VALOR-CKD: A Multicenter, Randomized, Double-Blind Placebo-Controlled Trial Evaluating Veverimer in Slowing Progression of CKD in Patients with Metabolic Acidosis.

SIGNIFICANCE STATEMENT: Metabolic acidosis is a common complication of CKD and is associated with more rapid decline of kidney function, but well-powered controlled randomized trials testing the effect of treating metabolic acidosis on slowing CKD progression have not been conducted. The VALOR-CKD study randomized 1480 individuals with CKD and metabolic acidosis, across 320 sites to placebo or veverimer (a novel hydrochloric acid binder). The findings did not demonstrate the efficacy of veverimer in slowing CKD progression, but the difference in serum bicarbonate between placebo and drug arms was only approximately 1 mEq/L. Veverimer was safe and well tolerated. BACKGROUND: Metabolic acidosis is common in CKD, but whether its treatment slows CKD progression is unknown. Veverimer, a novel hydrochloric acid binder that removes acid from the gastrointestinal tract, leads to an increase in serum bicarbonate. METHODS: In a phase 3, double-blind, placebo-controlled trial, patients with CKD (eGFR of 20-40 ml/min per 1.73 m 2 ) and metabolic acidosis (serum bicarbonate of 12-20 mEq/L) from 35 countries were randomized to veverimer or placebo. The primary outcome was the composite end point of CKD progression, defined as the development of ESKD (kidney transplantation or maintenance dialysis), a sustained decline in eGFR of ≥40% from baseline, or death due to kidney failure. RESULTS: The mean (±SD) baseline eGFR was 29.2±6.3 ml/min per 1.73 m 2 , and serum bicarbonate was 17.5±1.4 mEq/L; this increased to 23.4±2.0 mEq/L after the active treatment run-in. After randomized withdrawal, the mean serum bicarbonate was 22.0±3.0 mEq/L and 20.9±3.3 mEq/L in the veverimer and placebo groups at month 3, and this approximately 1 mEq/L difference remained stable for the first 24 months. A primary end point event occurred in 149/741 and 148/739 patients in the veverimer and placebo groups, respectively (hazard ratio, 0.99; 95% confidence interval, 0.8 to 1.2; P = 0.90). Serious and overall adverse event incidence did not differ between the groups. CONCLUSIONS: Among patients with CKD and metabolic acidosis, treatment with veverimer did not slow CKD progression. The lower than expected bicarbonate separation may have hindered the ability to test the hypothesis. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: VALOR-CKD, NCT03710291 .

Executive summary of the KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease: known knowns and known unknowns.

The Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease (CKD) updates the KDIGO 2012 guideline and has been developed with patient partners, clinicians, and researchers around the world, using robust methodology. This update, based on a substantially broader base of evidence than has previously been available, reflects an exciting time in nephrology. New therapies and strategies have been tested in large and diverse populations that help to inform care; however, this guideline is not intended for people receiving dialysis nor those who have a kidney transplant. The document is sensitive to international considerations, CKD across the lifespan, and discusses special considerations in implementation. The scope includes chapters dedicated to the evaluation and risk assessment of people with CKD, management to delay CKD progression and its complications, medication management and drug stewardship in CKD, and optimal models of CKD care. Treatment approaches and actionable guideline recommendations are based on systematic reviews of relevant studies and appraisal of the quality of the evidence and the strength of recommendations which followed the "Grading of Recommendations Assessment, Development, and Evaluation" (GRADE) approach. The limitations of the evidence are discussed. The guideline also provides practice points, which serve to direct clinical care or activities for which a systematic review was not conducted, and it includes useful infographics and describes an important research agenda for the future. It targets a broad audience of people with CKD and their healthcare, while being mindful of implications for policy and payment.

Prediction models for earlier stages of chronic kidney disease.

