06,492 diabetic patients with end-stage renal disease. All the studies were prospective studies, except for three studies that were retrospective.

Conclusion

There is an elevated cardiovascular mortality risk in concomitant type 2 diabetes mellitus and end-stage renal disease, especially with uncontrolled blood glucose levels.

The Role of Prognostic and Predictive Biomarkers for Assessing Cardiovascular Risk in Chronic Kidney Disease Patients

Chronic kidney disease (CKD) is currently defined as the presence of proteinuria and/or an eGFR < 60 mL/min/1.73m² on the basis of the renal diagnosis. The global dimension of CKD is relevant, since its prevalence and incidence have doubled in the past three decades worldwide. A major complication that occurs in CKD patients is the development of cardiovascular (CV) disease, being the incidence rate of fatal/nonfatal CV events similar to the rate of ESKD in CKD. Moreover, CKD is a multifactorial disease where multiple mechanisms contribute to the individual prognosis. The correct development of novel biomarkers of CV risk may help clinicians to ameliorate the management of CKD patients. Biomarkers of CV risk in CKD patients are classifiable as prognostic, which help to improve CV risk prediction regardless of treatment, and predictive, which allow the selection of individuals who are likely to respond to a specific treatment. Several prognostic (cystatin C, cardiac troponins, markers of inflammation, and fibrosis) and predictive (genes, metalloproteinases, and complex classifiers) biomarkers have been developed. Despite previous biomarkers providing information on the pathophysiological mechanisms of CV risk in CKD beyond proteinuria and eGFR, only a minority have been adopted in clinical use. This mainly depends on heterogeneous results and lack of validation of biomarkers. The purpose of this review is to present an update on the already assessed biomarkers of CV risk in CKD and examine the strategies for a correct development of biomarkers in clinical practice. Development of both predictive and prognostic biomarkers is an important task for nephrologists. Predictive biomarkers are useful for designing novel clinical trials (enrichment design) and for better understanding of the variability in response to the current available treatments for CV risk. Prognostic biomarkers could help to improve risk stratification and anticipate diagnosis of CV disease, such as heart failure and coronary heart disease.

Precision Nephrology Is a Non-Negligible State of Mind in Clinical Research: Remember the Past to Face the Future

CKD is a major public health problem. It is characterized by a multitude of risk factors that, when aggregated, can strongly modify outcome. While major risk factors, namely, albuminuria and low estimated glomerular filtration rate (eGFR) have been well analyzed, a large variability in disease progression still remains. This happens because (1) the weight of each risk factor varies between populations (general population or CKD cohort), countries, and single individuals and (2) response to nephroprotective drugs is so heterogeneous that a non-negligible part of patients maintains a high cardiorenal risk despite optimal treatment. Precision nephrology aims at individualizing cardiorenal prognosis and therapy. The purpose of this review is to focus on the risk stratification in different areas, such as clinical practice, population research, and interventional trials, and to describe the strategies used in observational or experimental studies to afford individual-level evidence. The future of precision nephrology is also addressed. Observational studies can in fact provide more adequate findings by collecting more information on risk factors and building risk prediction models that can be applied to each individual in a reliable fashion. Similarly, new clinical trial designs can reduce the individual variability in response to treatment and improve individual outcomes.

Contribution of Predictive and Prognostic Biomarkers to Clinical Research on Chronic Kidney Disease

Chronic kidney disease (CKD), defined as the presence of albuminuria and/or reduction in estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2, is considered a growing public health problem, with its prevalence and incidence having almost doubled in the past three decades. The implementation of novel biomarkers in clinical practice is crucial, since it could allow earlier diagnosis and lead to an improvement in CKD outcomes. Nevertheless, a clear guidance on how to develop biomarkers in the setting of CKD is not yet available. The aim of this review is to report the framework for implementing biomarkers in observational and intervention studies. Biomarkers are classified as either prognostic or predictive; the first type is used to identify the likelihood of a patient to develop an endpoint regardless of treatment, whereas the second type is used to determine whether the patient is likely to benefit from a specific treatment. Many single assays and complex biomarkers were shown to improve the prediction of cardiovascular and kidney outcomes in CKD patients on top of the traditional risk factors. Biomarkers were also shown to improve clinical trial designs. Understanding the correct ways to validate and implement novel biomarkers in CKD will help to mitigate the global burden of CKD and to improve the individual prognosis of these high-risk patients.

