Validation of the Kidney Failure Risk Equation in Manitoba

Representation of multimorbidity and frailty in the development and validation of kidney failure prognostic prediction models: a systematic review

BACKGROUND

Prognostic models that identify individuals with chronic kidney disease (CKD) at greatest risk of developing kidney failure help clinicians to make decisions and deliver precision medicine. It is recognised that people with CKD usually have multiple long-term health conditions (multimorbidity) and often experience frailty. We undertook a systematic review to evaluate the representation and consideration of multimorbidity and frailty within CKD cohorts used to develop and/or validate prognostic models assessing the risk of kidney failure.

METHODS

We identified studies that described derivation, validation or update of kidney failure prognostic models in MEDLINE, CINAHL Plus and the Cochrane Library-CENTRAL. The primary outcome was representation of multimorbidity or frailty. The secondary outcome was predictive accuracy of identified models in relation to presence of multimorbidity or frailty.

RESULTS

Ninety-seven studies reporting 121 different kidney failure prognostic models were identified. Two studies reported prevalence of multimorbidity and a single study reported prevalence of frailty. The rates of specific comorbidities were reported in a greater proportion of studies: 67.0% reported baseline data on diabetes, 54.6% reported hypertension and 39.2% reported cardiovascular disease. No studies included frailty in model development, and only one study considered multimorbidity as a predictor variable. No studies assessed model performance in populations in relation to multimorbidity. A single study assessed associations between frailty and the risks of kidney failure and death.

CONCLUSIONS

There is a paucity of kidney failure risk prediction models that consider the impact of multimorbidity and/or frailty, resulting in a lack of clear evidence-based practice for multimorbid or frail individuals. These knowledge gaps should be explored to help clinicians know whether these models can be used for CKD patients who experience multimorbidity and/or frailty.

SYSTEMATIC REVIEW REGISTRATION

This review has been registered on PROSPERO (CRD42022347295).

Early prediction of end-stage kidney disease using electronic health record data: a machine learning approach with a 2-year horizon

Objectives

In the United States, end-stage kidney disease (ESKD) is responsible for high mortality and significant healthcare costs, with the number of cases sharply increasing in the past 2 decades. In this study, we aimed to reduce these impacts by developing an ESKD model for predicting its occurrence in a 2-year period.

Materials and Methods

We developed a machine learning (ML) pipeline to test different models for the prediction of ESKD. The electronic health record was used to capture several kidney disease-related variables. Various imputation methods, feature selection, and sampling approaches were tested. We compared the performance of multiple ML models using area under the ROC curve (AUCROC), area under the Precision-Recall curve (PR-AUC), and Brier scores for discrimination, precision, and calibration, respectively. Explainability methods were applied to the final model.

Results

Our best model was a gradient-boosting machine with feature selection and imputation methods as additional components. The model exhibited an AUCROC of 0.97, a PR-AUC of 0.33, and a Brier score of 0.002 on a holdout test set. A chart review analysis by expert physicians indicated clinical utility.

Discussion and Conclusion

An ESKD prediction model can identify individuals at risk for ESKD and has been successfully deployed within our health system.

External validation of the KFRE and Grams prediction models for kidney failure and death in a Spanish cohort of patients with advanced chronic kidney disease

BACKGROUND

The Kidney Failure Risk Equation (KFRE) is a 2- and 5-year kidney failure prediction model that is applied in chronic kidney disease (CKD) G3 + . The Grams model predicts kidney failure and death at 2 and 4 years in CKD G4 + . There are limited external validations of the Grams model, especially for predicting mortality before kidney failure.

METHODS

We performed an external validation of the Grams and Kidney Failure Risk Equation prediction models in incident patients with CKD G4 + at Hospital Universitario Fundación Alcorcón, Spain, between 1/1/2014 and 31/12/2018, ending follow-up on 30/09/2023. Discrimination was performed calculating the area under the receiver-operating characteristic curve. Calibration was assessed using the Hosmer-Lemeshow test and the Brier score.

RESULTS

The study included 339 patients (mean age 72.2 ± 12.7 years and baseline estimated glomerular filtration rate 20.6 ± 5.0 ml/min). Both models showed excellent discrimination. The area under the curve (AUC) for Kidney Failure Risk Equation-2 and Grams-2 were 0.894 (95% CI 0.857-0.931) and 0.897 (95%CI 0.859-0.935), respectively. For Grams-4 the AUC was 0.841 (95%CI 0.798-0.883), and for Kidney Failure Risk Equation-5 it was 0.823 (95% CI 0.779-0.867). For death before kidney failure, the Grams model showed acceptable discrimination (AUC 0.708 (95% CI 0.626-0.790) and 0.744 (95% CI 0.683-0.804) for Grams-2 and Grams-4, respectively). Both models presented excellent calibration for predicting kidney failure. Grams model calibration to estimate mortality before kidney failure was also excellent. In all cases, Hosmer-Lemeshow test resulted in a p-value greater than 0.05, and the Brier score was less than 0.20.

CONCLUSIONS

In a cohort of patients with CKD G4 + from southern Europe, both the Grams and Kidney Failure Risk Equation models are accurate in estimating the risk of kidney failure. Additionally, the Grams model provides a reliable estimate of the risk of mortality before kidney failure.

Utilization of the corticomedullary difference in magnetic resonance imaging-derived apparent diffusion coefficient for noninvasive assessment of chronic kidney disease in type 2 diabetes

BACKGROUNDS

Accumulating data demonstrated that the cortico-medullary difference in apparent diffusion coefficient (ΔADC) of diffusion-weighted magnetic resonance imaging (DWI) was a better correlation with kidney fibrosis, tubular atrophy progression, and a predictor of kidney function evolution in chronic kidney disease (CKD).

