#NephJC Chat
Tuesday, May, 7th, 2024 at 9 pm Eastern (AEST = May 8th, 11am)
Wednesday, May 8th, 2024, at 9 pm Indian Standard by Time and 3:30 pm GMT (AEST = May 9th, 2am)
Kidney Int.2024 Apr;105(4S):S117-S314. doi: 10.1016/j.kint.2023.10.018.
KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease
Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group
PMID: 38490803
KDIGO CKD webpage
Introduction
More than a decade has passed since the last Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease (CKD) guidelines (Stevens et al, Ann Int Med 2013) were released, and certainly, a lot has changed since then! Be it getting more robust evidence from wider population based studies, to etio-pathological research, to diagnostics and therapeutics (Flozins, MRAs, GLP1RAs, DOACs—yes, you will find all of these here!), much has changed the way we think, and practice. Through a two-part summary and chats NephJC plans to cover the length and breadth of this document. Let’s hope we are wiser than before for tackling a disease that’s now an unquestionable global public priority, backed by studies that bring to us some astonishing numbers.
If we accept the KDIGO CKD definitions, a staggering 850 million (Jager et al, KI 2019) are estimated to have kidney disease, giving a prevalence of ~10%, roughly double the number of people who live with diabetes (422 million), and 20 times more than the prevalence of cancer (42 million) or AIDS/HIV (36.7 million) worldwide. CKD and its impact on CVD were associated with 2.6 million deaths in 2017, rising from 19th to 11th in the leading causes of death between 1990 and 2019. What’s more on the 10-year horizon (abstract of IMPACT CKD study, PDF at link)? A projected rise in CKD prevalence to 16.5%, a 25% rise in advanced stage CKD to 58.9%, a surge in dialysis requirements by 75%, and an enormous impact on the economy and carbon footprint. However, despite the growing burden of CKD, population screening and specialized initiatives are still a matter of ongoing debate due to the complex sociopolitical and resource context. Will the new guidelines help us navigate the landscape any better?
The 2024 update reflects advances in GFR evaluation, risk prediction, and innovative medications that have improved CKD prognosis. The guideline includes recommendations for adult and pediatric populations, excluding dialysis and kidney transplants. Chapters cover CKD evaluation, risk assessment, treatment to slow progression and manage consequences, medication stewardship, and optimum CKD care models. Compared to KDIGO 2012 CKD (Levin and Stevens, Kidney Int 2014) guideline, many of the graded recommendations have been converted to practice points, highlighting the lack of enough evidence to support a graded recommendation. In this current guideline, there are a total of 2 recommendations each of Grade 1D, 2A, and 2B; 3 recommendations of Grade 2D, 4 recommendations of Grade 1A and 1C; 5 recommendations of Grade 2C and 6 recommendations of Grade 1B.
The current guideline encourages the community to include people across the lifecycle and consider CKD etiology, sex, and gender in all research.
The goal of the recommendations, suggestions, and practice points is to guide physicians in individualizing CKD diagnosis and treatment, while providing the best care with the available evidence. However, let’s keep a critical eye on the evidence used for these since the underlying justifications can vary from weak to very strong. Please take a look on how KDIGO defines 2024 recommendations:
Without further ado, let’s dive into the first 2 chapters about evaluation and risk assessment of CKD.
Chapter 1: Evaluation of CKD
Chapter 1 focuses on the following broad themes:
Detection and evaluation of CKD: essentially draws from the ‘CGA’ concept of ‘cause, GFR and albuminuria’ to define and stage CKD, and brings out practice points regarding who should be screened, what tests to be used, and how to evaluate chronicity and cause of CKD.
Evaluation of GFR: using serum creatinine as the first step followed by a validated GFR estimating equation, indications for use of cystatin-C based estimation, merits and fallacies of creatinine versus cystatin-C, guidance to laboratories and a note on pediatric considerations.
Evaluation of albuminuria: preferable urine sample to use, preferable method of testing, alternatives, understanding variation in albuminuria, guidance to laboratories and a note on pediatric considerations.
Point-of-care testing: for serum creatinine and urine albumin.
What is the best way to detect CKD?
Initial testing should include blood and urine tests to check urine albumin and GFR. KDIGO breaks down suggested ways to use GFR and ACR throughout CKD care stages.
Practice point 1.1.1.1: Test people at risk for and with chronic kidney disease (CKD) using both urine albumin measurement and assessment of glomerular filtration rate (GFR).
Emphasis is given to recognize people at high risk for CKD to prompt early testing. This infographic summarizes some of the risk factors for CKD:
However, testing should be repeated in people with low-risk factors for CKD. For example, hematuria should be re-tested, and, if persistent, needs proper investigation.