PURPOSE OF REVIEW: Identifying patients with risk of developing progressive chronic kidney disease (CKD) early is an important step in improving kidney care. This review discusses four recently developed models, two which predict risk of new onset disease, and two which predict progression earlier in the course of disease. RECENT FINDINGS: Several models predicting CKD incidence and progression have been recently developed and externally validated. A connecting theme across these models is the use of data beyond estimated glomerular filtration rate, allowing for greater accuracy and personalization. Two models were developed with stratification by diabetes status, displaying excellent model fit with and without variables like use of diabetes medication and hemoglobin A1C. Another model was designed to be patient facing, not requiring the knowledge of any laboratory values for use. The final model was developed using lab data and machine learning. These models demonstrated high levels of discrimination and calibration in external validation, suggesting suitability for clinical use. SUMMARY: Models that predict risk of CKD onset and progression have the potential to significantly reduce disease burden, financial cost, and environmental output from CKD through upstream disease prevention and slowed progression. These models should be implemented and evaluated prospectively in primary care settings.

Suboptimal monitoring and management in patients with unrecorded stage 3 chronic kidney disease in real-world settings: Insights from REVEAL-CKD.

BACKGROUND: Clinical practice guidelines for patients with chronic kidney disease (CKD) recommend regular monitoring and management of kidney function and CKD risk factors. However, the majority of patients with stage 3 CKD lack a diagnosis code, and data on the implementation of these recommendations in the real world are limited. AIM: To assess the implementation of guideline-directed monitoring and management practices in the real world in patients with stage 3 CKD without a recorded diagnosis code. METHODS: REVEAL-CKD (NCT04847531) is a multinational, observational study of patients with stage 3 CKD. Eligible patients had ≥2 consecutive estimated glomerular filtration rate (eGFR) measurements indicative of stage 3 CKD recorded >90 and ≤730 days apart, lacked an International Classification of Diseases 9/10 diagnosis code corresponding to CKD any time before and up to 6 months after the second eGFR measurement. Testing of key measures of care quality were assessed. RESULTS: The study included 435,971 patients from 9 countries. In all countries, the prevalence of urinary albumin-creatinine ratio and albuminuria testing was low. Angiotensin-converting enzyme inhibitor, angiotensin receptor blocker and statin prescriptions were highly variable, and sodium-glucose cotransporter-2 inhibitor prescriptions remained below 21%. Blood pressure measurements were recorded in 20.2%-89.9% of patients. CONCLUSIONS: Overall, a large proportion of patients with evidence of stage 3 CKD did not receive recommended, guideline-directed monitoring and management. The variability in standard of care among countries demonstrates a clear opportunity to improve monitoring and management of these patients, most likely improving long-term outcomes.

Population-wide eGFR percentiles in younger adults and clinical outcomes.

BACKGROUND AND HYPOTHESIS: Identifying meaningful estimated glomerular filtration rate (eGFR) reductions in younger adults (<65 years) could guide prevention efforts. To aid in interpretation and identification of young adults at risk, we examined the association of population-level eGFR percentiles relative to the median by age and clinical outcomes. METHODS: We conducted a retrospective cohort study of 8.7 million adults from Ontario, Canada from age 18 to 65 from 2008 to 2021 with an eGFR measure (both single outpatient value and repeat measures). We calculated median eGFR values by age and examined the association of reduced eGFR percentiles (≤10th, 5th, 2.5th and 1st) with outcomes using time to event models. Outcomes were a composite of all-cause mortality, major adverse cardiac outcomes (MACE) with/without heart failure (MACE+) and kidney failure as well as each component individually. RESULTS: From age 18 to 65, the median eGFR declined with age (range 128 to 90) and across percentiles [eGFR ranges 102 to 68 for ≤10th, 96 to 63 for ≤5th, 90 to 58 for ≤2.5th and 83 to 54 for 1st]. The adjusted rate for any adverse outcome was elevated at ≤ 10th percentile (HR 1.14 95%CI 1.10-1.18) and was consistent for all-cause mortality, MACE, MACE+ and predominant for kidney failure (HR 5.57 95%CI 3.79-8.19) compared to the median eGFR for age. Young adults with an eGFR in the lower percentiles were less likely to be referred to a specialist, have a repeat eGFR or albumin to creatinine ratio measure. CONCLUSIONS: eGFR values at the 10th percentile or lower based on a population-level distribution are associated with adverse clinical outcomes and in younger adults (18 to 39) this corresponds to a higher level of eGFR that may be underrecognized. Application of population-based eGFR percentiles may aid interpretation and improve identification of younger adults at risk.

