Using the kidney failure risk equation to predict end-stage kidney disease in CKD patients of South Asian ethnicity: an external validation study.

BACKGROUND: The kidney failure risk equation (KFRE) predicts the 2- and 5-year risk of needing kidney replacement therapy (KRT) using four risk factors - age, sex, urine albumin-to-creatinine ratio (ACR) and creatinine-based estimated glomerular filtration rate (eGFR). Although the KFRE has been recalibrated in a UK cohort, this did not consider minority ethnic groups. Further validation of the KFRE in different ethnicities is a research priority. The KFRE also does not consider the competing risk of death, which may lead to overestimation of KRT risk. This study externally validates the KFRE for patients of South Asian ethnicity and compares methods for accounting for ethnicity and the competing event of death. METHODS: Data were gathered from an established UK cohort containing 35,539 individuals diagnosed with chronic kidney disease. The KFRE was externally validated and updated in several ways taking into account ethnicity, using recognised methods for time-to-event data, including the competing risk of death. A clinical impact assessment compared the updated models through consideration of referrals made to secondary care. RESULTS: The external validation showed the risk of KRT differed by ethnicity. Model validation performance improved when incorporating ethnicity and its interactions with ACR and eGFR as additional risk factors. Furthermore, accounting for the competing risk of death improved prediction. Using criteria of 5 years ≥ 5% predicted KRT risk, the competing risks model resulted in an extra 3 unnecessary referrals (0.59% increase) but identified an extra 1 KRT case (1.92% decrease) compared to the previous best model. Hybrid criteria of predicted risk using the competing risks model and ACR ≥ 70 mg/mmol should be used in referrals to secondary care. CONCLUSIONS: The accuracy of KFRE prediction improves when updated to consider South Asian ethnicity and to account for the competing risk of death. This may reduce unnecessary referrals whilst identifying risks of KRT and could further individualise the KFRE and improve its clinical utility. Further research should consider other ethnicities.

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 <60 ml/min per 1.73 m 2 . However, the CKD-EPI 2021 creatinine equation for eGFR is now recommended for use but has not been fully tested in the context of KFRE. In 59 cohorts comprising 312,424 patients with CKD, the authors assessed the predictive performance and calibration associated with the use of the CKD-EPI 2021 equation and whether additional variables and accounting for the competing risk of death improves the KFRE's performance. The KFRE generally performed well using the CKD-EPI 2021 eGFR in populations with eGFR <45 ml/min per 1.73 m 2 and was not improved by adding the 2-year prior eGFR slope and cardiovascular comorbidities. 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 <60 ml/min per 1.73 m 2 . 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.

Major cardiovascular events and subsequent risk of kidney failure with replacement therapy: a CKD Prognosis Consortium study.

AIMS: Chronic kidney disease (CKD) increases risk of cardiovascular disease (CVD). Less is known about how CVD associates with future risk of kidney failure with replacement therapy (KFRT). METHODS AND RESULTS: The study included 25 903 761 individuals from the CKD Prognosis Consortium with known baseline estimated glomerular filtration rate (eGFR) and evaluated the impact of prevalent and incident coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF) events as time-varying exposures on KFRT outcomes. Mean age was 53 (standard deviation 17) years and mean eGFR was 89 mL/min/1.73 m2, 15% had diabetes and 8.4% had urinary albumin-to-creatinine ratio (ACR) available (median 13 mg/g); 9.5% had prevalent CHD, 3.2% prior stroke, 3.3% HF, and 4.4% prior AF. During follow-up, there were 269 142 CHD, 311 021 stroke, 712 556 HF, and 605 596 AF incident events and 101 044 (0.4%) patients experienced KFRT. Both prevalent and incident CVD were associated with subsequent KFRT with adjusted hazard ratios (HRs) of 3.1 [95% confidence interval (CI): 2.9-3.3], 2.0 (1.9-2.1), 4.5 (4.2-4.9), 2.8 (2.7-3.1) after incident CHD, stroke, HF and AF, respectively. HRs were highest in first 3 months post-CVD incidence declining to baseline after 3 years. Incident HF hospitalizations showed the strongest association with KFRT [HR 46 (95% CI: 43-50) within 3 months] after adjustment for other CVD subtype incidence. CONCLUSION: Incident CVD events strongly and independently associate with future KFRT risk, most notably after HF, then CHD, stroke, and AF. Optimal strategies for addressing the dramatic risk of KFRT following CVD events are needed.

Potential impact of NICE guidelines on referrals from primary care to nephrology: a primary care database and prospective research study.

