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

Best practice for the selection, design and implementation of UK Kidney Association guidelines: a modified Delphi consensus approach

BACKGROUND

Despite research into how to effectively implement evidence-based recommendations into clinical practice, a lack of standardisation in the commissioning and development of clinical practice guidelines can lead to inconsistencies and gaps in implementation. This research aimed to ascertain how topics in kidney care worthy of guideline development within the UK should be chosen, prioritised, designed and implemented.

METHODS

Following a modified Delphi methodology, a multi-disciplinary panel of experts in kidney healthcare from across the UK developed 35 statements on the issues surrounding the selection, development and implementation of nephrology guidelines. Consensus with these statements was determined by agreement using an online survey; the consensus threshold was defined as 75% agreement.

RESULTS

419 responses were received. Of the 364 healthcare practitioners (HCPs), the majority had over 20 years of experience in their role (n=123) and most respondents were nephrologists (n=95). Of the 55 non-clinical respondents, the majority were people with kidney disease (n=41) and the rest were their carers or family. Participants were from across England, Northern Ireland, Scotland and Wales. Consensus between HCPs was achieved in 32/35 statements, with 28 statements reaching ≥90% agreement. Consensus between patients and patient representatives was achieved across all 20 statements, with 13/20 reaching ≥90% agreement.

CONCLUSIONS

The current results have provided the basis for six recommendations to improve the selection, design and implementation of guidelines. Actioning these recommendations will help improve the accessibility of, and engagement with, clinical guidelines, contributing to the continuing development of best practice in UK kidney care.

Detecting and managing the patient with chronic kidney disease in primary care: A review of the latest guidelines

Chronic kidney disease (CKD) is a major global health problem, affecting about 9.5% of the population and 850 million people worldwide. In primary care, most CKD is caused by diabetes and/or hypertension, but a substantial proportion of cases may have alternative causes. During the early stages, CKD is asymptomatic, and many people are unaware that they are living with the disease. Despite the lack of symptoms, CKD is associated with elevated risks of cardiovascular disease, progressive kidney disease, kidney failure and premature mortality. Risk reduction strategies are effective and cost-effective but require early diagnosis through testing of the estimated glomerular filtration rate and albuminuria in high-risk populations. Once diagnosed, the treatment of CKD centres around lifestyle interventions, blood pressure and glycaemic control, and preventative treatments for cardiovascular disease and kidney disease progression. Most patients with CKD should be managed with statins, renin-angiotensin-aldosterone system inhibitors and sodium-glucose cotransporter-2 inhibitors. Additional treatment options to reduce cardiorenal risk are available in patients with diabetes, including glucagon-like peptide-1 receptor agonists and non-steroidal mineralocorticoid receptor antagonists. The Kidney Failure Risk Equation is a new tool that can support the identification of patients at high risk of progressive kidney disease and kidney failure and can be used to guide referrals to nephrology. This review summarizes the latest guidance relevant to managing adults with, or at risk of, CKD and provides practical advice for managing patients with CKD in primary care.

Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease: multinational, longitudinal, population based, cohort study

OBJECTIVE

To train and test a super learner strategy for risk prediction of kidney failure and mortality in people with incident moderate to severe chronic kidney disease (stage G3b to G4).

DESIGN

Multinational, longitudinal, population based, cohort study.

SETTINGS

Linked population health data from Canada (training and temporal testing), and Denmark and Scotland (geographical testing).

PARTICIPANTS

People with newly recorded chronic kidney disease at stage G3b-G4, estimated glomerular filtration rate (eGFR) 15-44 mL/min/1.73 m2.

MODELLING

The super learner algorithm selected the best performing regression models or machine learning algorithms (learners) based on their ability to predict kidney failure and mortality with minimised cross-validated prediction error (Brier score, the lower the better). Prespecified learners included age, sex, eGFR, albuminuria, with or without diabetes, and cardiovascular disease. The index of prediction accuracy, a measure of calibration and discrimination calculated from the Brier score (the higher the better) was used to compare KDpredict with the benchmark, kidney failure risk equation, which does not account for the competing risk of death, and to evaluate the performance of KDpredict mortality models.

RESULTS

67 942 Canadians, 17 528 Danish, and 7740 Scottish residents with chronic kidney disease at stage G3b to G4 were included (median age 77-80 years; median eGFR 39 mL/min/1.73 m2). Median follow-up times were five to six years in all cohorts. Rates were 0.8-1.1 per 100 person years for kidney failure and 10-12 per 100 person years for death. KDpredict was more accurate than kidney failure risk equation in prediction of kidney failure risk: five year index of prediction accuracy 27.8% (95% confidence interval 25.2% to 30.6%) versus 18.1% (15.7% to 20.4%) in Denmark and 30.5% (27.8% to 33.5%) versus 14.2% (12.0% to 16.5%) in Scotland. Predictions from kidney failure risk equation and KDpredict differed substantially, potentially leading to diverging treatment decisions. An 80-year-old man with an eGFR of 30 mL/min/1.73 m2 and an albumin-to-creatinine ratio of 100 mg/g (11 mg/mmol) would receive a five year kidney failure risk prediction of 10% from kidney failure risk equation (above the current nephrology referral threshold of 5%). The same man would receive five year risk predictions of 2% for kidney failure and 57% for mortality from KDpredict. Individual risk predictions from KDpredict with four or six variables were accurate for both outcomes. The KDpredict models retrained using older data provided accurate predictions when tested in temporally distinct, more recent data.