Machine learning for prediction of chronic kidney disease progression: Validation of the Klinrisk model in the CANVAS Program and CREDENCE trial.

AIM: To validate the Klinrisk machine learning model for prediction of chronic kidney disease (CKD) progression in patients with type 2 diabetes in the pooled CANVAS/CREDENCE trials. MATERIALS AND METHODS: We externally validated the Klinrisk model for prediction of CKD progression, defined as 40% or higher decline in estimated glomerular filtration rate (eGFR) or kidney failure. Model performance was assessed for prediction up to 3 years with the area under the receiver operating characteristic curve (AUC), Brier scores and calibration plots of observed and predicted risks. We compared performance of the model with standard of care using eGFR (G1-G4) and urine albumin-creatinine ratio (A1-A3) Kidney Disease Improving Global Outcomes (KDIGO) heatmap categories. RESULTS: The Klinrisk model achieved an AUC of 0.81 (95% confidence interval [CI] 0.78-0.83) at 1 year, and 0.88 (95% CI 0.86-0.89) at 3 years. The Brier scores were 0.020 (0.018-0.022) and 0.056 (0.052-0.059) at 1 and 3 years, respectively. Compared with the KDIGO heatmap, the Klinrisk model had improved performance at every interval (P < .01). CONCLUSIONS: The Klinrisk machine learning model, using routinely collected laboratory data, was highly accurate in its prediction of CKD progression in the CANVAS/CREDENCE trials. Integration of the model in electronic medical records or laboratory information systems can facilitate risk-based care.

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.

Novel anemia therapies in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference.

Anemia is common in patients with chronic kidney disease and is associated with a high burden of morbidity and adverse clinical outcomes. In 2012, Kidney Disease: Improving Global Outcomes (KDIGO) published a guideline for the diagnosis and management of anemia in chronic kidney disease. Since then, new data from studies assessing established and emerging therapies for the treatment of anemia and iron deficiency have become available. Beginning in 2019, KDIGO planned 2 Controversies Conferences to review the new evidence and its potential impact on the management of anemia in clinical practice. Here, we report on the second of these conferences held virtually in December 2021, which focused on a new class of agents-the hypoxia-inducible factor-prolyl hydroxylase inhibitors (HIF-PHIs). This report provides a review of the consensus points and controversies from this second conference and highlights areas that warrant prioritization for future research.

A Predictive Model for Kidney Failure After Nephrectomy for Localized Kidney Cancer: The Kidney Cancer Risk Equation.

