Strategies to improve monitoring disease progression, assessing cardiovascular risk, and defining prognostic biomarkers in chronic kidney disease

Associations of Urine and Plasma Metabolites with Kidney Failure and Death in a CKD Cohort

RATIONALE & OBJECTIVE

Biomarkers that enable better identification of persons with chronic kidney disease (CKD) who are at higher risk for disease progression and adverse events are needed. This study sought to identify urine and plasma metabolites associated with progression of kidney disease.

STUDY DESIGN

Prospective metabolome-wide association study.

SETTING & PARTICIPANTS

Persons with CKD enrolled in the German CKD Study (GCKD) with metabolite measurements; with external validation within the Atherosclerosis Risk in Communities Study.

EXPOSURES

1,513 urine and 1,416 plasma metabolites (Metabolon, Inc.) measured at study entry using untargeted mass spectrometry.

OUTCOMES

Main endpoints were kidney failure (KF), and a composite endpoint of KF, eGFR <15 mL/min/1.73m2, or 40% decline in eGFR (CKE). Death from any cause was a secondary endpoint. After a median of 6.5 years follow-up, 500 persons experienced KF, 1,083 experienced CKE and 680 died.

ANALYTICAL APPROACH

Time-to-event analyses using multivariable proportional hazard regression models in a discovery-replication design, with external validation.

RESULTS

5,088 GCKD participants were included in analyses of urine metabolites and 5,144 in analyses of plasma metabolites. Among 182 unique metabolites, 30 were significantly associated with KF, 49 with CKE, and 163 with death. The strongest association with KF was observed for plasma hydroxyasparagine (hazard ratio: 1.95, 95% confidence interval: 1.68-2.25). An unnamed metabolite measured in plasma and urine was significantly associated with KF, CKE, and death. External validation of the identified associations of metabolites with KF or CKE revealed direction-consistency for 88% of observed associations. Selected associations of 18 metabolites with study outcomes have not been previously reported.

LIMITATIONS

Use of observational data and semi-quantitative metabolite measurements at a single time point.

CONCLUSIONS

The observed associations between metabolites and KF, CKE or death in persons with CKD confirmed previously reported findings and also revealed several associations not previously described. These findings warrant confirmatory research in other study cohorts.

Focus on the Prevention of Acute Limb Ischemia: Centrality of the General Practitioner from the Point of View of the Internist

The thrombotic mechanism, being common to peripheral arterial disease (PAD), acute myocardial infarction (AMI), and stroke, is responsible for the highest number of deaths in the western world. However, while much has been done for the prevention, early diagnosis, therapy of AMI and stroke, the same cannot be said for PAD, which is a negative prognostic indicator for cardiovascular death. Acute limb ischemia (ALI) and chronic limb ischemia (CLI) are the most severe manifestations of PAD. They both are defined by the presence of PAD, rest pain, gangrene, or ulceration and we consider ALI if symptoms last less than 2 weeks and CLI if they last more than 2 weeks. The most frequent causes are certainly atherosclerotic and embolic mechanisms and, to a lesser extent, traumatic or surgical mechanisms. From a pathophysiological point of view, atherosclerotic, thromboembolic, inflammatory mechanisms are implicated. ALI is a medical emergency that puts both limb and the patient's life at risk. In patients over age 80 undergoing surgery, mortality remains high reaching approximately 40% as well as amputation approximately 11%. The purpose of this paper is to summarize the scientific evidence on the possibilities of primary and secondary prevention of ALI and to raise awareness among doctors involved in the management of ALI, in particular by describing the central role of the general practitioner.

A decision-making algorithm proposal for PICCs and midlines insertion in patients with advanced kidney disease: A pilot study

INTRODUCTION

Kidney Disease Outcomes Quality Initiative clinical practice guidelines recommend avoiding placement of peripherally inserted vascular access devices in patients with an estimated glomerular filtration rate (eGFR) <45 ml/min. On the other hand, many patients with severe chronic kidney disease (CKD) have poor prognosis.This study carried out a global assessment of mortality at 2 years through Charlson Comorbidity Index (CCI) and Beclap score in patients with PICCs or Midlines, assuming that in those with an estimated high mortality rate at 2 years, it could be acceptable to implant a peripheral vascular access device (PVAD) despite the presence of CKD.