Urinary Neutrophil Gelatinase-Associated Lipocalin (NGAL) Predicts Renal Function Decline in Patients With Glomerular Diseases

Objective

Available biomarkers for monitoring primary glomerulonephritides (GNs), often lack the ability to assess longitudinal changes and have great variability with poor sensitivity. Accruing evidence has demonstrated that Neutrophil Gelatinase-Associated Lipocalin (NGAL), holds promising capacities in predicting renal function worsening in various renal diseases. We aimed at analyzing urinary NGAL (uNGAL) levels in a cohort of individuals with biopsy-proven GNs in order to evaluate its ability to reflect the entity of renal damage and to predict disease evolution overtime.

Methods

We enrolled 61 consecutive GNs patients still naïve to pathogenic therapy. uNGAL levels were measured at baseline and patients prospectively followed until the manifestation of a combined outcome of doubling of baseline serum creatinine and/or end-stage kidney disease requiring permanent dialysis support.

Results

Median uNGAL levels were 107[35–312] ng/mL. At univariate and multivariate analyses an inverse correlation was found between eGFR and uNGAL levels (p = 0.001). Progressor subjects showed exceedingly increased baseline uNGAL values as compared with non-progressors (p < 0.001). Twenty-one patients (34%) reached the composite renal endpoint. Subjects with uNGAL values above the optimal, ROC-derived, cut-off of 107 ng/mL experienced a more rapid progression to the renal endpoint (p < 0.001; HR: 5.47; 95% CI 2.31–12.95) with a mean follow-up time to progression of 73.4 vs 83.5 months.

Conclusion

In patients affected by primary glomerulonephritides, uNGAL may represent a real-time indicator of renal damage and an independent predictor of renal disease progression. Further studies on larger populations are warranted to confirm these findings.

Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients

Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transplantation, is crucial for patient's well-being and for successful management of the condition. In this paper, we explore the possibilities of creating forecasting models to predict the onset of RRT 3, 6, and 12 months from the time of the patient's first diagnosis with CKD, using only the comorbidities data from National Health Insurance from Taiwan. The goal of this study was to see whether a limited amount of data (including comorbidities but not considering laboratory values which are expensive to obtain in low- and medium-income countries) can provide a good basis for such predictive models. On the other hand, in developed countries, such models could allow policy-makers better planning and allocation of resources for treatment. Using data from 8,492 patients, we obtained the area under the receiver operating characteristic curve (AUC) of 0.773 for predicting RRT within 12 months from the time of CKD diagnosis. The results also show that there is no additional advantage in focusing only on patients with diabetes in terms of prediction performance. Although these results are not as such suitable for adoption into clinical practice, the study provides a strong basis and a variety of approaches for future studies of forecasting models in healthcare.

Main Risk Factors Related to Activities of Daily Living in Non-Dialysis Patients with Chronic Kidney Disease Stage 3-5: A Case-Control Study

Introduction

Elderly people are at increased risk of falls, disability and death due to reduced functional reserve, decline in multiple systems functions, which affects their activities of daily living (ADL) and eventually develop into frailty. The ADL assessment is conducive to early detection to avoid further serious situations. Previous studies on patients’ activities of daily living with chronic kidney disease (CKD) are mainly focused on dialysis patients. Little information is available on non-dialysis patients.

Patients and Methods

A total of 303 elderly patients with CKD stage 3–5 who were admitted to our hospital were selected. ADL evaluation was performed on patients at admission, with Barthel index (BI) as the evaluation tool. They were divided into two groups based on BI (≥60 and <60). Demographic information, lifestyle and clinical profile were collected. The risk factors related to ADL were analyzed by univariate and multivariate models.

Results

The data of 303 patients enrolled in this study were analyzed. The average age of patients was 84.48± 7.14 years and 62.05% were male. There were 88 patients (29.04%) in BI <60 group and 215 patients (70.96%) in the BI ≥60 group. The average age of subjects in the two groups was 87.47 ± 5.85 years and 83.26± 7.28 years, respectively. On univariate analysis, ADL impairment was associated with many factors, such as age, body mass index, blood lipid, heart rate, smoking history, Charlson comorbidity index (CCI), hemoglobin, serum albumin, BNP, eGFR, etc. Multivariate logistic regression showed that age (OR 1.08, 95% CI 1.00–1.17, P=0.0390), Charlson comorbidity index (OR 4.75, 95% CI 1.17–19.30, P=0.0295), and serum albumin (OR 0.80, 95% CI 0.70–0.92, P=0.0012) were the independent risk factors of ADL impairment.