OBJECTIVES

We aimed to assess the value of ΔADC in evaluating disease severity, differential diagnosis, and the prognostic risk stratification for patients with type 2 diabetes (T2D) and CKD.

METHODS

Total 119 patients with T2D and CKD who underwent renal MRI were prospectively enrolled. Of them, 89 patients had performed kidney biopsy for pathological examination, including 38 patients with biopsy-proven diabetic kidney disease (DKD) and 51 patients with biopsy-proven non-diabetic kidney disease (NDKD) and Mix (DKD + NDKD). Clinicopathological characteristics were compared according to different ΔADC levels. Moreover, univariate and multivariate-linear regression analyses were performed to explore whether ΔADC was independently associated with estimated glomerular filtration rate (eGFR) and urinary albumin creatinine ratio (UACR). The diagnostic performance of ΔADC for discriminating DKD from NDKD + Mix was evaluated by receiver operating characteristic (ROC) analysis. In addition, an individual's 2- or 5-year risk probability of progressing to end-stage kidney disease (ESKD) was calculated by the kidney failure risk equation (KFRE). The effect of ΔADC on prognostic risk stratification was assessed. Additionally, net reclassification improvement (NRI) was used to evaluate the model performance.

RESULTS

All enrolled patients had a median ΔADC level of 86 (IQR 28, 155) × 10-6 mm2/s. ΔADC significantly decreased across the increasing staging of CKD (P < 0.001). Moreover, those with pathological-confirmed DKD has a significantly lower level of ΔADC than those with NDKD and Mix (P < 0.001). It showed that ΔADC was independently associated with eGFR (β = 1.058, 95% CI = [1.002,1.118], P = 0.042) and UACR (β = -3.862, 95% CI = [-7.360, -0.365], P = 0.031) at multivariate linear regression analyses. Besides, ΔADC achieved an AUC of 0.707 (71% sensitivity and 75% specificity) and AUC of 0.823 (94% sensitivity and 67% specificity) for discriminating DKD from NDKD + Mix and higher ESKD risk categories (≥50% at 5 years; ≥10% at 2 years) from lower risk categories (<50% at 5 years; <10% at 2 years). Accordingly, the optimal cutoff value of ΔADC for higher ESKD risk categories was 66 × 10-6 mm2/s, and the group with the low-cutoff level of ΔADC group was associated with 1.232 -fold (95% CI 1.086, 1.398) likelihood of higher ESKD risk categories as compared to the high-cutoff level of ΔADC group in the fully-adjusted model. Reclassification analyses confirmed that the final adjusted model improved NRI.

CONCLUSIONS

ΔADC was strongly associated with eGFR and UACR in patients with T2D and CKD. More importantly, baseline ΔADC was predictive of higher ESKD risk, independently of significant clinical confounding. Specifically, ΔADC <78 × 10-6 mm2/s and <66 × 10-6 mm2/s would help to identify T2D patients with the diagnosis of DKD and higher ESKD risk categories, respectively.

Multicentre external validation of the prognostic model kidney failure risk equation in patients with CKD stages 3 and 4 in Peru: a retrospective cohort study

OBJECTIVES

To externally validate the four-variable kidney failure risk equation (KFRE) in the Peruvian population for predicting kidney failure at 2 and 5 years.

DESIGN

A retrospective cohort study.

SETTING

17 primary care centres from the Health's Social Security of Peru.

PARTICIPANTS

Patients older than 18 years, diagnosed with chronic kidney disease stage 3a-3b-4 and 3b-4, between January 2013 and December 2017. Patients were followed until they developed kidney failure, died, were lost, or ended the study (31 December 2019), whichever came first.

PRIMARY AND SECONDARY OUTCOME MEASURES

Performance of the KFRE model was assessed based on discrimination and calibration measures considering the competing risk of death.

RESULTS

We included 7519 patients in stages 3a-4 and 2798 patients in stages 3b-4. The estimated cumulative incidence of kidney failure, accounting for competing event of death, at 2 years and 5 years, was 1.52% and 3.37% in stages 3a-4 and 3.15% and 6.86% in stages 3b-4. KFRE discrimination at 2 and 5 years was high, with time-dependent area under the curve and C-index >0.8 for all populations. Regarding calibration in-the-large, the observed to expected ratio and the calibration intercept indicated that KFRE underestimates the overall risk at 2 years and overestimates it at 5 years in all populations.

CONCLUSIONS

The four-variable KFRE models have good discrimination but poor calibration in the Peruvian population. The model underestimates the risk of kidney failure in the short term and overestimates it in the long term. Further research should focus on updating or recalibrating the KFRE model to better predict kidney failure in the Peruvian context before recommending its use in clinical practice.

Clinical Decision Support Tools in the Electronic Medical Record

The integration of clinical decision support (CDS) tools into electronic medical record (EMR) systems has become common. Although there are many benefits for both patients and providers from successful integration, barriers exist that prevent consistent and effective use of these tools. Such barriers include tool alert fatigue, lack of interoperability between tools and medical record systems, and poor acceptance of tools by care providers. However, successful integration of CDS tools into EMR systems have been reported; examples of these include the Statin Choice Decision Aid, and the Kidney Failure Risk Equation (KFRE). This article reviews the history of EMR systems and its integration with CDS tools, the barriers preventing successful integration, and the benefits reported from successful integration. This article also provides suggestions and strategies for improving successful integration, making these tools easier to use and more effective for care providers.

The kidney failure risk equation predicts kidney failure: Validation in an Australian cohort

AIMS

Predicting progression to kidney failure for patients with chronic kidney disease is essential for patient and clinicians' management decisions, patient prognosis, and service planning. The Tangri et al Kidney Failure Risk Equation (KFRE) was developed to predict the outcome of kidney failure. The KFRE has not been independently validated in an Australian Cohort.