RATIONALE & OBJECTIVE: Nephrectomy is the mainstay of treatment for individuals with localized kidney cancer. However, surgery can potentially result in the loss of kidney function or in kidney failure requiring dialysis/kidney transplantation. There are currently no clinical tools available to preoperatively identify which patients are at risk of kidney failure over the long term. Our study developed and validated a prediction equation for kidney failure after nephrectomy for localized kidney cancer. STUDY DESIGN: Population-level cohort study. SETTING & PARTICIPANTS: Adults (n=1,026) from Manitoba, Canada, with non-metastatic kidney cancer diagnosed between January 1, 2004, and December 31, 2016, who were treated with either a partial or radical nephrectomy and had at least 1 estimated glomerular filtration rate (eGFR) measurement before and after nephrectomy. A validation cohort included individuals in Ontario (n=12,043) with a diagnosis of localized kidney cancer between October 1, 2008, and September 30, 2018, who received a partial or radical nephrectomy and had at least 1 eGFR measurement before and after surgery. NEW PREDICTORS & ESTABLISHED PREDICTORS: Age, sex, eGFR, urinary albumin-creatinine ratio, history of diabetes mellitus, and nephrectomy type (partial/radical). OUTCOME: The primary outcome was a composite of dialysis, transplantation, or an eGFR<15mL/min/1.73m2 during the follow-up period. ANALYTICAL APPROACH: Cox proportional hazards regression models evaluated for accuracy using area under the receiver operating characteristic curve (AUC), Brier scores, calibration plots, and continuous net reclassification improvement. We also implemented decision curve analysis. Models developed in the Manitoba cohort were validated in the Ontario cohort. RESULTS: In the development cohort, 10.3% reached kidney failure after nephrectomy. The final model resulted in a 5-year area under the curve of 0.85 (95% CI, 0.78-0.92) in the development cohort and 0.86 (95% CI, 0.84-0.88) in the validation cohort. LIMITATIONS: Further external validation needed in diverse cohorts. CONCLUSIONS: Our externally validated model can be easily applied in clinical practice to inform preoperative discussions about kidney failure risk in patients facing surgical options for localized kidney cancer. PLAIN-LANGUAGE SUMMARY: Patients with localized kidney cancer often experience a lot of worry about whether their kidney function will remain stable or will decline if they choose to undergo surgery for treatment. To help patients make an informed treatment decision, we developed a simple equation that incorporates 6 easily accessible pieces of patient information to predict the risk of reaching kidney failure 5 years after kidney cancer surgery. We expect that this tool has the potential to inform patient-centered discussions tailored around individualized risk, helping ensure that patients receive the most appropriate risk-based care.

A National Registry for People With All Stages of Kidney Disease: The National Kidney Foundation (NKF) Patient Network.

RATIONALE & OBJECTIVE: The National Kidney Foundation (NKF) launched the first national US kidney disease patient registry, the NKF Patient Network, that is open to patients throughout the continuum of chronic kidney disease (CKD). The Network provides individualized education and will facilitate patient-centered research, clinical care, and health policy decisions. Here, we present the overall design and the results of a feasibility study that was conducted July through December 2020. STUDY DESIGN: Longitudinal observational cohort study of patient-entered data with or without electronic health care record (EHR) linkage in collaboration with health systems. SETTING & PARTICIPANTS: People with CKD, age≥18 years, are invited through their provider, NKF communications, or national outreach campaign. People self-enroll and share their data through a secure portal that offers individualized education and support. The first health system partner is Geisinger. EXPOSURE: Any cause and stage of CKD, including dialysis and kidney transplant recipients. OUTCOME: Feasibility of the EHR data transfer, participants' characteristics, and their perspectives on usability and content. ANALYTICAL APPROACH: Data were collected and analyzed through the registry portal powered by the Pulse Infoframe healthie 2.0 platform. RESULTS: During the feasibility study, 80 participants completed their profile, and 42 completed a satisfaction survey. Mean age was 57.5 years, 51% were women, 83% were White, and 89% were non-Hispanic or Latino. Of the participants, 60% were not aware of their level of estimated glomerular filtration rate and 91% of their urinary albumin-creatinine ratio. LIMITATIONS: Challenges for the Network are lack of awareness of kidney disease for many with CKD, difficulty in recruiting vulnerable populations or those with low digital readiness, and loss to follow-up, all leading to selection bias. CONCLUSIONS: The Network is positioned to become a national and international platform for real-world data that can inform the development of patient-centered research, care, and treatments.

Metabolic acidosis is undertreated and underdiagnosed: a retrospective cohort study.