Practice point 1.1.1.2: Following incidental detection of elevated urinary albumin-to-creatinine ratio (ACR), hematuria, or low estimated GFR (eGFR), repeat tests to confirm the presence of CKD.
A special consideration needs to be given to the pediatric population. Due to decreased nephron number, people born pre-term and/or small for gestational age, are at increased risk for CKD. This risk is further increased if additional insults, like neonatal AKI and childhood obesity, are present.
CKD can progress without symptoms, so systematic testing is recommended by KDIGO to detect it early. This helps in timely treatment (since we do have effective options now), ultimately reducing the rates of CVD and CKD progression.
What are the ‘best’ methods for staging CKD?
KDIGO places high value on using eGFR based on 2 biomarkers, due to its individual limitations. As part of the evidence presented, based on the Chronic Kidney Disease Prognosis Consortium (CKD-PC) collaboration data (see Grams et al, JAMA 2023 and previous NephJC discussion on GFR equations), the combined eGFRcr-cys is considered superior to eGFRcr in distinguishing GFR risk stages. Thus, KDIGO recommends adding cystatin-C to creatinine to estimate GFR if it is available, even in some common clinical scenarios. They acknowledge cystatin-C does come with an extra cost, and it might not be accessible in every setting, but accurate CKD diagnosis outweighs this disadvantage. This comes with updates to CKD ‘heat-maps’, the color-coded depiction of associations between CKD staging and risk of pre-defined outcomes. First introduced in the KDIGO CKD guidelines in 2012 based on collaborative work by Levey et al (KI 2011), the inaugural study cohorts studied here were later continued as the CKD-PC. These updated heat maps (figure below) include observations from >27 million (!) participants for 10 adverse outcomes (6 cardio-vascular, 2 kidney-related, and 2 general outcomes). Most importantly, the raging controversy on whether to classify stage G3a A1 as being CKD at all, particularly in older adults, appears to be answered by the new findings. The investigators reported that the replacement of eGFRcr with eGFRcr-cys in the heat map led to several changes in the risk distributions. Most notably for the new G3a A1 group, which moves to higher risk for all 10 outcomes and is no longer labeled green for any of the complications.
The guidelines currently do not view elderly adults as a different group for eGFR interpretation, and define them on par with the younger ones. This is majorly attributable to the fact that elderly individuals with numerically lower eGFRs were still observed to have elevated risks for bad outcomes, and hence exercising caution may be prudent, leaving the contentious issues of age and eGFR unresolved for the present. An interesting approach also may be having an age-calibrated definition of CKD, considering the longer risk horizons in young adults compared to older adults (Delanaye et al Clin Biochem Rev 2016).
Figures 5 & 6 - Associations of chronic kidney disease (CKD) staging by estimated glomerular filtration rate by creatinine and cystatin C (eGFRcr-cys) and albumin-to-creatinine ratio (ACR) categories and risks for 10 common complications by age in multivariable-adjusted analyses from KDIGO CKD Work Group, KI, 2024.
Further explorations using spline analysis showed J-shaped association with eGFRcr (risk increased with eGFR values over 105 ml/min/1.73 m2, possibly related to inaccuracies of conventional creatinine based equations at higher eGFR ranges). In contrast, eGFRcr-cys demonstrated more linear associations with each of the 10 complications throughout its distribution.
However, we must point out certain limitations. eGFRcr was estimated using the 2021 CKD-EPI equation, which underestimates CKD prevalence in white populations. This equation included cohorts from Europe, Asia, US, and Australia, but the white population was grouped together without taking into consideration individual characteristics of each particular population. The result? The 2021 CKD-EPI equation performed worse for the European population than the 2009 CKD-EPI equation (Gansevoort et al Nephrol Dial Transplant 2023). This certainly limits the generalizability of the findings shown. Moreover, we should take the data from eGFRcr-cys with a grain of salt, because the sample size of the sub-analyses is much smaller (n = 720,736 vs 27,503,140). This is definitely something we must pay attention to in the next guidelines as more data with cystatin-C is gathered.
How should chronicity be evaluated?
Carrying on the CKD definition stated in KDIGO 2012 CKD guidelines, they offer different ways to prove chronicity. Chronicity, which is defined as the condition continuing for a minimum of three months, may be established by the following:
evaluation of prior GFR estimations and measurements;
analysis of prior urine microscopic examinations and proteinuria or albuminuria measurements;
imaging finds that involve renal pathological states such as fibrosis and atrophy; reduced kidney size and cortical thickness.
medical background, with specific attention to documented medical conditions;
performance of further measurements is permissible even beyond the three-month delay.