METHODS

Using data linkage of the Tasmanian Chronic Kidney Disease study (CKD.TASlink) and the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA), we externally validated the KFRE. We validated the 4, 6, and 8-variable KFRE at both 2 and 5 years. We assessed model fit (goodness of fit), discrimination (Harell's C statistic), and calibration (observed vs predicted survival).

RESULTS

There were 18 170 in the cohort with 12 861 participants with 2 years and 8182 with 5 years outcomes. Of these 2607 people died and 285 progressed to kidney replacement therapy. The KFRE has excellent discrimination with C statistics of 0.96-0.98 at 2 years and 0.95-0.96 at 5 years. The calibration was adequate with well-performing Brier scores (0.004-0.01 at 2 years, 0.01-0.03 at 5 years) however the calibration curves, whilst adequate, indicate that predicted outcomes are systematically worse than observed.

CONCLUSION

This external validation study demonstrates the KFRE performs well in an Australian population and can be used by clinicians and service planners for individualised risk prediction.

Impacting Management of Chronic Kidney Disease Through Primary Care Practice Audits: A Quality Improvement Study

Background

Risk prediction tools are important in chronic disease management, but their implementation into clinical workflow is often limited by lack of electronic health record (EHR)-linked solutions.

Objective

To implement the Khure Health (KH) clinical decision support platform with an artificial intelligence (AI)-enabled algorithm for chronic kidney disease (CKD) risk detection in 201 primary care provider practices across Ontario.

Design

Multi-practice quality improvement study.

Setting

The study was conducted in Ontario, Canada.

Participants

201 primary care practices.

Measurements

Per-practice CKD risk stratification and clinician action.

Methods

Data for estimated glomerular filtration rate (eGFR), albuminuria, demographics, and comorbid conditions were extracted from the EHR using KH's natural language processing (NLP) algorithms. Patients already on dialysis, visiting a nephrologist, older than 85, or already on a sodium-glucose cotransporter 2 inhibitor (SGLT2i) were excluded. The remaining individuals were risk stratified using the kidney failure risk equation, presence or absence of cardiovascular disease (CVD), or other comorbid conditions. A dashboard with disease-specific educational information and links to the EHRs of the identified patients was created.

Results

We screened 361 299 individuals and identified 8194 patients with CKD Stage 3 at risk for progression or cardiovascular events. A total of 620 individuals were at high risk for CKD progression or CVD, and 2592 were at intermediate risk. A total of 2010 individuals (10 patients per practice) at high or moderate risk were selected for a chart audit, and appropriate additional testing (repeat eGFR or albuminuria) or prescription of disease-modifying therapy occurred in 24.32% of these patients.

Limitations

Data on comorbidities, medications, or demographic variables are not available for presentation or statistical analysis due to privacy legislation and primary care provider (PCP) custodianship over EHR data.

Conclusion

An AI-enabled EHR clinical decision support application that can detect and risk stratify patients with CKD can enable improved laboratory testing and management. Larger trials of clinical decision support and practice audit applications will be needed to impact CKD management nationally.

Risk-based versus GFR threshold criteria for nephrology referral in chronic kidney disease

Chronic kidney disease (CKD) and kidney failure are global health problems associated with morbidity, mortality and healthcare costs, with unequal access to kidney replacement therapy between countries. The diversity of guidelines concerning referral from primary care to a specialist nephrologist determines different outcomes around the world among patients with CKD where several guidelines recommend referral when the glomerular filtration rate (GFR) is <30 mL/min/1.73 m2 regardless of age. Additionally, fixed non-age-adapted diagnostic criteria for CKD that do not distinguish correctly between normal kidney senescence and true kidney disease can lead to overdiagnosis of CKD in the elderly and underdiagnosis of CKD in young patients and contributes to the unfair referral of CKD patients to a kidney specialist. Non-age-adapted recommendations contribute to unnecessary referral in the very elderly with a mild disease where the risk of death consistently exceeds the risk of progression to kidney failure and ignore the possibility of effective interventions of a young patient with long life expectancy. The opportunity of mitigating CKD progression and cardiovascular complications in young patients with early stages of CKD is a task entrusted to primary care providers who are possibly unable to optimally accomplish guideline-directed medical therapy for this purpose. The shortage in the nephrology workforce has classically led to focused referral on advanced CKD stages preparing for kidney replacement, but the need for hasty referral to a nephrologist because of the urgent requirement for kidney replacement therapy in advanced CKD is still observed and changes are required to move toward reducing the kidney failure burden. The Kidney Failure Risk Equation (KFRE) is a novel tool that can guide wiser nephrology referrals and impact patients.

Bridging Gaps in Diabetic Nephropathy Care: A Narrative Review Guided by the Lived Experiences of Patient Partners

Purpose of review

Diabetes affects almost a 10th of the Canadian population, and diabetic nephropathy is one of its main complications. It remains a leading cause of kidney failure despite the availability of effective treatments.

Sources of information

The sources of information are iterative discussions between health care professionals and patient partners and literature collected through the search of multiple databases.

Methods

Major pitfalls related to optimal diabetic nephropathy care were identified through discussions between patient partners and clinician researchers. We identified underlying factors that were common between pitfalls. We then conducted a narrative review of strategies to overcome them, with a focus on Canadian initiatives.