BACKGROUND: Guidelines recommend treatment of metabolic acidosis (MA) in patients with chronic kidney disease (CKD), but the diagnosis and treatment rates in real-world settings are unknown. We investigated the frequency of MA treatment and diagnosis in patients with CKD. METHODS: In this retrospective cohort study, we examined administrative health data from two US databases [Optum's de-identified Integrated Claims + Clinical Electronic Health Record Database (US EMR cohort; 1 January 2007 to 30 June 2019) and Symphony Health Solutions IDV® (US claims cohort; 1 May 2016 to 30 April 2019)] and population-level databases from Manitoba, Canada (1 April 2006 to 31 March 2018). Patients who met laboratory criteria indicative of CKD and chronic MA were included: two consecutive estimated glomerular filtration results <60 mL/min/1.73 m2 and two serum bicarbonate results 12 to <22 mEq/L over 28-365 days. Outcomes included treatment of MA (defined as a prescription for oral sodium bicarbonate) and a diagnosis of MA (defined using administrative records). Outcomes were assessed over a 3-year period (1 year pre-index, 2 years post-index). RESULTS: A total of 96 184 patients were included: US EMR, 6179; Manitoba, 3223; US Claims, 86 782. Sodium bicarbonate treatment was prescribed for 17.6%, 8.7% and 15.3% of patients, and a diagnosis was found for 44.7%, 20.9% and 20.9% of patients, for the US EMR, Manitoba and US Claims cohorts, respectively. CONCLUSIONS: This analysis of 96 184 patients with laboratory-confirmed MA from three independent cohorts of patients with CKD and MA highlights an important diagnosis and treatment gap for this disease-modifying complication.

The association between dual RAAS inhibition and risk of acute kidney injury and hyperkalemia in patients with diabetic kidney disease: a systematic review and meta-analysis.

BACKGROUND AND OBJECTIVES: Dual renin-angiotensin-aldosterone system (RAAS) blockade involves dual therapy with a combination of angiotensin-converting enzyme inhibitors (ACEis), angiotensin-receptor blockers (ARBs), direct renin inhibitors (DRIs), or mineralocorticoid receptor antagonists (MRAs). It is hypothesized that dual RAAS blockade would result in a more complete inhibition of the RAAS cascade. However, large clinical trials on dual RAAS inhibition have shown increased risk of acute kidney injury (AKI) and hyperkalemia without additional benefit on mortality, cardiovascular events, or chronic kidney disease (CKD) progression compared to RAAS inhibitor monotherapy in patients with diabetic kidney disease (DKD). The development of newer, more selective non-steroidal MRAs as cardiorenal protective therapies has created a new opportunity for dual RAAS inhibition. We conducted a systematic review and meta-analysis of the risks of AKI and hyperkalemia with dual RAAS blockade in patients with DKD. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: This is a systematic review and meta-analysis of the randomized controlled trials (RCT) published from 1 January 2006 to 30 May 2022. The study population included adult patients with DKD receiving dual RAAS blockade. A total of 31 RCTs and 33 048 patients were included in the systematic review. Pooled risk ratios (RRs) and 95% confidence intervals (CIs) were calculated using random effects. RESULTS: There were 208 AKI events in 2690 patients on ACEi + ARB versus 170 in 4264 patients with ACEi or ARB monotherapy (pooled RR 1.48, 95% CI: 1.23-1.39). There were 304 hyperkalemia events in 2818 patients on ACEi + ARB versus 208 in 4396 patients with ACEi or ARB monotherapy (pooled RR 1.97, 95% CI: 1.32-2.94). A non-steroidal MRA + ACEi or ARB showed no increase in the risk of AKI (pooled RR 0.97, 95% CI: 0.81-1.16) compared to ACEi or ARB monotherapy but had a 2-fold higher risk of hyperkalemia with 953 events in 7837 patients in dual therapy versus 454 events in 6895 patients in monotherapy (pooled RR 2.05, 95% CI: 1.84-2.28). A steroidal MRA + ACEi or ARB had a 5-fold higher risk of hyperkalemia with 28 events in 245 at risk in dual therapy versus five events in 248 at risk in monotherapy (pooled RR 5.42 95% CI: 2.15-13.67). CONCLUSION: Dual therapy with RAASi is associated with an increased risk of AKI and hyperkalemia compared to RAASi monotherapy. Conversely, dual therapy with RAAS inhibitors and non-steroidal MRAs have no additional risk of AKI but a similar risk of hyperkalemia, which is lower than dual therapy with RAAS inhibitors and steroidal MRAs.

Design and population of the VALOR-CKD study: a multicenter, randomized, double-blind, placebo-controlled trial evaluating the efficacy and safety of veverimer in slowing progression of chronic kidney disease in patients with metabolic acidosis.