CKD can’t be assumed by a single abnormal level for eGFR and ACR since these results could be secondary to an acute injury. However, if there is a high suspicion for CKD (due to the presence of risk factors), the KDIGO panel wants you to consider initiating CKD treatments early on versus waiting to confirm chronicity.
A special consideration about the pediatric population is that you don’t need to wait 3 months to confirm CKD diagnosis in newborns who clearly have kidney disease (i.e. severe congenital malformations of the kidney and urinary tract).
How to evaluate and determine underlying cause of CKD?
Up to 25% of all current CKD registries (or study groups) have listed "unknown etiology" as an underlying cause of CKD (Robert et al Kidney Int Rep 2023.) This has sparked new interest in helping doctors and people with CKD, and also figuring out its specific etiologies. It is also imperative to identify the cause of CKD in order to apply targeted therapies (if indicated) and slow down CKD progression. To evaluate the cause of CKD, the guideline proposes a comprehensive approach, as shown in the following figure:
Usually, identification of the cause can be achieved through medical history, examination, and specific markers for kidney damage. In the case additional testing is required, Table 6 shows a suggested guide to facilitate selection:
As KDIGO places a high value on identifying CKD causes, this guideline offers a suggestion about kidney biopsy that was not mentioned in the 2012 guideline.
Despite bleeding and non-diagnostic risk, a kidney biopsy is a safe procedure and should be performed if it will help clarify a diagnosis, prognosis, and/ or treatment options. Take into account that this suggestion is based on very low evidence (Supplementary Table S4).
Among one of the new emerging diagnostic tools is genetic testing. KDIGO Controversies Conference suggests genetic testing in these particular scenarios can be informative:
This has become valuable since there are actionable genes that can change CKD management (Figure 9). It is also important to have a multidisciplinary workforce (genetic counseling and medical genetics) available. In the near future, genetic screening may actually be done at the initiation of CKD evaluation and management. In the meantime, focus should also be given to determining its appropriate use and increase accessibility.
Despite newer, more precise tools, the unfortunate truth is that not all of them are available worldwide. Evaluation of CKD causes should be individualized according to the clinical context.
How should we evaluate GFR?
This section describes an overall approach to evaluating GFR. This new guideline recommends using more eGFRcr-cys validated equations, given their improved accuracy versus previous equations that only included creatinine. The guidelines also attempt to clarify the value and limitations of both creatinine and cystatin C. Table 7 describes different tests available for the evaluation of GFR.
As to how to choose? Here is a proposed algorithm:
Figure 11: Approach to glomerular filtration rate (GFR) evaluation using initial and supportive tests from KDIGO CKD Work Group, KI, 2024.
As you can notice, KDIGO still recommends the use of serum creatinine as the initial test since it is widely available. Interestingly, compared to KDIGO 2012 the recommendation is downgraded from 1A to 1C, due to its limitations. Some of these are due to how serum creatinine becomes unreliable in certain scenarios like: muscle wasting/loss or decreased tubular secretion as a medication effect. Also, it is important to be aware of substances that can interfere with serum creatinine assays.
As mentioned before, cystatin C may not be readily available and it requires additional resources and costs, thus it is important to know when it is most valuable and appropriate to measure. This table breaks down the indications to use cystatin C:
Numerous studies have shown that 25%-30% of individuals have eGFRcr-eGFRcys discrepancies of 15 ml/min per 1.73 m2or >20% when compared with estimation based solely upon creatinine. In cases where eGFRcr and eGFRcys are discordant, it is recommended to assess cystatin C serially, alongside creatinine, in contexts where GFR impacts clinical choices. It is also useful to examine mGFR for drugs with limited therapeutic window, and severe toxicity, or to guide essential treatment decisions.
How should we deal with gender and GFR?
As we learn more about how to figure out GFR using cystatin C versus creatinine or both, there are numerous known effects of these changes that we all need to understand, both in terms of the direction and size of the effects. There are problems with figuring out the best way to measure GFR in transgender, gender-diverse, or nonbinary people whose gender identity is different from the sex they were given at birth and who may or may not be taking hormone-affirming or hormone-blocking treatments for puberty. It's important to look at the whole person, including their muscle mass, sex hormones, and gender identity, to figure out the best way to compute GFR. In the same way, gender-affirming hormone treatment may change cystatin C-based formulae, though perhaps less so than for creatinine. When knowing the precise GFR matters for decisions concerning treatment (like how much of a cancer drug to give, who can be a kidney donor, etc.), one should use measured GFR, rather than rely on estimated GFR.