Key findings

We identified 5 pitfalls along the diabetic nephropathy trajectory, including a delay in diabetes diagnosis, suboptimal glycemic control, delay in the detection of kidney involvement, suboptimal kidney protection, and deficient management of advanced chronic kidney disease. Several innovative care models and approaches have been proposed to address these pitfalls; however, they are not consistently applied. To improve diabetic nephropathy care in Canada, we recommend focusing initiatives on improving awareness of diabetic nephropathy, improving access to timely evidence-based care, fostering inclusive patient-centered care environment, and generating new evidence that supports complex disease management. It is imperative that patients and their families are included at the center of these initiatives.

Limitations

This review was limited to research published in peer-reviewed journals. We did not perform a systematic review of the literature; we included articles that were relevant to the major pitfalls identified by our patient partners. Study quality was also not formally assessed. The combination of these factors limits the scope of our conclusions.

Assessment of Cystatin C Level for Risk Stratification in Adults With Chronic Kidney Disease

Importance

Kidney function is usually estimated from serum creatinine level, whereas an alternative glomerular filtration marker (cystatin C level) associates more closely with future risk of cardiovascular disease (CVD) and mortality.

Objectives

To evaluate whether testing concordance between estimated glomerular filtration rates based on cystatin C (eGFRcys) and creatinine (eGFRcr) levels would improve risk stratification for future outcomes and whether estimations differ by age.

Design, Setting, and Participants

A prospective population-based cohort study (UK Biobank), with participants recruited between 2006-2010 with median follow-up of 11.5 (IQR, 10.8-12.2) years; data were collected until August 31, 2020. Participants had eGFRcr greater than or equal to 45 mL/min/1.73 m2, albuminuria (albumin <30 mg/g), and no preexisting CVD or kidney failure.

Exposures

Chronic kidney disease status was categorized by concordance between eGFRcr and eGFRcys across the threshold for hronic kidney disease (CKD) diagnosis (60 mL/min/1.73 m2).

Main Outcomes and Measures

Ten-year probabilities of CVD, mortality, and kidney failure were assessed according to CKD status. Multivariable-adjusted Cox proportional hazards models tested associations between CVD and mortality. Area under the receiving operating curve tested discrimination of eGFRcr and eGFRcys for CVD and mortality. The Net Reclassification Index assessed the usefulness of eGFRcr and eGFRcys for CVD risk stratification. Analyses were stratified by older (age 65-73 years) and younger (age <65 years) age.

Results

There were 428 402 participants: median age was 57 (IQR, 50-63) years and 237 173 (55.4%) were women. Among 76 629 older participants, there were 9335 deaths and 5205 CVD events. Among 351 773 younger participants, there were 14 776 deaths and 9328 CVD events. The 10-year probability of kidney failure was less than 0.1%. Regardless of the eGFRcr, the 10-year probabilities of CVD and mortality were low when eGFRcys was greater than or equal to 60 mL/min/1.73 m2; conversely, with eGFRcys less than 60 mL/min/1.73 m2, 10-year risks were nearly doubled in older adults and more than doubled in younger adults. Use of eGFRcys better discriminated CVD and mortality risk than eGFRcr. Across a 7.5% 10-year risk threshold for CVD, eGFRcys improved case Net Reclassification Index by 0.7% (95% CI, 0.6%-0.8%) in older people and 0.7% (95% CI, 0.7%-0.8%) in younger people; eGFRcr did not add to CVD risk estimation.

Conclusions and Relevance

The findings of this study suggest that eGFRcr 45 to 59 mL/min/1.73 m2 includes a proportion of individuals at low risk and fails to capture a substantial proportion of individuals at high-risk for CVD and mortality. The eGFRcys appears to be more sensitive and specific for CVD and mortality risks in mild CKD.

Independent External Validation and Comparison of Death and Kidney Replacement Therapy Prediction Models in Advanced CKD

Rationale & Objective

Study Design

Setting & Participants

Outcomes & Analytical Approach

Results

Limitations

Conclusions

Referral patterns, disease progression and impact of the kidney failure risk equation (KFRE) in a Queensland Chronic Kidney Disease Registry (CKD.QLD) cohort: a study protocol

INTRODUCTION

Chronic kidney disease (CKD) is a rapidly increasing and global phenomenon which carries high morbidity and mortality. Although timely referral from primary care to secondary care confers favourable outcomes, it is not possible for every patient with CKD to be managed at secondary care. With 1 in 10 Australians currently living with markers of CKD against a workforce of about 600 nephrology specialists, a risk stratification strategy is required that will reliably identify individuals whose kidney disease is likely to progress.

METHODS AND ANALYSIS

This study will undertake a retrospective secondary analysis of the Chronic Kidney Disease Queensland Registry (CKD.QLD) data of consented adults to examine the referral patterns to specialist nephrology services from primary care providers and map the patient trajectory and outcomes to inform the optimal referral timing for disease mitigation. Patient data over a 5-year period will be examined to determine the impact of the kidney failure risk equation-based risk stratification on the referral patterns, disease progression and patient outcomes. The results will inform considerations of a risk stratification strategy that will ensure adequate predialysis management and add to the discussion of the time interval between referral and initiation of kidney replacement therapy or development of cardiovascular events.

ETHICS AND DISSEMINATION

This protocol was approved by the Ethics Committee of the Royal Brisbane and Women's Hospital in January 2021 (LNR/2020/QRBW/69707 14/01/2021). The HREC waived the requirement for patient consent as all patients had consented for the use of their data for the purpose of research on recruitment into CKD.QLD Registry. The results will be presented as a component of a PhD study with The University of Queensland. It is anticipated that the results will be presented at health-related conferences (local, national and possibly international) and via publication in peer-reviewed academic journals.