CONCLUSIONS

KDpredict could be incorporated into electronic medical records or accessed online to accurately predict the risks of kidney failure and death in people with moderate to severe CKD. The KDpredict learning strategy is designed to be adapted to local needs and regularly revised over time to account for changes in the underlying health system and care processes.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Recent evaluation by nephrologists is associated with decreased incidence of tunneled dialysis catheter being used at the time of first arteriovenous access creation

OBJECTIVE

Late primary care provider (PCP) or nephrologist evaluation of patients with progressive kidney disease may be associated with increased morbidity and mortality. Among patients undergoing initial arteriovenous (AV) access creation, we aimed to study the relationship of recent PCP and nephrologist evaluations with perioperative morbidity and mortality.

METHODS

We performed a retrospective review of patients from 2014 to 2022 who underwent initial AV access creation at an urban, safety-net hospital. Univariable and multivariable analyses identified associations of PCP and nephrologist evaluations <1 year and <3 months before surgery, respectively, with hemodialysis initiation via tunneled dialysis catheters (TDCs), 90-day readmission, and 90-day mortality.

RESULTS

Among 558 patients receiving initial AV access, mean age was 59.7 ± 14 years, 59% were female gender, and 60.6% were Black race. Recent PCP and nephrology evaluations occurred in 386 (69%) and 362 (65%) patients, respectively. On multivariable analysis, unemployed and uninsured statuses were associated with decreased likelihood of PCP evaluation (unemployment: odds ratio [OR], 0.51; 95% confidence interval [CI], 0.34-0.77; uninsured status: OR, 0.05; 95% CI, 0.01-0.45) and nephrologist evaluation (unemployment: OR, 0.63; 95% CI, 0.43-0.91; uninsured status: OR, 0.22; 95% CI, 0.06-0.83) (all P < .05). Social support was associated with increased likelihood of PCP evaluation (OR, 1.81; 95% CI, 1.07-3.08) (all P < .05). Hemodialysis was initiated with TDCs in 304 patients (55%). Older age (OR, 0.98; 95% CI, 0.96-0.99), obesity (OR, 0.38; 95% CI, 0.25-0.58), and nephrologist evaluation (OR, 0.12; 95% CI, 0.08-0.19) were independently associated with decreased hemodialysis initiation with TDCs in patients receiving an initial AV access (all P < .05). Ninety-day readmission occurred in 270 cases (48%). Cirrhosis (OR, 2.5; 95% CI, 1.03-6.03; P = .04), coronary artery disease (OR, 2.31; 95% CI, 1.5-3.57), prosthetic AV access (OR, 1.84; 95% CI, 1.04-3.26), and impaired ambulation (OR, 1.75; 95% CI, 1.15-2.66) were independently associated with increased readmission (all P < .05). Older age (OR, 0.98; 95% CI, 0.97-0.99), prior TDC (OR, 0.65; 95% CI, 0.45-0.94), and unemployment (OR, 0.58; 95% CI, 0.39-0.86) were associated with decreased readmission (all P < .05). Ninety-day mortality occurred in 1.6% of patients. Neither PCP nor nephrologist evaluation was associated with readmission or mortality.

CONCLUSIONS

Recent nephrology evaluation was associated with reduced hemodialysis initiation with TDCs among patients undergoing initial AV access creation. Unemployed and uninsured statuses posed barriers to accessing nephrology care.

Retaining Race in Chronic Kidney Disease Diagnosis and Treatment

The best overall measure of kidney function is glomerular filtration rate (GFR) as commonly estimated from serum creatinine concentrations (eGFRcr) using formulas that correct for the higher average creatinine concentrations in Blacks. After two decades of use, these formulas have come under scrutiny for estimating GFR differently in Blacks and non-Blacks. Discussions of whether to include race (Black vs. non-Black) in the calculation of eGFRcr fail to acknowledge that the original race-based eGFRcr provided the same CKD treatment recommendations for Blacks and non-Blacks based on directly (exogenously) measured GFR. Nevertheless, the National Kidney Foundation and the American Society of Nephrology Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease removed race in CKD treatment guidelines and pushed for the immediate adoption of a race-free eGFRcr formula by physicians and clinical laboratories. This formula is projected to negate CKD in 5.51 million White and other non-Black adults and reclassify CKD to less severe stages in another 4.59 million non-Blacks, in order to expand treatment eligibility to 434,000 Blacks not previously diagnosed and to 584,000 Blacks previously diagnosed with less severe CKD. This review examines: 1) the validity of the arguments for removing the original race correction, and 2) the performance of the proposed replacement formula. Excluding race in the derivation of eGFRcr changed the statistical bias from +3.7 to -3.6 ml/min/1.73m2 in Blacks and from +0.5 to +3.9 in non-Blacks, i.e., promoting CKD diagnosis in Blacks at the cost of restricting diagnosis in non-Blacks. By doing so, the revised eGFRcr greatly exaggerates the purported racial disparity in CKD burden. Claims that the revised formulas identify heretofore undiagnosed CKD in Blacks are not supported when studies that used kidney failure replacement therapy and mortality are interpreted as proxies for baseline CKD. Alternatively, a race-stratified eGFRcr (i.e., separate equations for Blacks and non-Blacks) would provide the least biased eGFRcr for both Blacks and non-Blacks and the best medical treatment for all patients.