BACKGROUND: National Institute for Health and Care Excellence 2021 guidelines on chronic kidney disease (CKD) recommend the use of the Kidney Failure Risk Equation (KFRE), which includes measurement of albuminuria. The equation to calculate estimated glomerular filtration rate (eGFR) has also been updated. AIM: To investigate the impact of the use of KFRE and the updated eGFR equation on CKD diagnosis (eGFR <60 mL/min/1.73 m2) in primary care and potential referrals to nephrology. DESIGN AND SETTING: Primary care database (Secure Anonymised Information Linkage Databank [SAIL]) and prospective cohort study (UK Biobank) using data available between 2013 and 2020. METHOD: CKD diagnosis rates were assessed when using the updated eGFR equation. Among people with eGFR 30-59 mL/min/1.73 m2 the following groups were identified: those with annual albuminuria testing and those who met nephrology referral criteria because of: a) accelerated eGFR decline or significant albuminuria; b) eGFR decline <30 mL/ min/1.73 m2 only; and c) KFRE >5% only. Analyses were stratified by ethnicity in UK Biobank. RESULTS: Using the updated eGFR equation resulted in a 1.2-fold fall in new CKD diagnoses in the predominantly White population in SAIL, whereas CKD prevalence rose by 1.9-fold among Black participants in UK Biobank. Rates of albuminuria testing have been consistently below 30% since 2015. In 2019, using KFRE >5% identified 182/61 721 (0.3%) patients at high risk of CKD progression before their eGFR declined and 361/61 721 (0.6%) low-risk patients who were no longer eligible for referral. Ethnic groups 'Asian' and 'other' had disproportionately raised KFREs. CONCLUSION: Application of KFRE criteria in primary care will lead to referral of more patients at elevated risk of kidney failure (particularly among minority ethnic groups) and fewer low-risk patients. Albuminuria testing needs to be expanded to enable wider KFRE implementation.

Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP.

AIMS: The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an 'Add-on' to incorporate CKD measures into these algorithms, using a validated approach. METHODS: In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP. We validated C-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997 719 participants from 34 different datasets. RESULTS: In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved C-statistic by 0.006 (95%CI 0.004-0.008) and 0.016 (0.010-0.023), respectively, for SCORE2 and 0.012 (0.009-0.015) and 0.024 (0.014-0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57 485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI [e.g. 0.100 (0.062-0.138) for SCORE2] compared to the qualitative approach in the ESC guideline. CONCLUSION: Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD.

Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis.

OBJECTIVE: To externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19. DESIGN: Two stage individual participant data meta-analysis. SETTING: Secondary and tertiary care. PARTICIPANTS: 46 914 patients across 18 countries, admitted to a hospital with polymerase chain reaction confirmed covid-19 from November 2019 to April 2021. DATA SOURCES: Multiple (clustered) cohorts in Brazil, Belgium, China, Czech Republic, Egypt, France, Iran, Israel, Italy, Mexico, Netherlands, Portugal, Russia, Saudi Arabia, Spain, Sweden, United Kingdom, and United States previously identified by a living systematic review of covid-19 prediction models published in The BMJ, and through PROSPERO, reference checking, and expert knowledge. MODEL SELECTION AND ELIGIBILITY CRITERIA: Prognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor. METHODS: Eight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters. MAIN OUTCOME MEASURES: 30 day mortality or in-hospital mortality. RESULTS: Datasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al's model (0.96, 0.59 to 1.55, 0.21 to 4.28). CONCLUSION: The prognostic value of the included models varied greatly between the data sources. Although the Knight 4C Mortality Score and Wang clinical model appeared most promising, recalibration (intercept and slope updates) is needed before implementation in routine care.

Development and Validation of Prediction Models of Adverse Kidney Outcomes in the Population With and Without Diabetes.

OBJECTIVE: To predict adverse kidney outcomes for use in optimizing medical management and clinical trial design. RESEARCH DESIGN AND METHODS: In this meta-analysis of individual participant data, 43 cohorts (N = 1,621,817) from research studies, electronic medical records, and clinical trials with global representation were separated into development and validation cohorts. Models were developed and validated within strata of diabetes mellitus (presence or absence) and estimated glomerular filtration rate (eGFR; ≥60 or <60 mL/min/1.73 m2) to predict a composite of ≥40% decline in eGFR or kidney failure (i.e., receipt of kidney replacement therapy) over 2-3 years. RESULTS: There were 17,399 and 24,591 events in development and validation cohorts, respectively. Models predicting ≥40% eGFR decline or kidney failure incorporated age, sex, eGFR, albuminuria, systolic blood pressure, antihypertensive medication use, history of heart failure, coronary heart disease, atrial fibrillation, smoking status, and BMI, and, in those with diabetes, hemoglobin A1c, insulin use, and oral diabetes medication use. The median C-statistic was 0.774 (interquartile range [IQR] = 0.753, 0.782) in the diabetes and higher-eGFR validation cohorts; 0.769 (IQR = 0.758, 0.808) in the diabetes and lower-eGFR validation cohorts; 0.740 (IQR = 0.717, 0.763) in the no diabetes and higher-eGFR validation cohorts; and 0.750 (IQR = 0.731, 0.785) in the no diabetes and lower-eGFR validation cohorts. Incorporating the previous 2-year eGFR slope minimally improved model performance, and then only in the higher-eGFR cohorts. CONCLUSIONS: Novel prediction equations for a decline of ≥40% in eGFR can be applied successfully for use in the general population in persons with and without diabetes with higher or lower eGFR.