BACKGROUND: Whether treating metabolic acidosis slows progression of chronic kidney disease (CKD) has not been established. Veverimer is a novel hydrochloric acid binder that removes acid from the gastrointestinal tract leading to an increase in serum bicarbonate; it is being developed to treat metabolic acidosis with the goal of slowing progression of CKD. METHODS: The VALOR-CKD trial is an international, randomized, multicenter, double-blind, placebo-controlled study designed to evaluate the effect of once-daily veverimer on kidney disease progression in patients with metabolic acidosis and CKD. Eligibility criteria include a serum bicarbonate in the range of 12-20 mmol/L and an estimated glomerular filtration rate (eGFR) of 20-40 mL/min/1.73 m2. The primary outcome is kidney disease progression defined as the development of end-stage kidney disease, a sustained decline in eGFR of >40% from baseline or death due to kidney failure. Key secondary endpoints include effects on physical function. RESULTS: Between December 2018 and December 2021, 1480 participants were randomized. The mean age at baseline was 65.1 years and 42% of the patients were female. The mean baseline eGFR was 29.1 mL/min/1.73 m2 and mean serum bicarbonate was 17.5 mmol/L. The median urine albumin-to-creatinine ratio at screening was 201 mg/g and the median 5-year predicted risk of kidney failure was 32%. Diabetes and hypertension were present in 56% and 98% of participants, respectively. CONCLUSIONS: VALOR-CKD has recruited a large population of people with metabolic acidosis at high risk for CKD progression to determine the effects of veverimer on the risk of progressive loss of kidney function.

Patient views regarding cannabis use in chronic kidney disease and kidney failure: a survey study.

BACKGROUND: Cannabis is frequently used recreationally and medicinally, including for symptom management in patients with kidney disease. METHODS: We elicited the views of Canadian adults with kidney disease regarding their cannabis use. Participants were asked whether they would try cannabis for anxiety, depression, restless legs, itchiness, fatigue, chronic pain, decreased appetite, nausea/vomiting, sleep, cramps and other symptoms. The degree to which respondents considered cannabis for each symptom was assessed with a modified Likert scale ranging from 1 to 5 (1, definitely would not; 5, definitely would). Multilevel multivariable linear regression was used to identify respondent characteristics associated with considering cannabis for symptom control. RESULTS: Of 320 respondents, 290 (90.6%) were from in-person recruitment (27.3% response rate) and 30 (9.4%) responses were from online recruitment. A total of 160/320 respondents (50.2%) had previously used cannabis, including smoking [140 (87.5%)], oils [69 (43.1%)] and edibles [92 (57.5%)]. The most common reasons for previous cannabis use were recreation [84/160 (52.5%)], pain alleviation [63/160 (39.4%)] and sleep enhancement [56/160 (35.0%)]. Only 33.8% of previous cannabis users thought their physicians were aware of their cannabis use. More than 50% of respondents probably would or definitely would try cannabis for symptom control for all 10 symptoms. Characteristics independently associated with interest in trying cannabis for symptom control included symptom type (pain, sleep, restless legs), online respondent {ß = 0.7 [95% confidence interval (CI) 0.1-1.4]} and previous cannabis use [ß = 1.2 (95% CI 0.9-1.5)]. CONCLUSIONS: Many patients with kidney disease use cannabis and there is interest in trying cannabis for symptom control.

Practical Utilization of Prediction Equations in Chronic Kidney Disease.

Chronic kidney disease (CKD) is common and can lead to kidney failure, cardiovascular complications, and early mortality. While nephrologists can provide valuable insights for patients at all stages of CKD, these scarce resources should be targeted at patients with the highest risk of progression and adverse outcomes. Prediction models are tools that can help providers risk stratify patients if they are effectively implemented into the clinical workflow. We believe these equations should demonstrate (1) clinical utility: where they can provide useful information to the physician and patients; and (2) clinical usability: where they are able to be easily integrated into clinical workflow and do not result in unnecessary costs or visits. CKD often remains unrecognized until later stages when a large window of opportunity to delay progression has already passed. Models to determine progression of CKD using thresholds such as a 40% decline in eGFR can provide clinical utility in risk stratifying patients at all stages of CKD, an endpoint that has been recommended by the FDA for the evaluation of drug approvals for disease-modifying therapies. For patients at more advanced stages of CKD with a greater risk of kidney failure, tools such as the kidney failure risk equation can be implemented to help guide most costly decisions, such as referral to multidisciplinary care, commencing dialysis modality education, or planning for vascular access placement surgery. In addition, models focused on determining outcomes following dialysis initiation can help inform shared decision-making between patient and provider to better inform decisions around conservative care. To ensure widespread adoption of these tools, it is important to ensure that they are broadly generalizable to many health settings and easily implemented into existing clinic workflows with minimum disruption.