METHODS

We analyzed data on patients with PICCs or Midlines inserted from October 2018 to November 2019. CCI, Beclap score, and eGFR were calculated for each patient at the time of the catheter insertion. We then followed patients for 2 years to assess 2-year mortality for each.

RESULTS

One hundred and thirty-one patients were enrolled, 49 (37.4%) had eGFR<45 ml. The 2-year mortality rate was 57.3%. The cut off derived from ROC curve analysis of 15 for Beclap score and 5 for CCI, showed good sensitivity and specificity in predicting mortality of the total population, patients without an oncological disease and patients with eGFR<45 ml/min.

CONCLUSION

CCI and Beclap score are good predictors of mortality at 2 years.Physicians and nurses can use these tools in the evaluation of patients at risk for future dialysis, instead of relying exclusively on renal function to decide whether implanting PICCs, Midlines, or other vascular access devices.

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.

Associations between urinary cysteine-rich protein 61 excretion and kidney function decline in outpatients with chronic kidney disease: a prospective cohort study in Taiwan

OBJECTIVES

To examine whether urinary excretion of cysteine-rich protein 61 (Cyr61), an acknowledged proinflammatory factor in kidney pathologies, increases in chronic kidney disease (CKD) and is associated with subsequent rapid kidney function decline.

DESIGN

An observational cohort study.

SETTING

In the nephrology outpatient clinics of a tertiary hospital in Taiwan.

PARTICIPANTS

We enrolled 138 adult CKD outpatients (n=12, 32, 18, 18, 29 and 29 in stages 1, 2, 3a, 3b, 4 and 5 CKD, respectively) between February and October 2014 and followed them for 1 year. Their mean age was 60.46±13.16 years, and 51 (37%) of them were women.

PRIMARY OUTCOME MEASURES

Urinary Cyr61 levels were measured by ELISA. Rapid kidney function decline was defined as an estimated glomerular filtration rate (eGFR) decline rate ≥ 4 mL/min/1.73 m²/year or developing end-stage renal disease during subsequent 3-month or 1-year follow-up period. Models were adjusted for demographic and clinical variables.

RESULTS

The urine Cyr61-to-creatinine ratio (UCyr61CR) increased significantly in patients with stage 4 or 5 CKD. Multivariable linear regression analysis showed that log(UCyr61CR) was positively correlated with log(urine protein-to-creatinine ratio) (p<0.001) but negatively correlated with baseline eGFR (p<0.001) and hypertension (p=0.007). Complete serum creatinine data during the follow-up were available for 112 patients (81.2%). Among them, multivariable logistic regression identified log(UCyr61CR) was independently associated with rapid kidney function decline (adjusted OR 2.29, 95% CI 1.27 to 4.15) during the subsequent 3 months. UCyr61CR improved the discriminative performance of clinical models to predict 3-month rapid kidney function decline. In contrast, log(UCyr61CR) was not associated with rapid eGFR decline during the entire 1-year follow-up.

CONCLUSIONS

Elevated urinary Cyr61 excretion is associated with rapid short-term kidney function deterioration in patients with CKD. Measuring urinary Cyr61 excretion is clinically valuable for monitoring disease trajectory and may guide treatment planning.

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.

Risk prediction models for acute kidney injury in adults: An overview of systematic reviews

Background

The incidence of Acute Kidney Injury (AKI) and its human and economic cost is increasing steadily. One way to reduce the burden associated with AKI is to prevent the event altogether. An important step in prevention lies in AKI risk prediction. Due to the increasing number of available risk prediction models (RPMs) clinicians need to be able to rely on systematic reviews (SRs) to provide an objective assessment on which RPM can be used in a specific setting. Our aim was to assess the quality of SRs of RPMs in AKI.

Methods

The protocol for this overview was registered in PROSPERO. MEDLINE and Embase were searched for SRs of RPMs of AKI in any setting from 2003 till August 2020. We used the ROBIS tool to assess the methodological quality of the retrieved SRs.

Results

Eight SRs were retrieved. All studies were assessed as being at high risk for bias using the ROBIS tool. Eight reviews had a high risk of bias in study eligibility criteria (domain 1), five for study identification and selection (domain 2), seven for data collection and appraisal (domain 3) and seven for synthesis and findings (domain 4). Five reviews were scored at high risk of bias across all four domains. Risk of bias assessment with a formal risk of bias tool was only performed in five reviews. Primary studies were heterogeneous and used a wide range of AKI definitions. Only 19 unique RPM were externally validated, of which 11 had only 1 external validation report.