Evaluation of a predictive model of end-stage kidney disease in a French-based cohort

BACKGROUND

The risk of ESKD is highly heterogeneous among renal diseases, and risk scores were developed to account for multiple progression factors. Kidney failure risk equation (KFRE) is the most widely accepted, although external validation is scarce. The objective of this study was to evaluate the usefulness of this score in a French case-control cohort and test the pertinence of the proposed thresholds.

METHODS

A retrospective case-control study comparing a group of patients starting renal replacement therapy (RRT) to a group of patients with CKD stages 3-5. Multivariate analysis to assess the predictors of ESKD risk. Discrimination of 4-, 6- and 8-variable scores using ROC curves and compared with eGFR alone and albumin/creatinine ratio (ACR) alone.

RESULTS

314 patients with a ratio of 1 case for 1 control. In multivariate analysis, increasing age and higher eGFR were associated with a lower risk of ESKD (OR 0.62, 95% CI 0.48-0.79; and OR 0.72, 95% CI 0.59-0.86, respectively). The log-transformed ACR was associated with a higher risk of ESKD (OR 1.25 per log unit, 95% CI 1.02-1.55). The 4-variable score was significantly higher in the RRT group than in the CKD-ND group, and was more efficient than the eGFR (AUROC 0.66, 95% CI 0.60-0.72, p = 0.018) and the log-transformed ACR (AUROC 0.63 95% CI 0.60-0.72, p = 0.0087) to predict ESKD. The 6-variable score including BP metrics and diabetes was not more discriminant as the 4-variable score. The 8-variable score had similar performance compared with the 4-score (AUROC 8-variable score: 0.70, 95% CI 0.64-0.76, p = 0.526). A 40% and 20% score thresholds were not superior to eGFR < 15 and 20 mL/min/1.73 m², respectively. A 10% threshold was more specific than an eGFR < 30 mL/min/1.73 m².

CONCLUSION

KFRE was highly discriminant between patients progressing to ESKD vs those non-progressing. The 4-variable score may help stratify renal risk and referral in the numerous patients with stage 3 CKD. Conversely, the proposed thresholds for creating vascular access or preemptive transplantation were not superior to eGFR alone.

The Effect of Age on Performance of the Kidney Failure Risk Equation in Advanced CKD

Introduction

The Kidney Failure Risk Equation (KFRE) is a clinical tool widely used to predict progression from chronic kidney disease (CKD) to kidney failure. This study aimed to evaluate the effect of age on KFRE performance in advanced CKD.

Methods

We conducted a retrospective cohort study among 1701 consecutive patients referred to an advanced CKD clinic in Ottawa, Canada, between 2010 and 2018. Patients were categorized by age as follows: <60, 60 to 69, 70 to 79, and ≥80 years. Calibration plots compared the predicted (through the KFRE) and observed incidence of kidney failure. Concordance statistic (C-statistic) evaluated discrimination. Cumulative incidence of kidney failure was compared between models that accounted for the competing risk of death and those that did not.

Results

We found that the KFRE overestimated the risk of kidney failure among the oldest subset of patients (≥80 years) with absolute and relative differences of 7.6% and 22.8%, respectively, over 2 years (P = 0.047), and 24.7% and 40.4%, respectively, over 5 years (P < 0.001). The degree of overestimation in the elderly was most pronounced among those with the highest predicted risks for kidney failure. KFRE discrimination was acceptable (C-statistic 0.70–0.79) across all age categories. The cumulative incidence of kidney failure was overestimated in models that did not account for the competing risk of death, and this overestimation was more pronounced with older age.

Conclusion

The KFRE overestimates kidney failure risk among elderly patients with advanced CKD. This overestimation relates to the increasing competing risk of death with older age, particularly over longer time horizons.

Retinopathy and Risk of Kidney Disease in Persons With Diabetes

Rationale & Objective

Retinopathy and chronic kidney disease (CKD) are typically considered microvascular complications of diabetes, and cardiovascular and cerebrovascular diseases are considered macrovascular complications; however, all may share common pathological mechanisms. This study quantified the association of retinopathy with risk of kidney disease and compared with the association with cardiovascular disease in persons with diabetes.

Study Design

Retrospective cohort study.

Setting & Participants

1,759 participants in the ARIC study who had diabetes at visit 4 and underwent retinal examination at visit 3.

Exposure

Retinopathy.

Outcome

Prevalent CKD (estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73 m²), prevalent albuminuria (urinary albumin-creatinine ratio [UACR] > 30 mg/g), incident CKD, incident end-stage kidney disease (ESKD), incident coronary heart disease (CHD), and incident stroke.

Analytical Approach

The cross-sectional association of retinopathy with prevalent CKD and albuminuria was assessed by logistic regression. The associations between retinopathy, incident CKD, incident ESKD, incident CHD, and incident stroke were examined using Cox proportional hazards models. Seemingly unrelated regression was used to compare the strength of association between retinopathy and outcomes.

Results

During the median follow-up period of 14.2 years, 723 participants developed CKD, and there were 109 ESKD events, 399 CHD events, and 196 stroke events. Compared with the participants without retinopathy, participants with retinopathy were more likely to have reduced eGFR (OR, 1.56 [95% CI, 1.09-2.23]) and UACR > 30 mg/g (OR, 1.61 [95% CI, 1.24-2.10]). Retinopathy was associated with risk of incident CKD (HR, 1.22 [95% CI, 1.02-1.46]), ESKD (HR, 1.69 [95% CI, 1.11-2.58]), CHD (HR, 1.46 [95% CI, 1.15-1.84]), and stroke (HR, 1.43 [95% CI, 1.03-1.97]). A stronger relationship was found between retinopathy and CHD when compared with retinopathy and CKD (P = 0.03); all other associations were similar.

Limitations

Retinal examination and kidney measurements were taken at different visits.