Conclusion

Decline of ADL in CKD patients was independently correlated with age, Charlson comorbidity index and serum albumin. ADL and its influential factors in the elderly CKD patients deserve further attention.

Treatment Costs for Patients with Chronic Kidney Disease Who Received Multidisciplinary Care in a District Hospital in Thailand

Aim

To estimate direct medical treatment costs in patients with pre-dialysis chronic kidney disease (CKD) in a district hospital and to analyze the factors that affected the treatment costs.

Patients and Methods

Data were retrospectively retrieved from the hospital database in the period from January 2015 to December 2017. Patients who were diagnosed with CKD and had visited ambulatory care services at least two times during the index year (January to December 2015) were included. Patients' data were excluded if they had cancer, had received renal replacement therapy, or had been referred to receive treatment at other hospitals. Treatment costs based on the providers' perspectives in the first and second years after the index year were assessed. Descriptive statistics were used to analyze patients' characteristics, and multiple linear regression was used to analyze the factors in the cost model.

Results

Data of 212 patients with CKD stage G3a, G3b, or G4 who met inclusion and exclusion criteria were included for analysis. Average costs for treatment in year 1 and year 2 were not statistically different. Total cost was 5701.34 Thai Baht (THB) per year. The total cost for patients with CKD stage G4 was two times greater than for patients with CKD stage G3. Costs were increased for longer hospitalization, more frequent ambulatory visits, having diabetes mellitus or dyslipidemia as a comorbidity, and uncontrolled fasting blood glucose (FBG). A cost model with R ²=0.906 was provided. Significant predictors were length of stay, ambulatory visits, diabetes mellitus, dyslipidemia, serum creatinine, FBG, and body mass index.

Conclusion

Total annual treatment costs for the 2 years were not different. A more advanced stage of CKD, having diabetes mellitus or dyslipidemia as comorbidities, and uncontrolled FBG were significantly associated with increased costs for treatment in patients with pre-dialysis CKD.

Atherosclerotic-nephropathy: an updated narrative review

The increased prevalence of chronic kidney disease (CKD) in elderly patients recognizes, as main cause, the long-term exposure to atherosclerosis and hypertension. Chronic ischemic damage due to critical renal arterial stenosis induces oxidative stress and intra-renal inflammation, resulting in fibrosis and microvascular remodelling, that is the histological picture of atherosclerotic renal vascular disease (ARVD). The concomitant presence of a long history of hypertension may generate intimal thickening and luminal narrowing of renal arteries and arterioles, glomerulosclerosis, interstitial fibrosis and tubular atrophy, more typically expression of hypertensive nephropathy. These complex mechanisms contribute to the development of CKD and the progression to End Stage Kidney Disease. In elderly CKD patients, the distinction among these nephropathies may be problematic; therefore, ischemic and hypertensive nephropathies can be joined in a unique clinical syndrome defined as atherosclerotic nephropathy. The availability of novel diagnostic procedures, such as intra-vascular ultrasound and BOLD-MRI, in addition to traditional imaging, have opened new scenarios, because these tools allow to identify ischemic lesions responsive to renal revascularization. Indeed, although trials have deflated the role of renal revascularization on the renal outcomes, it should be still used to avoid dialysis initiation and/or to reduce blood pressure in selected elderly patients at high risk. Nonetheless, lifestyle modifications (smoking cessation, increased physical activity), statins and antiplatelet use, as well as cautious use of renin-angiotensin system inhibitors, remain the main therapeutic approach aimed at slowing the renal damage progression. Mesenchymal stem cells and Micro-RNA are promising target of anti-fibrotic therapy, which might provide potential benefit in ARVD patients, though safety and efficacy profile in humans is unknown too.

The Association of Matrix Metalloproteinases with Chronic Kidney Disease and Peripheral Vascular Disease: A Light at the End of the Tunnel?