What are the recommendations to evaluate for albuminuria?
KDIGO still recommends focusing on albuminuria instead of proteinuria, as was initially recommended in the 2012 CKD guidelines. However, this time gives more priority to urine albumin as the initial test: urine ACR or reagent strip urinalysis for albumin and ACR with automated reading using a first-morning void midstream sample. The guidelines also recommend confirming an ACR > 30mg/g on a random urine sample with a first-morning void midstream sample. It is key to be aware of the factors that can alter an ACR or PCR result. Table 16 provides a summary of these factors:
KDIGO continues to recommend using eGFR rather than serum filtration markers alone. Now it is graded as a 1D recommendation, whereas in 2012 it was a 1B recommendation. This demotion is most likely due to the ongoing emergence of proposed validated estimating GFR equations particular to populations. Even though new validated eGFR equations have been proposed, at the end of the day, it is still an estimation and an imperfect way to assess true GFR.
As a last suggestion in Chapter 1, KDIGO recommends the use of POCT when laboratories are limited. This is based on the fact that the majority of the world’s population with CKD is in low- and middle-income countries where there are serious disparities in access to laboratory diagnostic services. As per a global survey by ISN, only 1 in 4 surveyed countries had facilities for routine measurements of SCr or proteinuria (Bello et al, JAMA 2017). The POCT for serum creatinine should be followed by estimation of GFR through validated equations. Similarly, POCT for urine albumin, should preferably also have the capacity to analyze creatinine and generate ACR values. Take-away point here? While ordering a POCT device for our own practice, we will follow what the guideline says about acceptable device performance- choose a device that gives a positive result in 85% of people with significant albuminuria (Sensitivity lesser than this is clearly not desirable!).
Summary of Chapter 1 Recommendations
Summary of Chapter 1 Practice points
Chapter 2: Risk assessment in people with CKD
Chapter 2 highlights clinical monitoring for progression of CKD based upon GFR and ACR categories and deals with the contentious issues of risk equations for predicting kidney failure risk and cardiovascular risk.
CKD staging helps inform providers and patients about prognosis, timing of interventions, and assessment of treatment effect. In order to update staging, KDIGO recommends assessing albuminuria and GFR at least annually. However, this surveillance should be more frequent for patients at higher risk for CKD progression or if it is needed for therapeutic decisions. The albuminuria and GFR grid depicts the risk of advancement based on color intensity (green, yellow, orange, red, and deep red). The numbers in the boxes indicate the frequency of monitoring (per year).
There are other instances in which further evaluation is warranted: change in eGFR > 20% on a subsequent test; GFR reduction of >30% after initiating hemodynamically active therapies; and doubling of the ACR on a subsequent test. Increases in albuminuria and proteinuria in pediatric populations are linked with a higher risk of disease progression, similar to adults. The following infographic summarizes studies that highlight the value of measuring albuminuria:
How do we predict risks in people with CKD?
In order to provide a more individualized approach, there is high value in providing individual risk predictions, being the first 1A graded recommendation of this guideline. KDIGO highlights 3 validated models: The Kidney Failure Risk Equation (KFRE) (Tangri et al JAMA 2011), the Veterans Affairs model, and the Z6 Score model (Zacharias et al Am J Kidney Dis 2022).
KDIGO proposes to integrate these risk assessment tools to determine the timing of multidisciplinary care. For example: a 5-year kidney failure risk of 3%-5% can be used as a cutoff for a nephrology referral. Moreover, a 2-year kidney failure risk of >10% can be used to start adding interdisciplinary care: pharmacist, renal dietitian; whereas more than 40% can be used to start education about dialysis modalities and referral for renal transplantation. Since the publication of these guidelines, another risk prediction model has been published (Liu et al BMJ 2024; KDPredict.com) which also incorporates death along with kidney failure in the forecasting. This new prediction model has opened the door to be more critical about risk assessment tools. KFRE itself has been available for more than a decade and its accuracy has been explored outside the Canadian population (Tangri et al JAMA 2016). Likewise, KDIGO encourages the use of disease-specific risk prediction models, including the Mayo Clinic Classification tool (Irazabal et al JASN 2015) and PROPKD Score (Cornec-Le Gall et al JASN 2016) for ADPKD, and the International Risk Prediction Tool (Barbour et al JAMA Intern Med 2019; NephJC summary) for IgA nephropathy.
How to adequately predict cardiovascular risk in people with CKD?