Conclusions

The presence of retinopathy was associated with higher prevalence of kidney disease and higher risk of incident CKD, ESKD, and CHD. These results may suggest that a similar mechanism underlies the development of retinopathy and other adverse outcomes in diabetes.

A novel drug response score more accurately predicts renoprotective drug effects than existing renal risk scores

BACKGROUND

Risk factor-based equations are used to predict risk of kidney disease progression in patients with type 2 diabetes order to guide treatment decisions. It is, however, unknown whether these models can also be used to predict the effects of drugs on clinical outcomes.

METHODS

The previously developed Parameter Response Efficacy (PRE) score, which integrates multiple short-term drug effects, was first compared with the existing risk scores, Kidney Failure Risk Equation (KFRE) and The Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) renal risk score, in its performance to predict end-stage renal disease (ESRD; KFRE) and doubling of serum creatinine or ESRD (ADVANCE). Second, changes in the risk scores were compared after 6 months' treatment to predict the long-term effects of losartan on these renal outcomes in patients with type 2 diabetes and chronic kidney disease.

RESULTS

The KFRE, ADVANCE and PRE scores showed similarly good performance in predicting renal risk. However, for prediction of the effect of losartan, the KFRE risk score predicted a relative risk change in the occurrence of ESRD of 3.1% [95% confidence interval (CI) -5 to 12], whereas the observed risk change was -28.8% (95% CI -42.0 to -11.5). For the composite endpoint of doubling of serum creatinine or ESRD, the ADVANCE score predicted a risk change of -12.4% (95% CI -17 to -7), which underestimated the observed risk change -21.8% (95% CI -34 to -6). The PRE score predicted renal risk changes that were close to the observed risk changes with losartan treatment [-24.0% (95% CI -30 to -17) and -22.6% (95% CI -23 to -16) for ESRD and the composite renal outcome, respectively].

CONCLUSION

A drug response score such as the PRE score may assist in improving clinical decision making and implement precision medicine strategies.

Performance of the Kidney Failure Risk Equation by Disease Etiology in Advanced CKD

BACKGROUND AND OBJECTIVES

The kidney failure risk equation is a clinical tool commonly used for prediction of progression from CKD to kidney failure. The kidney failure risk equation's accuracy in advanced CKD and whether this varies by CKD etiology remains unknown. This study examined the kidney failure risk equation's discrimination and calibration at 2 and 5 years among a large tertiary care population with advanced CKD from heterogeneous etiologies.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

This retrospective cohort study included 1293 patients with advanced CKD (median eGFR 15 ml/min per 1.73 m²) referred to the Ottawa Hospital Multi-Care Kidney Clinic between 2010 and 2016, with follow-up clinical data available through 2018. Four-variable kidney failure risk equation scores for 2- and 5-year risks of progression to kidney failure (defined as dialysis or kidney transplantation) were calculated upon initial referral and correlated with the subsequent observed kidney failure incidence within these time frames. Receiver operating characteristic curves and calibration plots were used to measure the discrimination and calibration of the kidney failure risk equation both in the overall advanced CKD population and by CKD etiology: diabetic kidney disease, hypertensive nephrosclerosis, GN, polycystic kidney disease, and other. Pairwise comparisons of the receiver operating characteristic curves by CKD etiology were performed to compare kidney failure risk equation discrimination.

RESULTS

The kidney failure risk equation provided adequate to excellent discrimination in identifying patients with CKD likely to progress to kidney failure at the 2- and 5-year time points both overall (2-year area under the curve, 0.83; 95% confidence interval, 0.81 to 0.85; 5-year area under the curve, 0.81; 95% confidence interval, 0.77 to 0.84) and across CKD etiologies. The kidney failure risk equation displayed adequate calibration at the 2- and 5-year time points both overall and across CKD etiologies (Hosmer-Lemeshow P≥0.05); however, the predicted risks of kidney failure were higher than the observed risks across CKD etiologies with the exception of polycystic kidney disease.

CONCLUSIONS

The kidney failure risk equation provides adequate discrimination and calibration in advanced CKD and across CKD etiologies.

An independent validation of the kidney failure risk equation in an Asian population

Predicting the risk of end-stage renal disease (ESRD) progression facilitates appropriate nephrology care of patients with chronic kidney disease (CKD). Previously, the kidney failure risk equations (KFREs) were developed and validated in several cohorts. The purpose of this study is to validate the KFREs in a Korean population and to recalibrate the equations. A total of 38,905 adult patients, including 13,244 patients with CKD stages G3–G5, who were referred to nephrology were recruited. Using the original KFREs (4-, 6- and 8-variable equations) and recalibration equations, we predicted the risk of 2- and 5-year ESRD progression. All analyses were conducted in CKD stages G3-G5 patients as well as the total population. In CKD stages G3–G5 patients, All the original 4-, 6- and 8-variable equations showed excellent areas under the receiver operating characteristic curve of 0.87 and 0.83 for the 2- and 5-year risk of ESRD, respectively. The results of net reclassification improvement, integrated discrimination index and Brier score showed that recalibration improved the prediction models in some cases. The original KFREs showed high discrimination in both CKD stages G3–G5 patients and the total population referred to nephrology in this large Korean cohort. KFREs can be implemented in Korean health systems and can guide nephrology referrals and other CKD-related treatment decisions.

The Impact of a New Triage and Booking System on Renal Clinic Wait Times

Background:

Prolonged wait times are known barriers to accessing nephrology care for patients needing more urgent specialist services. Improved process and standardized triage systems are known to minimize wait times of urgent or semi-urgent care in health care disciplines. In Central Zone (CZ) renal clinic, mean wait times for urgent (P1) and semi-urgent (P2) referrals were prolonged before 2014. We also observed prolonged wait times for elective (P3-P5) categories. Improving wait times was identified as an access to care quality improvement focus in CZ renal clinic of the Nova Scotia Health Authority (NSHA).