: Chronic Kidney Disease (CKD) represents a risk factor for fatal and nonfatal cardiovascular (CV) events, including peripheral vascular disease (PVD). This occurs because CKD encompasses several factors that lead to poor prognoses, mainly due to a reduction of the estimated glomerular filtration rate (eGFR), the presence of proteinuria, and the uremic inflammatory milieu. The matrix metalloproteinases (MMPs) are a group of zinc-containing endopeptidases implicated in extracellular matrix (ECM) remodeling, a systemic process in tissue homeostasis. MMPs play an important role in cell differentiation, angiogenesis, inflammation, and vascular damage. Our aim was to review the published evidence regarding the association between MMPs, PVD, and CKD to find possible common pathophysiological mechanisms. MMPs favor ECM deposition through the glomeruli, and start the shedding of cellular junctions and epithelial-mesenchymal transition in the renal tubules. MMP-2 and -9 have also been associated with the presence of systemic vascular damage, since they exert a pro-inflammatory and proatherosclerotic actions. An imbalance of MMPs was found in the context of PVD, where MMPs are predictors of poor prognoses in patients who underwent lower extremity revascularization. MMP circulating levels are increased in both conditions, i.e., that of CKD and PVD. A possible pathogenic link between these conditions is represented by the enhanced production of transforming growth factor-β that worsens vascular calcifications and atherosclerosis and the development of proteinuria in patients with increased levels of MMPs. Proteinuria has been recognized as a marker of systemic vascular damage, and this may explain in part the increase in CV risk that is manifest in patients with CKD and PVD. In conclusion, MMPs can be considered a useful tool by which to stratify CV risk in patients with CKD and PVD. Further studies are needed to investigate the causal-relationships between MMPs, CKD, and PVD, and to optimize their prognostic and predictive (in response to treatments) roles.

Unraveling Cardiovascular Risk in Renal Patients: A New Take on Old Tale

Chronic kidney disease (CKD), defined by an estimated glomerular filtration rate <60 ml/min/1.73 m² and/or an increase in urine protein excretion (i.e., albuminuria), is an important public health problem. Prevalence and incidence of CKD have risen by 87 and 89%, worldwide, over the last three decades. The onset of either albuminuria and eGFR reduction has found to predict higher cardiovascular (CV) risk, being this association strong, independent from traditional CV risk factors and reproducible across different setting of patients. Indeed, this relationship is present not only in high risk cohorts of CKD patients under regular nephrology care and in those with hypertension or type 2 diabetes, but also in general, otherwise healthy population. As underlying mechanisms of damage, it has hypothesized and partially proved that eGFR reduction and albuminuria can directly promote endothelial dysfunction, accelerate atherosclerosis and the deleterious effects of hypertension. Moreover, the predictive accuracy of risk prediction models was consistently improved when eGFR and albuminuria have been added to the traditional CV risk factors (i.e., Framingham risk score). These important findings led to consider CKD as an equivalent CV risk. Although it is hard to accept this definition in absence of additional reports from scientific Literature, a great effort has been done to reduce the CV risk in CKD patients. A large number of clinical trials have tested the effect of drugs on CV risk reduction. The targets used in these trials were different, including blood pressure, lipids, albuminuria, inflammation, and glucose. All these trials have determined an overall better control of CV risk, performed by clinicians. However, a non-negligible residual risk is still present and has been attributed to: (1) missed response to study treatment in a consistent portion of patients, (2) role of many CV risk factors in CKD patients not yet completely investigated. These combined observations provide a strong argument that kidney measures should be regularly included in individual prediction models for improving CV risk stratification. Further studies are needed to identify high risk patients and novel therapeutic targets to improve CV protection in CKD patients.

Diabetic kidney disease: New clinical and therapeutic issues. Joint position statement of the Italian Diabetes Society and the Italian Society of Nephrology on "The natural history of diabetic kidney disease and treatment of hyperglycemia in patients with type 2 diabetes and impaired renal function"

AIMS

This joint document of the Italian Diabetes Society and the Italian Society of Nephrology reviews the natural history of diabetic kidney disease (DKD) in the light of the recent epidemiological literature and provides updated recommendations on anti-hyperglycemic treatment with non-insulin agents.