Dietary potassium liberalization with fruit and vegetables versus potassium restriction in people with chronic kidney disease (DK-Lib CKD): a clinical trial protocol.

BACKGROUND: Potassium regulation in the body is primarily done in the kidney. In addition to this, hyperkalemia, occurs in approximately 10% of individuals with chronic kidney disease (CKD) and is associated with elevated all-cause mortality. Individuals with CKD are often told to restrict dietary potassium (K), however, this recommendation is based on low quality evidence. Reduced quality of life, limited dietary choices and nutritional deficiencies are all potential negative outcomes that may occur when restricting dietary K in CKD patients. There is a need for randomized controlled trials investigating the impact of dietary K modification on serum K concentrations in people with CKD. METHODS: A randomized 2-period crossover design comparing a liberalized K fruit and vegetable diet where participants will be required to consume ~ 3500 mg of dietary K daily, to a standard K restricted diet where participants will be required to consume < 2000 mg of dietary K daily. All participants will begin on a liberalized K run-in period for 2 weeks where they will receive fruit and vegetables home deliveries and for safety will have clinical chemistry, including serum potassium measurements taken after 1 week. Participants will then be randomized into either liberalized K or standard K diet for six weeks and then crossover to the other intervention for another 6 weeks after a 2-week washout period. DISCUSSION: 30 male and female CKD outpatients, ≥ 18 years of age, who have an estimated glomerular filtration rate (eGFR) between 15 and 45 ml/min/1.73m2 and serum K between 4.5 and 5.5 mEq/L. This design would have greater than 80% power to detect a difference of 0.35 mEq/L serum K between groups. Anthropometric measurements, clinical chemistry, dietary recalls, physical function assessments, as well as a quality of life assessments will also be measured in this trial. These findings will provide high quality evidence for, or against, recommendations for dietary K restriction in individuals living with CKD. The removal of K restriction could provide individuals living with CKD more dietary choice leading to improved dietary status and quality of life. TRIAL REGISTRATION: This trial has received approval from the University of Manitoba Research Ethics board (HS25191 (B2021:104)).

Advancing Exercise Science for Better Health Outcomes Across the Spectrum of Chronic Kidney Disease.

Despite over 30 years of evidence for improvements in physical function, physical fitness, and health-related quality of life with exercise training in individuals with chronic kidney disease, access to dedicated exercise training programs remains outside the realm of standard of care for most kidney care programs. In this review, we explore possible reasons for this by comparing approaches in other chronic diseases where exercise rehabilitation has become the standard of care, identifying enablers and factors that need to be addressed for continued growth in this area, and discussing knowledge gaps for future research. For exercise rehabilitation to be relevant to all stakeholders and become a sustainable component of kidney care, a focus on the effect of exercise on clinically relevant outcomes that are prioritized by individuals living with kidney disease, use of evidence-based implementation strategies for diverse settings and populations, and approaching exercise as a medical therapy are required.

Calculated versus measured albumin-creatinine ratio to predict kidney failure and death in people with chronic kidney disease.