CKD patients are disproportionately affected by cardiovascular morbidity and mortality, and risk prediction techniques designed for non-CKD individuals may underestimate the risk of atherosclerotic CVD or heart failure in CKD populations. For these reasons, it is recommended to use externally validated models that include CKD populations or that incorporate eGFR and albuminuria. For example, for CV risk prediction, new models have been developed: QRISK3 (Hippisley-Cox et al BMJ 2017), ckdpc.org (Chronic Kidney Disease Prognosis Consortium KI 2018) and the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) (Khan et al Circulation 2024).
Finally, to guide discussions about goals of care, it is recommended to use an all-mortality risk prediction tool. For the CKD population, there have been 2 models developed: CKD-PC (Chronic Kidney Disease Prognosis Consortium KI 2018) and a 5-year mortality model in the Cardiovascular Health Study (Khan et al Circulation 2024).
Summary of Chapter 2 Recommendations and Practice Points
Chapter 6: Research Recommendations
There has been a huge increase in publications about kidney diseases over the last 30 years. Even though people with CKD are now included in prospective RCTs, people with lower GFR are still not well represented. Before the KDIGO 2012 CKD guideline, having a low eGFR meant that a person could not participate in almost any big cardiovascular or blood pressure study. Because of this, we had a lot of literature that was based on opinions. That is starting to change. In the five years ending in December 2022, the number of papers about CKD that are either an RCT, meta-analysis, or systematic review doubled, from 3.3% to 6.5% of all articles released. This is still a small number. Recently, eight years' worth of large international interventional studies have been completed. These studies have either been aimed at people with CKD and other conditions, mostly diabetes or CVD, or at people with CKD as defined by eGFR and ACR criteria. Some examples are: Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation [CREDENCE] (Perkovic et al NEJM 2019), DAPA-CKD (Heerspink et al NEJM 2020), EMPA-KIDNEY (Herrington et al NEJM 2023), FIGARO-DKD, (Pitt et al NEJM 2021) and FIDELIO-DKD (Bakris et al NEJM 2020).
Interventional studies that focus on specific pathways and diseases are also growing, but they are restricted in scope because some cases are particularly rare (like IgAN, membranous nephropathy, systemic lupus erythematosus, etc.). The amount of data is still not complete enough to fully explain the best ways to make diagnoses, make decisions, and provide care. Also, some treatments that show potential have not been tried enough in people with CKD who meet certain conditions, such as those who don't have diabetes, children, women, pregnancy, PKD, frail, elderly, etc., and who live in low-income or low-middle-income countries.
To start this part on research suggestions, here are some general rules that KDIGO suggests as a guide for future studies.
To these we think that females should be added as one of the groups to promote recruitment. Females are underrepresented, only estimated to be 39% of participants in nephrology trials (Lodhi et al KI 2024). By looking at this guide at a glance, it is clear that CKD heterogeneity is a challenge when trying to come the best variables for research design and KDIGO is attempting to include in the mix most of what ‘we know’ is important (inclusion of CKD cause, ACR, advanced CKD stages). Despite the need of new GFR formulas and risk assessment tools, its development contributes to the challenge comes with more generalizable tools while still adjusting to the individual characteristics that different populations present.
Having these guiding principles in mind, KDIGO suggests the following research recommendations for the evaluation of CKD (Chapter 1) and risk assessment in patients of CKD (Chapter 2).
Conclusion
As the authors say, this guideline should be viewed as a ‘dynamic, evolving resource rather than a static document’, imploring us to reflect on what’s best suited for the CKD patient in our clinic and act on it. KDIGO 2024 may have pragmatic, beneficial insights. However, the emergence of many practice points uncovers the lack of strong research when it comes to evaluation and risk assessment of CKD. Hopefully, more data will be available with the gradual application of the GFR equations, cystatin-C inclusion and use of risk prediction tools. Will need to see if a decade is enough to have good evidence behind future recommendations.
Summary prepared by
Stephanie Torres Rodríguez, MD
Assistant Professor
UT Southwestern, Dallas, TX
Medhavi Gautam, MD
Associate Professor
King George’s Medical University, Lucknow, India
Visual Abstracts and Infographics created by Cristina Popa, Medhavi Gautam, Anvitha Rangan, Stephanie Torres Rodriguez, Elba Medina, Jasmine Sethi, and Vamsidhar Veeranki
NephEdC Interns, Class of 2024
Summary, Visual Abstracts and Infographics reviewed by Brian Rifkin, Sabarinath S, Swapnil Hiremath, Sayali Thakare, Cristina Popa, Divya Bajpai, PS Vali, Anand Chellapan
Header Image created by AI, based on prompts by Evan Zeitler