DATA SYNTHESIS

Recent epidemiological studies have disclosed a wide heterogeneity of DKD. In addition to the classical albuminuric phenotype, two new albuminuria-independent phenotypes have emerged, i.e., "nonalbuminuric renal impairment" and "progressive renal decline", suggesting that DKD progression toward end-stage kidney disease (ESKD) may occur through two distinct pathways, albuminuric and nonalbuminuric. Several biomarkers have been associated with decline of estimated glomerular filtration rate (eGFR) independent of albuminuria and other clinical variables, thus possibly improving ESKD prediction. However, the pathogenesis and anatomical correlates of these phenotypes are still unclear. Also the management of hyperglycemia in patients with type 2 diabetes and impaired renal function has profoundly changed during the last two decades. New anti-hyperglycemic drugs, which do not cause hypoglycemia and weight gain and, in some cases, seem to provide cardiorenal protection, have become available for treatment of these individuals. In addition, the lowest eGFR safety thresholds for some of the old agents, particularly metformin and insulin secretagogues, have been reconsidered.

CONCLUSIONS

The heterogeneity in the clinical presentation and course of DKD has important implications for the diagnosis, prognosis, and possibly treatment of this complication. The therapeutic options for patients with type 2 diabetes and impaired renal function have substantially increased, thus allowing a better management of these individuals.

Comparison and development of machine learning tools in the prediction of chronic kidney disease progression

BACKGROUND

Urinary protein quantification is critical for assessing the severity of chronic kidney disease (CKD). However, the current procedure for determining the severity of CKD is completed through evaluating 24-h urinary protein, which is inconvenient during follow-up.

OBJECTIVE

To quickly predict the severity of CKD using more easily available demographic and blood biochemical features during follow-up, we developed and compared several predictive models using statistical, machine learning and neural network approaches.

METHODS

The clinical and blood biochemical results from 551 patients with proteinuria were collected. Thirteen blood-derived tests and 5 demographic features were used as non-urinary clinical variables to predict the 24-h urinary protein outcome response. Nine predictive models were established and compared, including logistic regression, Elastic Net, lasso regression, ridge regression, support vector machine, random forest, XGBoost, neural network and k-nearest neighbor. The AU-ROC, sensitivity (recall), specificity, accuracy, log-loss and precision of each of the models were evaluated. The effect sizes of each variable were analysed and ranked.

RESULTS

The linear models including Elastic Net, lasso regression, ridge regression and logistic regression showed the highest overall predictive power, with an average AUC and a precision above 0.87 and 0.8, respectively. Logistic regression ranked first, reaching an AUC of 0.873, with a sensitivity and specificity of 0.83 and 0.82, respectively. The model with the highest sensitivity was Elastic Net (0.85), while XGBoost showed the highest specificity (0.83). In the effect size analyses, we identified that ALB, Scr, TG, LDL and EGFR had important impacts on the predictability of the models, while other predictors such as CRP, HDL and SNA were less important.

CONCLUSIONS

Blood-derived tests could be applied as non-urinary predictors during outpatient follow-up. Features in routine blood tests, including ALB, Scr, TG, LDL and EGFR levels, showed predictive ability for CKD severity. The developed online tool can facilitate the prediction of proteinuria progress during follow-up in clinical practice.

Kidney Injury Molecule 1 (KIM-1) as an Early Predictor for Acute Kidney Injury in Post-Cardiopulmonary Bypass (CPB) in Open Heart Surgery Patients

INTRODUCTION

Postoperative acute kidney injury is associated with a higher mortality, a more complicated hospital course with longer hospital stay. Urinary kidney injury molecule 1 may play an important role as an early predictor of acute kidney injury post-cardiopulmonary in open heart surgery.

METHODS

We evaluated 45 patients who underwent open heart surgery from January 2016 to June 2016. Both urinary kidney injury molecule 1 and serum creatinine were evaluated before operation and 3hs and 24hs after operation. Acute kidney injury was diagnosed according to Kidney Disease: Improving Global Outcomes, 2012 guidelines.

RESULTS

In this study, 27 patients developed acute kidney injury. The three hour-post-surgery urinary kidney injury molecule 1 was significantly higher in the acute kidney injury group (P<0.015) and, at the same time, we did not find any significant difference in the serum creatinine levels between the two groups.

CONCLUSION

Although serum creatinine is still the gold standard for diagnosis of acute kidney injury searching for other new markers is mandatory. Urinary kidney injury molecule 1 can be used as simple noninvasive and specific biomarker for early diagnosis of acute kidney injury.