Albumin-to-creatinine ratio (ACR), the preferred method to quantify proteinuria, can be calculated from urine dipstick protein or protein-to-creatinine ratio (PCR). The performance of calculated vs. measured ACR in predicting kidney failure and death without kidney failure in people with chronic kidney disease (CKD) is unknown. Here, we used population-based data from Alberta, Canada, to identify adults with incident moderate-severe CKD (sustained for more than 90 days) from 2008-04-01 to 2017-03-31, who had same-day measures of ACR and urine dipstick (ACR-dipstick cohort) or PCR (ACR-PCR cohort) in the two years before cohort entry. We followed participants until 2019-03-31 and trained competing risk models of kidney failure and death without kidney failure including age, sex, estimated glomerular filtration rate, diabetes, cardiovascular disease, and either measured or calculated ACR. Model performance was tested in cohorts created using the same algorithm in Manitoba, Canada. The ACR-dipstick and ACR-PCR cohorts included 18,731 and 4,542 people (training cohorts) and 821 and 1,831 people (testing cohorts), respectively. In internal and external testing, there was closer agreement between predictions based on measured vs. PCR-calculated ACR than between those based on measured vs. dipstick-calculated ACR. The dipstick-calculated ACR had higher Brier scores than measured ACR from year three for both outcomes, indicating worsening calibration. Models including measured or calculated ACR had similar discrimination: year one-to-five area under the receiver operating characteristic curve of 83-89% for kidney failure and 69-75% for mortality. Thus, if confirmed in different ethnic groups, calculated ACR can be used for risk predictions when the measured ACR is not available. PCR-calculated ACR may have superior performance to dipstick-calculated ACR.

The Comparative Outcomes of Radical Prostatectomy versus Radiotherapy for Nonmetastatic Prostate Cancer: A Longitudinal, Population-Based Analysis.

PURPOSE: The comparative effectiveness of radical prostatectomy (RP) versus radiation therapy (RT) for prostate cancer remains a largely debated topic. Utilizing a provincial population-based linked data set from an equal-access, universal health care system, we sought to compare outcomes among patients treated with either radiation or prostatectomy for nonmetastatic prostate cancer. MATERIALS AND METHODS: We performed a retrospective cohort study by linking several administrative data sets to identify patients who were diagnosed with prostate cancer between 2004 and 2016 in Manitoba, Canada and who were subsequently treated with either RP or RT. Cox proportional hazard models with inverse probability of treatment weighting were used to compare rates of all-cause mortality, as well as prostate cancer specific mortality (PCSM) between patients who underwent RP vs RT. RESULTS: During the study period, 2,540 patients underwent RP and 1,895 underwent RT for prostate cancer. Unadjusted overall survival was higher for RP vs RT (5-year overall survival 95.52% for RP compared with 84.55% for RT, p <0.0001). In inverse probability of treatment weighting-adjusted Cox regression analysis, compared to patients in the RP groups, patients in the RT group had an increased rate of all-cause mortality (HR 1.93, 95% CI 1.65-2.26, p <0.0001), and PCSM (HR 3.98, 95% CI 2.89-5.49; p <0.0001). CONCLUSIONS: RT was associated with higher all-cause mortality and PCSM rates compared with RP. These findings highlight the importance of comparative effectiveness research to identify treatment disparities and warrant further investigation.

Role of artificial intelligence in the diagnosis and management of kidney disease: applications to chronic kidney disease and acute kidney injury.

PURPOSE OF REVIEW: Chronic kidney disease (CKD) and acute kidney injury (AKI) are global public health problems associated with a significant burden of morbidity, healthcare resource use, and all-cause mortality. This review explores recently published studies that take a machine learning approach to the diagnosis, management, and prognostication in patients with AKI or CKD. RECENT FINDINGS: The release of novel therapeutics for CKD has highlighted the importance of accurately identifying patients at the highest risk of progression. Many models have been constructed with reasonable predictive accuracy but have not been extensively externally validated and peer reviewed. Similarly, machine learning models have been developed for prediction of AKI and have found sufficient accuracy. There are issues to implementing these models, however, with conflicting results with respect to the relationship between prediction of an AKI outcome and improvements in the occurrence of other adverse events, and in some circumstances potential harm. SUMMARY: Artificial intelligence models can help guide management of CKD and AKI, but it is important to ensure that they are broadly applicable and generalizable to various settings and associated with improved clinical decision-making and outcomes.