Conclusion

The methodological quality of SRs of RPMs of AKI is inconsistent. Most SRs lack a formal risk of bias assessment. SRs ought to adhere to certain standard quality criteria so that clinicians can rely on them to select a RPM for use in an individual patient.

Trial registration

PROSPERO registration number is CRD 42020204236, available at https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=204236.

Low performance of prognostic tools for predicting dialysis in elderly people with advanced CKD

INTRODUCTION

Clinical decision-making about care plans can be difficult for very elderly people with advanced chronic kidney disease (CKD). Current guidelines propose the use of prognostic tools predicting end stage renal disease (ESRD) to assist in a patient-centered shared decision-making approach. Our objective was to evaluate the existing risk model scores predicting ESRD, from data collected for a French prospective multicenter cohort of mainly octogenarians with advanced CKD.

METHODS

We performed a rapid review to identify the risk model scores predicting ESRD developed from CKD patient cohorts and evaluated them with data from a prospective multicenter French cohort of elderly (> 75 years) patients with advanced CKD (estimated glomerular filtration rate [eGFR] < 20 mL/min/1.75m²), followed up for 5 years. We evaluated these scores (in absolute risk) for discrimination, calibration and the Brier score. For scores using the same time frame, we made a joint calibration curve and compared areas under the curve (AUCs).

RESULTS

The PSPA cohort included 573 patients; their mean age was 83 years and their median eGFR was 13 mL/min/1.73 m². At the end of follow-up, 414 had died and 287 had started renal replacement therapy (RRT). Our rapid review found 12 scores that predicted renal replacement therapy. Five were evaluated: the TANGRI 4-variable, DRAWZ, MARKS, GRAMS, and LANDRAY scores. No score performed well in the PSPA cohort: AUCs ranged from 0.57 to 0.65, and Briers scores from 0.18 to 0.25.

CONCLUSIONS

The low predictiveness for ESRD of the scores tested in a cohort of octogenarian patients with advanced CKD underlines the need to develop new tools for this population.

Selective endothelin A receptor antagonism in patients with proteinuric chronic kidney disease

Introduction: Selective antagonists of Endothelin-1 receptors (ERA) have been tested in diabetic and nondiabetic chronic kidney disease (CKD). The SONAR trial (Study Of diabetic Nephropathy with AtRasentan) was the first randomized, phase 3, study assessing the long-term effect of ERA on CKD progression.Areas covered: We examine the ERA effects in proteinuric CKD. We discuss the results of the main clinical studies on ERA in CKD and offer an opinion on the findings of SONAR study and future perspectives in this field. We searched in PubMed and ISI Web of Science databases for including experimental and clinical studies that evaluated ERA in proteinuric CKD.Expert opinion: The SONAR study demonstrated that ERA confers protection against risk for CKD progression. This trial stimulated clinical research on ERA, to expand the therapeutic opportunities in CKD patients. Two novel phase 3 studies testing ERA in patients with glomerular disease are ongoing. Within the context of personalized medicine, we think it would be relevant to evaluate the effect of multiple treatments, including ERA, in proteinuric CKD patients. Testing ERA in clinical trials of novel design will also help at identifying the patients who would more benefit from these drugs.

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.

Liposome-Enhanced Polymerization-Based Signal Amplification for Highly Sensitive Naked-Eye Biodetection in Paper-Based Sensors

Polymerization-based signal amplification (PBA) is a material-based approach to improving the sensitivity of paper-based diagnostic tests. Eosin Y is used as an assay label to photo-initiate free-radical polymerization to produce colored hydrogels in the presence of target analytes captured by bioactive paper. PBA achieves high-contrast and time-independent signals, but its nanomolar detection limit makes it impractical for early diagnosis of many diseases. In this work, we demonstrated efficient localization of large quantities of eosin Y per captured target analyte by incorporating eosin Y-loaded liposomes into PBA. This new "materials approach" allowed 30-fold signal enhancement compared to conventional PBA. To further improve the detection limit of liposome-enhanced PBA, we used a continuous flow-through assay format with 100 μL of analyte solution, achieving sub-nanomolar detection limits with high-contrast signals that were easily discernible to the unaided eye.