Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis.

Importance: Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US. Objective: To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes. Design, Setting, and Participants: Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021. Exposures: The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR). Main Outcomes and Measures: The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses. Results: Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years]). Conclusions and Relevance: In this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations.

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.

Risk factors associated with COVID-19 severity among patients on maintenance haemodialysis: a retrospective multicentre cross-sectional study in the UK.

OBJECTIVES: To assess the applicability of risk factors for severe COVID-19 defined in the general population for patients on haemodialysis. SETTING: A retrospective cross-sectional study performed across thirty four haemodialysis units in midlands of the UK. PARTICIPANTS: All 274 patients on maintenance haemodialysis who tested positive for SARS-CoV-2 on PCR testing between March and August 2020, in participating haemodialysis centres. EXPOSURE: The utility of obesity, diabetes status, ethnicity, Charlson Comorbidity Index (CCI) and socioeconomic deprivation scores were investigated as risk factors for severe COVID-19. MAIN OUTCOMES AND MEASURES: Severe COVID-19, defined as requiring supplemental oxygen or respiratory support, or a C reactive protein of ≥75 mg/dL (RECOVERY trial definitions), and its association with obesity, diabetes status, ethnicity, CCI, and socioeconomic deprivation. RESULTS: 63.5% (174/274 patients) developed severe disease. Socioeconomic deprivation associated with severity, being most pronounced between the most and least deprived quartiles (OR 2.81, 95% CI 1.22 to 6.47, p=0.015), after adjusting for age, sex and ethnicity. There was no association between obesity, diabetes status, ethnicity or CCI with COVID-19 severity. We found no evidence of temporal evolution of cases (p=0.209) or clustering that would impact our findings. CONCLUSION: The incidence of severe COVID-19 is high among patients on haemodialysis; this cohort should be considered high risk. There was strong evidence of an association between socioeconomic deprivation and COVID-19 severity. Other risk factors that apply to the general population may not apply to this cohort.

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.

Aspirin for the primary prevention of cardiovascular disease in individuals with chronic kidney disease: a systematic review and meta-analysis.

AIMS: Cardiovascular disease (CVD) is the major cause of morbidity and mortality in individuals with chronic kidney disease (CKD). This study assessed the risks and benefits of aspirin in the primary prevention of CVD in individuals with CKD. METHODS AND RESULTS: Ovid MEDLINE was searched from 2015 to 15th of September 2020 to include randomized controlled trials that assessed aspirin versus placebo in adults with non-end stage CKD without a previous diagnosis of CVD. A pre-specified protocol was registered with PROSPERO (identification number CRD42014008860). A random effects model was used to calculate a pooled hazard ratio (HR), pooled risk difference, and the number needed to treat or harm (NNT/NNH). The primary endpoint was CVD. Secondary endpoints included: all-cause mortality; coronary heart disease; stroke; and major and minor bleeding events. Five trials were identified (n = 7852 total, n = 3935 aspirin, n = 3917 placebo). Overall, 434 CVD events occurred. There was no statistically significant reduction in CVD events (HR 0.76, 95% confidence interval (CI) 0.54-1.08; P = 0.13, I2 = 63%), all-cause mortality (HR 0.94, 95% CI 0.74-1.19; P = 0.60, I2 = 21%), coronary heart disease events (HR 0.66, 95% CI 0.27-1.63; P = 0.37, I2 = 64%) or stroke (HR 0.87, 95% CI 0.6-1.27; P = 0.48, I2 = 24%) from aspirin therapy. The risk of major bleeding events were increased by approximately 50% (HR 1.53, 95% CI 1.13-2.05; P = 0.01, I2 = 0%) and minor bleeding events were more than doubled (HR 2.64, 95% CI 1.64-4.23; P < 0.01, I2 = 0%). CONCLUSIONS: Aspirin cannot be routinely recommended for the primary prevention of CVD in individuals with CKD as there is no evidence for its benefit but there is an increased risk of bleeding.

The impact of amino acid dialysate on anthropometric measures in adult patients on peritoneal dialysis: A systematic review and meta-analysis.

BACKGROUND: Glucose-containing dialysate underpins peritoneal dialysis (PD) therapy. However, its use is associated with amino acid loss in the dialysis effluent, a risk factor for protein-energy wasting (PEW) in PD patients. Amino acid-based dialysis solutions (AAD) may ameliorate this loss. However, the evidence of clinical benefit in preventing PEW is unclear. The aim of this review was to assess the effect of AAD versus standard dialysis solutions (STD) on anthropometric measures and serum albumin. METHODS: Studies up until 30 September 2020 were identified from databases including MEDLINE and Embase, using a prespecified protocol (PROSPERO - CRD42020209581). Studies evaluating adults on PD were included. Data pertaining to muscle mass (primary outcome), other anthropometric measures and serum albumin were extracted. A meta-analysis of the eligible studies was conducted. RESULTS: A total of 6945 abstracts were reviewed, from which 14 studies (9 randomised and 5 non-randomised) were included. There was no significant difference in any of the anthropometric measures, between AAD and STD during follow-up. Serum albumin at 6 months was statistically lower with AAD compared to STD [mean difference = -0.89 (95%CI -1.77 to -0.01, p = 0.046)]. The quality of evidence was graded low for each outcome. CONCLUSIONS: AAD may not alter anthropometric measures when compared to STD. The impact on serum albumin is uncertain, with an estimated difference that is unlikely to be of clinical value. These findings should be cautiously interpreted due to low quality of the evidence. Robust studies are needed to address the limitations in evidence.

The association of blood pressure variability with adverse outcomes in a primary care chronic kidney disease cohort.

