The Kidney Failure Risk Equation for prediction of end stage renal disease in UK primary care: An external validation and clinical impact projection cohort study

BACKGROUND: The Kidney Failure Risk Equation (KFRE) uses the 4 variables of age, sex, urine albumin-to-creatinine ratio (ACR), and estimated glomerular filtration rate (eGFR) in individuals with chronic kidney disease (CKD) to predict the risk of end stage renal disease (ESRD), i.e., the need for dialysis or a kidney transplant, within 2 and 5 years. Currently, national guideline writers in the UK and other countries are evaluating the role of the KFRE in renal referrals from primary care to secondary care, but the KFRE has had limited external validation in primary care. The study's objectives were therefore to externally validate the KFRE's prediction of ESRD events in primary care, perform model recalibration if necessary, and assess its projected impact on referral rates to secondary care renal services. METHODS AND FINDINGS: Individuals with 2 or more Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) eGFR values < 60 ml/min/1.73 m2 more than 90 days apart and a urine ACR or protein-to-creatinine ratio measurement between 1 December 2004 and 1 November 2016 were included in the cohort. The cohort included 35,539 (5.6%) individuals (57.5% female, mean age 75.9 years, median CKD-EPI eGFR 51 ml/min/1.73 m2, median ACR 3.2 mg/mmol) from a total adult practice population of 630,504. Overall, 176 (0.50%) and 429 (1.21%) ESRD events occurred within 2 and 5 years, respectively. Median length of follow-up was 4.7 years (IQR 2.8 to 6.6). Model discrimination was excellent for both 2-year (C-statistic 0.932, 95% CI 0.909 to 0.954) and 5-year (C-statistic 0.924, 95% 0.909 to 0.938) ESRD prediction. The KFRE overpredicted risk in lower (<20%) risk groups. Reducing the model's baseline risk improved calibration for both 2- and 5-year risk for lower risk groups, but led to some underprediction of risk in higher risk groups. Compared to current criteria, using referral criteria based on a KFRE-calculated 5-year ESRD risk of ≥5% and/or an ACR of ≥70 mg/mmol reduced the number of individuals eligible for referral who did not develop ESRD, increased the likelihood of referral eligibility in those who did develop ESRD, and referred the latter at a younger age and with a higher eGFR. The main limitation of the current study is that the cohort is from one region of the UK and therefore may not be representative of primary care CKD care in other countries. CONCLUSIONS: In this cohort, the recalibrated KFRE accurately predicted the risk of ESRD at 2 and 5 years in primary care. Its introduction into primary care for referrals to secondary care renal services may lead to a reduction in unnecessary referrals, and earlier referrals in those who go on to develop ESRD. However, further validation studies in more diverse cohorts of the clinical impact projections and suggested referral criteria are required before the latter can be clinically implemented

Association between native T1 mapping of the kidney and renal fibrosis in patients with IgA nephropathy.

INTRODUCTION: IgA nephropathy (IgAN) is the commonest global cause of glomerulonephritis. Extent of fibrosis, tubular atrophy and glomerulosclerosis predict renal function decline. Extent of renal fibrosis is assessed with renal biopsy which is invasive and prone to sampling error. We assessed the utility of non-contrast native T1 mapping of the kidney in patients with IgAN for assessment of renal fibrosis. METHODS: Renal native T1 mapping was undertaken in 20 patients with IgAN and 10 healthy subjects. Ten IgAN patients had a second scan to assess test-retest reproducibility of the technique. Native T1 times were compared to markers of disease severity including degree of fibrosis, eGFR, rate of eGFR decline and proteinuria. RESULTS: All patients tolerated the MRI scan and analysable quality T1 maps were acquired in at least one kidney in all subjects. Cortical T1 times were significantly longer in patients with IgAN than healthy subjects (1540 ms ± 110 ms versus 1446 ± 88 ms, p = 0.038). There was excellent test-retest reproducibility of the technique, with Coefficient-of-variability of axial and coronal T1 mapping analysis being 2.9 and 3.7% respectively. T1 correlated with eGFR and proteinuria (r = - 0.444, p = 0.016; r = 0.533, p = 0.003 respectively). Patients with an eGFR decline > 2 ml/min/year had increased T1 times compared to those with a decline  0, compared to those with a 'T'-score of 0 (1575 ± 106 ms versus 1496 ± 105 ms, p = 0.131), though not to significance. CONCLUSIONS: Cortical native T1 time is significantly increased in patients with IgAN compared to healthy subjects and correlates with markers of renal disease. Reproducibility of renal T1 mapping is excellent. This study highlights the potential utility of native T1 mapping in IgAN and other progressive nephropathies, and larger prospective studies are warranted

An Innovative Chemical Adherence Test Demonstrates Very High Rates of Nonadherence to Oral Cardio-Metabolic Medications