Objectives:

To describe our new referral process and new triage system, and to examine their effect on number of referrals wait-listed and mean wait times.

Design:

A quasi-experimental design was used.

Setting:

Halifax, Nova Scotia, Canada.

Participants:

Patients referred to Central Zone Renal Clinic between 2012 and 2018.

Measurements:

A time series of referral counts and wait times for each triage category were measured before our interventions and after implementing our interventions.

Methods:

We reviewed our referral processes to identify gaps leading to prolonged wait times. On January 1, 2014, we implemented new administrative procedures: pretriage (standardized referral information form and staff training), triage (standardized clinic intake criteria and new triage guidelines), posttriage (protecting clinic spots for urgent and semi-urgent referrals, wait-list maintenance, and increasing new referral clinic capacity). Data were collected prospectively. Descriptive analysis on mean wait times was done using run charts.

Results:

A 33% reduction in total number of referrals wait-listed was observed over 4.5 years after intervention. Descriptive analysis of the urgent and semi-urgent categories (P1 and P2) revealed a significant shift of mean wait times on run charts after the interventions. Target wait time was achieved in 94% of P1 category and 78% of P2 category.

Limitations:

This type of study design does not exclude confounding variables influencing results. We did not explore stakeholder satisfaction or whether the new referral process presented barriers to resending referrals that had insufficient triage data. The long-term sustainability of adding demand-responsive surge clinics and opportunity cost were not assessed. Our referral process and triage system have not been externally validated and may not be applicable in settings without wait-lists or settings that use electronic, telephone or telemedicine consults.

Conclusion:

Our selective intake of referrals with adequate triage information and referrals needing nephrology consult as defined by our clinic intake criteria reduced number of referrals wait-listed. We saw improved wait times for urgent and semi-urgent referrals with these categories now falling within target wait times for the vast majority of patients. The work of this improvement initiative continues especially for the lower-risk triage categories.

Trial registration:

Not applicable as this was a Quality improvement initiative.

Validation of the kidney failure risk equation for end-stage kidney disease in Southeast Asia

BACKGROUND

Patients with chronic kidney disease (CKD) are at high risk of end-stage kidney disease (ESKD). The Kidney Failure Risk Equation (KFRE), which predicts ESKD risk among patients with CKD, has not been validated in primary care clinics in Southeast Asia (SEA). Therefore, we aimed to (1) evaluate the performance of existing KFRE equations, (2) recalibrate KFRE for better predictive precision, and (3) identify optimally feasible KFRE thresholds for nephrologist referral and dialysis planning in SEA.

METHODS

All patients with CKD visiting nine primary care clinics from 2010 to 2013 in Singapore were included and applied 4-variable KFRE equations incorporating age, sex, estimated glomerular filtration rate (eGFR), and albumin-to-creatinine ratio (ACR). ESKD onset within two and five years were acquired via linkage to the Singapore Renal Registry. A weighted Brier score (the squared difference between observed vs predicted ESKD risks), bias (the median difference between observed vs predicted ESKD risks) and precision (the interquartile range of the bias) were used to select the best-calibrated KFRE equation.

RESULTS

The recalibrated KFRE (named Recalibrated Pooled KFRE SEA) performed better than existing and other recalibrated KFRE equations in terms of having a smaller Brier score (square root: 2.8% vs. 4.0-9.3% at 5 years; 2.0% vs. 6.1-9.1% at 2 years), less bias (2.5% vs. 3.3-5.2% at 5 years; 1.8% vs. 3.2-3.6% at 2 years), and improved precision (0.5% vs. 1.7-5.2% at 5 years; 0.5% vs. 3.8-4.2% at 2 years). Area under ROC curve for the Recalibrated Pooled KFRE SEA equations were 0.94 (95% confidence interval [CI]: 0.93 to 0.95) at 5 years and 0.96 (95% CI: 0.95 to 0.97) at 2 years. The optimally feasible KFRE thresholds were > 10-16% for 5-year nephrologist referral and > 45% for 2-year dialysis planning. Using the Recalibrated Pooled KFRE SEA, an estimated 82 and 89% ESKD events were included among 10% of subjects at highest estimated risk of ESKD at 5-year and 2-year, respectively.

CONCLUSIONS

The Recalibrated Pooled KFRE SEA performs better than existing KFREs and warrants implementation in primary care settings in SEA.

The Use of Renin-Angiotensin System Inhibitors in Patients With Chronic Kidney Disease

Chronic kidney disease (CKD) is a growing public health issue worldwide. It is acknowledged that CKD is associated with increased risk of cardiovascular disease, which is the leading cause of morbidity and mortality in this population. The role of the renin-angiotensin-aldosterone system in the pathophysiology of hypertension, and cardiovascular and kidney diseases is well known and the renin-angiotensin-aldosterone system is a major regulator of blood pressure through its effect on body fluids and electrolyte homeostasis. For 2 decades, renin-angiotensin system inhibitors have been the mainstay of treatment for CKD. Clinical trials have shown that prescription of monotherapy with angiotensin-converting enzyme inhibitors or angiotensin receptor blockers reduces albuminuria and slows the progression of nephropathy in patients with diabetes. In clinical practice guidelines, renin-angiotensin system inhibitors are recommended as the antihypertensive drug of choice in patients with CKD with or without diabetes. Moreover, renin-angiotensin system inhibitors have been shown to offer cardiovascular protection beyond those resulting after blood pressure control. However, the benefits of renin-angiotensin system inhibitor prescriptions for patients with advanced CKD remain controversial. Patients with advanced CKD or who undergo dialysis are under-represented in clinical trials, and studies in this population are urgently needed.