Primary skeletal muscle cells from chronic kidney disease patients retain hallmarks of cachexia in vitro.

BACKGROUND: Skeletal muscle wasting and dysfunction are common characteristics noted in people who suffer from chronic kidney disease (CKD). The mechanisms by which this occurs are complex, and although progress has been made, the key underpinning mechanisms are not yet fully elucidated. With work to date primarily conducted in nephrectomy-based animal models, translational capacity to our patient population has been challenging. This could be overcome if rationale developing work could be conducted in human based models with greater translational capacity. This could be achieved using cells derived from patient biopsies, if they retain phenotypic traits noted in vivo. METHODS: Here, we performed a systematic characterization of CKD derived muscle cells (CKD; n = 10; age: 54.40 ± 15.53 years; eGFR: 22.25 ± 13.22 ml/min/1.73 m2 ) in comparison with matched controls (CON; n = 10; age: 58.66 ± 14.74 years; eGFR: 85.81 ± 8.09 ml/min/1.73 m2 ). Harvested human derived muscle cells (HDMCs) were taken through proliferative and differentiation phases and investigated in the context of myogenic progression, inflammation, protein synthesis, and protein breakdown. Follow up investigations exposed HDMC myotubes from each donor type to 0, 0.4, and 100 nM of IGF-1 in order to investigate any differences in anabolic resistance. RESULTS: Harvested human derived muscle cells isolated from CKD patients displayed higher rates of protein degradation (P = 0.044) alongside elevated expression of both TRIM63 (2.28-fold higher, P = 0.054) and fbox32 (6.4-fold higher, P < 0.001) in comparison with CONs. No differences were noted in rates of protein synthesis under basal conditions (P > 0.05); however, CKD derived cells displayed a significant degree of anabolic resistance in response to IGF-1 stimulation (both doses) in comparison with matched CONs (0.4 nm: P < 0.001; 100 nM: P < 0.001). CONCLUSIONS: In summary, we report for the first time that HDMCs isolated from people suffering from CKD display key hallmarks of the well documented in vivo phenotype. Not only do these findings provide further mechanistic insight into CKD specific cachexia, but they also demonstrate this is a reliable and suitable model in which to perform targeted experiments to begin to develop novel therapeutic strategies targeting the CKD associated decline in skeletal muscle mass and function.

Inflammation and physical dysfunction: responses to moderate intensity exercise in chronic kidney disease.

BACKGROUND: People with chronic kidney disease (CKD) experience skeletal muscle wasting, reduced levels of physical function and performance, and chronic systemic inflammation. While it is known that a relationship exists between inflammation and muscle wasting, the association between inflammation and physical function or performance in CKD has not been well studied. Exercise has anti-inflammatory effects, but little is known regarding the effect of moderate intensity exercise. This study aimed to (i) compare systemic and intramuscular inflammation between CKD stage G3b-5 and non-CKD controls; (ii) establish whether a relationship exists between physical performance, exercise capacity and inflammation in CKD; (iii) determine changes in systemic and intramuscular inflammation following 12 weeks of exercise; and (iv) investigate whether improving inflammatory status via training contributes to improvements in physical performance and muscle mass. METHODS: This is a secondary analysis of previously collected data. CKD patients stages G3b-5 (n = 84, n = 43 males) and non-CKD controls (n = 26, n = 17 males) underwent tests of physical performance, exercise capacity, muscle strength and muscle size. In addition, a subgroup of CKD participants underwent 12 weeks of exercise training, randomized to aerobic (AE, n = 21) or combined (CE, n = 20) training. Plasma and intramuscular inflammation and myostatin were measured at rest and following exercise. RESULTS: Tumour necrosis factor-α was negatively associated with lower $^{^{^{.}}}{\rm V}$O2Peak (P = 0.01), Rectus femoris-cross sectional area (P = 0.002) and incremental shuttle walk test performance (P < 0.001). Interleukin-6 was negatively associated with sit-to-stand 60 performances (P = 0.006) and hand grip strength (P = 0.001). Unaccustomed exercise created an intramuscular inflammatory response that was attenuated following 12 weeks of training. Exercise training did not reduce systemic inflammation, but AE training did significantly reduce mature myostatin levels (P = 0.02). Changes in inflammation were not associated with changes in physical performance. CONCLUSIONS: Systemic inflammation may contribute to reduced physical function in CKD. Twelve weeks of exercise training was unable to reduce the level of chronic systemic inflammation in these patients, but did reduce plasma myostatin concentrations. Further research is required to further investigate this.