Chronic kidney disease (CKD) is one of the leading causes of death worldwide. About 13% of the world’s population are living with CKD; and over the last 20 years, there has been over a 40% increase in mortality rates due to CKD.1,2 Compared to patients without CKD, CKD stages G3a to G4 (estimated glomerular filtration rate 15–60 ml/min per 1.73 m2) is associated with a 2 to 3 fold increase in risk of cardiovascular disease mortality.3 It is estimated that about 17% to 74% of patients with CKD are nonadherent to their medications.4 Improvement in adherence has been identified as a key strategy to enhance cardiovascular outcomes.5 However, the diagnosis of nonadherence, until recently, was difficult due to the lack of objective tools in busy clinics because some subjective methods have been found to be unreliable.6 Chemical adherence testing (CAT) is a novel, objective, robust and clinically reliable test that uses liquid-chromatography tandem mass spectrometry to assess adherence to medications. A random spot urine or blood sample is screened to determine the presence or absence of 70 of the most common cardio-metabolic medications (Supplementary Table S1) (including antihypertensives, lipid lowering medications, and glucose lowering drugs).7 There are guidelines available to help implement the use of the test and address common questions about the clinical use of the test.7 Currently, CAT is being used in routine care in some specialist hypertension clinics across Europe and has been recommended by the European Society of Cardiology and the European Society of Hypertension as the method to be used to measure adherence in patients with suspected resistant hypertension.8 The use of CAT is limited outside of hypertension and to the best of our knowledge there has been no publication that has used CAT to diagnose medication nonadherence in renal patients. The aim of this study was therefore to demonstrate and highlight the usefulness of CAT to determine the prevalence of nonadherence to cardio-metabolic medications in patients attending routine renal clinics.</p

Seroprevalence of antibody to S1 spike protein following vaccination against COVID-19 in patients receiving hemodialysis: a call to arms

Letter to the EditorSeroprevalence of antibody to S1 spike protein following vaccination against COVID-19 in patients receiving hemodialysis: a call to arms</div

Cohort profile: Extended Cohort for E-health, Environment and DNA (EXCEED).

[First paragraph] EXCEED aims to develop understanding of the genetic, environmental and lifestyle-related causes of health and disease. Cohorts like EXCEED, with broad consent to study multiple phenotypes related to onset and progression of disease and drug response, have a role to play in medicines development, by providing genetic evidence that can identify, support or refute putative drug efficacy or identify possible adverse effects.1 Furthermore, such cohorts are well suited to the study of multimorbidity

The Kidney Failure Risk Equation: Evaluation of Novel Input Variables including eGFR Estimated Using the CKD-EPI 2021 Equation in 59 Cohorts

  Significance statement: The kidney failure risk equation (KFRE) uses age, sex, GFR, and urine albumin-to-creatinine ratio (ACR) to predict 2- and 5-year risk of kidney failure in populations with eGFR Background: The kidney failure risk equation (KFRE) uses age, sex, GFR, and urine albumin-to-creatinine ratio (ACR) to predict kidney failure risk in people with GFR Methods: Using 59 cohorts with 312,424 patients with CKD, we tested several modifications to the KFRE for their potential to improve the KFRE: using the CKD-EPI 2021 creatinine equation for eGFR, substituting 1-year average ACR for single-measure ACR and 1-year average eGFR in participants with high eGFR variability, and adding 2-year prior eGFR slope and cardiovascular comorbidities. We also assessed calibration of the KFRE in subgroups of eGFR and age before and after accounting for the competing risk of death. Results: The KFRE remained accurate and well calibrated overall using the CKD-EPI 2021 eGFR equation. The other modifications did not improve KFRE performance. In subgroups of eGFR 45-59 ml/min per 1.73 m 2 and in older adults using the 5-year time horizon, the KFRE demonstrated systematic underprediction and overprediction, respectively. We developed and tested a new model with a spline term in eGFR and incorporating the competing risk of mortality, resulting in more accurate calibration in those specific subgroups but not overall. Conclusions: The original KFRE is generally accurate for eGFR <45 ml/min per 1.73 m 2 when using the CKD-EPI 2021 equation. Incorporating competing risk methodology and splines for eGFR may improve calibration in low-risk settings with longer time horizons. Including historical averages, eGFR slopes, or a competing risk design did not meaningfully alter KFRE performance in most circumstances.</p

Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets

Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. “CKD Patch” is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures. Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several “CKD Patches” incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch. Findings: We confirmed the prediction improvement with the CKD Patch for CVD mortality beyond SCORE and ASCVD beyond PCE in validation datasets (Δc-statistic 0.027 [95% CI 0.018–0.036] and 0.010 [0.007–0.013] and categorical net reclassification improvement 0.080 [0.032–0.127] and 0.056 [0.044–0.067], respectively). The median (IQI) of the ratio of predicted risk for CVD mortality with CKD Patch vs. the original prediction with SCORE was 2.64 (1.89–3.40) in very high-risk CKD (e.g., eGFR 30–44 ml/min/1.73m2 with albuminuria ≥30 mg/g), 1.86 (1.48–2.44) in high-risk CKD (e.g., eGFR 45–59 ml/min/1.73m2 with albuminuria 30–299 mg/g), and 1.37 (1.14–1.69) in moderate risk CKD (e.g., eGFR 60–89 ml/min/1.73m2 with albuminuria 30–299 mg/g), indicating considerable risk underestimation in CKD with SCORE. The corresponding estimates for ASCVD with PCE were 1.55 (1.37–1.81), 1.24 (1.10–1.54), and 1.21 (0.98–1.46). Interpretation: The “CKD Patch” can be used to quantitatively enhance ASCVD and CVD mortality risk prediction equations recommended in major US and European guidelines according to CKD measures, when available. Funding: US National Kidney Foundation and the NIDDK