Patient and provider experience and perspectives of a risk-based approach to multidisciplinary chronic kidney disease care: a mixed methods study

BACKGROUND

The Kidney Failure Risk Equation (KFRE) predicts risk of progression to kidney failure and is used to guide clinical decisions for patients with chronic kidney disease (CKD).

METHODS

The KFRE was implemented to guide access to multidisciplinary care for CKD patients in Alberta, Canada, based on their 2-year risk of kidney failure. We used a mixed methods approach to investigate patients' and providers' perspectives and experiences 1 year following KFRE implementation. We conducted post-implementation interviews with multidisciplinary clinic providers and with low-risk patients who transitioned from multidisciplinary to general nephrology care. We also administered pre- and post-implementation patient care experience surveys, targeting both low-risk patients discharged to general nephrology and high-risk patients who remained in the multidisciplinary clinic, and provider job satisfaction surveys.

RESULTS

Twenty-seven interviews were conducted (9 patients, 1 family member, 17 providers). Five categories were identified among patients and providers: targeted care; access to resources outside the multidisciplinary clinics; self-efficacy; patient reassurance and reduced stress; and transition process for low-risk patients Two additional categories were identified among providers only: anticipated concerns and job satisfaction. Patients and providers reported that the risk-based approach allowed the clinic to target care to those most likely to experience kidney failure and most likely to benefit from multidisciplinary care. While some participants indicated the risk-based model enhanced the sustainability of the clinics, others expressed concern that care for low-risk patients discharged from multidisciplinary care, or those now considered ineligible, may be inadequate. Overall, 413 patients completed the care experience survey and 73 providers completed the workplace satisfaction survey. The majority of patients were satisfied with their care in both periods with no overall differences. When considering the responses "Always" and "Often" together versus not, there were statistically significant improvements in domains of access to care, caring staff, and safety of care. There were no differences in healthcare providers' job satisfaction following KFRE implementation.

CONCLUSIONS

Patients and healthcare providers reported that the risk-based approach improved the focus of the multidisciplinary CKD clinics by targeting patients at highest risk, with survey results suggesting no difference in patient care experience or healthcare provider job satisfaction.

Perceived Benefits and Challenges of a Risk-Based Approach to Multidisciplinary Chronic Kidney Disease Care: A Qualitative Descriptive Study

Background:

The kidney failure risk equation (KFRE) provides an estimate of risk of progression to kidney failure, and may guide clinical care.

Objective:

We aimed to describe patient, family, and health care provider’s perspectives of the perceived benefits and challenges of using a risk-based approach to guide care delivery for patients with advanced chronic kidney disease (CKD), and refine implementation based on their input.

Methods:

We used qualitative methodology to explore perceived benefits and challenges of implementing a risk-based approach (using the KFRE) to determine eligibility for multidisciplinary CKD care in Southern Alberta. We obtained perspectives from patients and families through focus groups, as well as input from health care providers through interviews and open-ended responses from an online survey. Twelve patients/family members participated in 2 focus groups, 16 health care providers participated in an interview, and 40 health care providers responded to the survey.

Results:

Overall, participants felt that a KFRE-based approach had the potential to improve efficiency of the clinics by targeting care to patients at highest risk of kidney failure; however, they also expressed concerns about the impact of loss of services for lower risk individuals. Participants also articulated concerns about a perceived lack of capacity for adequate CKD patient care in the community. Our implementation strategy was modified as a result of participants’ feedback.

Conclusions:

We identified benefits and challenges to implementation of a risk-based approach to guide care of patients with advanced CKD. Based on these results, our implementation strategy has been modified by removing the category of referral back to primary care alone, and instead having that decision made jointly by nephrologists and patients among low-risk patients.

Implementation and Evaluation of a Risk-Based Approach to Guide Chronic Kidney Disease Care: Protocol for a Multiphase Mixed-Methods Study

Background

Risk prediction tools are used in a variety of clinical settings to guide patient care, although their use in chronic kidney disease (CKD) care is limited.

Objectives

To assess the association of a risk-based model of CKD care on patient care, satisfaction, outcomes, and cost.

Design

Mixed-methods with a pre-post design.

Setting

We will use mixed-methods and a pre-post design to evaluate use of the Kidney Failure Risk Equation (KFRE) to guide CKD care. The KFRE will be applied to patients currently followed in nephrology multidisciplinary CKD clinics in Alberta, as well as to new patients being considered for multidisciplinary care.

Patients

Patients with a 2-year risk of kidney failure ≥10% or estimated glomerular filtration rate (eGFR) ≤15 mL/min/1.73 m² will be recommended care by a multidisciplinary team coordinated by a nurse clinician and nephrologist, with access to other multidisciplinary resources including dietitians, pharmacists, and social workers as required.

Measurements/Methods

Focus groups and interviews will be conducted to qualitatively describe patient and provider perspectives of potential barriers and facilitators to implementation of the risk-based approach to CKD care. Patient and provider surveys will also be used to quantify patient and provider satisfaction before and after the intervention. Finally, administrative data will be used to evaluate the association between the risk-based approach to care and outcomes including health care resource use, frequency of testing, modality choice, and death.

Conclusions

Use of a risk-based model of care has the potential to increase use of optimal treatments such as the use of home dialysis and preemptive kidney transplantation, while reducing costs and poor outcomes related to processes of care such as unnecessary laboratory testing; however, there is also potential for unintended consequences. Our mixed-methods approach will integrate perceptions and needs from key stakeholders (including patients with CKD, their families, and their providers) to guide implementation and ensure appropriate modifications.