BACKGROUND: Hypertension is common in individuals with chronic kidney disease and both conditions are associated with adverse outcomes including cardiovascular morbidity. Therefore, it is clinically important to identify methods of risk prediction in individuals with chronic kidney disease. Blood pressure variability has recently emerged as a predictor of cardiovascular events and mortality in the general population, with growing evidence indicating that it may play a similar role in individuals with chronic kidney disease. However, there have been no large studies assessing blood pressure variability in individuals with chronic kidney disease in primary care, where the majority of these patients are managed. METHOD: Using a retrospective observational study design, we analyzed routinely collected blood pressure readings from 16 999 individuals in The Leicester and County Chronic Kidney Disease cohort. Standard deviation, coefficient of variation and average real variability of SBP were used to calculate blood pressure variability. RESULTS: During a median follow-up of 5.0 (IQR 3.3--5.0) years, 2053 (12.1%) patients had cardiovascular events, death occurred in 5021 (29.6%) individuals and 156 (0.9%) individuals had endstage kidney disease events. In adjusted models, standard deviation and coefficient of variation were associated with cardiovascular events, all-cause mortality and endstage kidney disease. Average real variability was associated with all-cause mortality and cardiovascular events, but not endstage kidney disease. CONCLUSION: Blood pressure variability may be an accessible, routinely collected, noninvasive measure for stratifying the risk of adverse events in individuals with chronic kidney disease in a primary care setting.

Association between vitamin D deficiency and exercise capacity in patients with CKD, a cross-sectional analysis.

BACKGROUND: Evidence is growing for a role of vitamin D in regulating skeletal muscle mass, strength and functional capacity. Given the role the kidneys play in activating total vitamin D, and the high prevalence of vitamin D deficiency in Chronic Kidney Disease (CKD), it is possible that deficiency contributes to the low levels of physical function and muscle mass in these patients. METHODS: This is a secondary cross-sectional analysis of previously published interventional study, with in vitro follow up work. 34 CKD patients at stages G3b-5 (eGFR 25.5 ± 8.3 mL/min/1.73m2; age 61 ± 12 years) were recruited, with a sub-group (n = 20) also donating a muscle biopsy. Vitamin D and associated metabolites were analysed in plasma by liquid chromatography tandem-mass spectroscopy and correlated to a range of physiological tests of muscle size, function, exercise capacity and body composition. The effects of 1α,25(OH)2D3 supplementation on myogenesis and myotube size was investigated in primary skeletal muscle cells from vitamin D deficient donors. RESULTS: In vivo, there was no association between total or active vitamin D and muscle size or strength, but a significant correlation with V̇O2Peak was seen with total vitamin D (25OHD). in vitro, 1α,25(OH)2D3 supplementation reduced IL-6 mRNA expression, but had no effect upon proliferation, differentiation or myotube diameter. CONCLUSIONS: Vitamin D deficiency is not a prominent factor driving the loss of muscle mass in CKD, but may play a role in reduced exercise capacity.

"To take or not to take an aspirin?" The age-old question of cardiovascular disease primary prevention for people with chronic kidney disease.

Despite the higher risk of cardiovascular events in patients with chronic kidney disease, the role of aspirin for primary prevention is unclear. In the current issue, Wolfe et al. present a subgroup analysis of the ASPirin in Reducing Events in the Elderly (ASPREE) trial that suggests there was no reduction in cardiovascular events but bleeding events were doubled. Aspirin cannot be recommended for primary prevention in chronic kidney disease, but the continuation of ongoing research, such as the Aspirin To Target Arterial Events in Chronic Kidney Disease (ATTACK trial), is warranted.

Comorbidities and outcomes in South Asian individuals with chronic kidney disease: an observational primary care cohort.

BACKGROUND: South Asian (SA) individuals are more likely to develop end-stage renal disease (ESRD), but how chronic kidney disease (CKD) differs in relation to demographics, comorbidities and outcomes has not been studied. We aimed to study differences in SA individuals with CKD compared with White individuals. METHODS: This was an observational CKD cohort comparing SA with White individuals. Inclusion criteria were ≥18 years of age and two or more Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) eGFRs <60 mL/min/1.73 m2 >3 months apart. Individuals with ESRD at baseline were excluded. Baseline characteristics, including eGFR formulae [CKD-EPI and CKD-EPI-Pakistan (CKD-EPI-PK)], were compared. Analysis using competing risk regression for cardiovascular (CV) and ESRD events and Cox proportional hazard model for mortality was performed. RESULTS: From an adult population of 277 248 individuals, 17 248 individuals had CKD, of whom 1990 (11.5%) were of SA ethnicity. Age-adjusted prevalence of CKD was similar between ethnicities. SA individuals were more likely to be male, younger and socioeconomically deprived, and to have diabetes mellitus, CV disease and advanced CKD. Mean CKD-EPI-PK eGFR was 6.5 mL/min/1.73 m2 lower (41.1 versus 47.6, 95% confidence interval for difference 6.47-6.56) than for CKD-EPI. During 5 years of follow-up, 5109 (29.6%) individuals died, 2072 (12.0%) had a CV and 156 (0.90%) an ESRD event. Risk for SA individuals was higher for ESRD, similar to CV events and lower for mortality. Each 1 mL/min/1.73 m2 decrease in CKD-EPI-PK was associated with a 13.1% increased ESRD risk (adjusted subdistribution hazard ratio 0.869, 95% confidence interval 0.841-0.898). CONCLUSIONS: SA individuals with CKD were younger and had more advanced disease than White individuals. Risk of ESRD was higher and CKD-EPI-PK was associated with ESRD risk in SA individuals. Specific CKD interventions, including the use of CKD-EPI-PK, should be considered in SA populations.

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.