Background

With more than 850 million people affected worldwide, Chronic Kidney Disease (CKD) has evolved into a serious public health issue [1,2]. The global burden of CKD is expected to increase substantially from 1.2 million deaths in 2016 to as many as 4.1 million deaths in 2040, rising from 16th to 5th place among the leading causes of death worldwide [3]. This rapid trend is linked to a growing and simultaneously ageing population, which is additionally accompanied by an increase in disease-promoting risk factors such as diabetes and hypertension [3]. CKD is a progressive illness for which there is no cure, hence current treatment options aim to slow the decline in kidney function. Transition to end-stage kidney disease (ESKD) implies kidney replacement therapy, i.e., dialysis and kidney transplantation, as a life-sustaining measure [4]. To spare patients from stressful interventions, it is important to diagnose and treat CKD early. However, a major issue is that the disorder is predominantly asymptomatic in its early stages and is therefore not in the primary focus of general practitioners (GPs), resulting in a high number of undiagnosed cases [5]. Structured screening for CKD, that concentrates on identifying individuals at-risk and timely intervention can overcome this challenge. This review emphasizes the role of GPs in the early identification of people with CKD and is intended to raise awareness of the risk factors. Diagnostic and therapeutic strategies are summarized to support optimal and earliest possible CKD management in the primary care setting.

Definition and Classification of CKD

A widely accepted definition of CKD is proposed by the Kidney Disease: Improving Global Outcomes (KDIGO) 2012 guideline which sets the following three criteria for the presence of the disorder: (1) a reduced kidney function manifested by a Glomerular Filtration Rate (GFR) <60 mL/min per 1.73 m² (2) and/or evidence of a single or more markers of kidney damage, (3) persisting for >3 months. Markers associated with kidney injury are albuminuria (urine albumin-to-creatinine ratio (UACR) ≥30 mg/g), abnormalities of either urine sediment, electrolytes, tissue or kidney structure, and a history of kidney transplantation [6].

The KDIGO guidelines recommend CKD classification (Figure 1) using the two diagnostic parameters GFR and UACR, in addition to the underlying cause. Categories for GFR range from G1 (≥90 ml/min per 1.73 m², normal or high) to G5 (<15 ml/min per 1.73 m², kidney failure). Albuminuria is grouped into three entities: A1 (ACR <3 mg/mmol  <30 mg/g, normal to mildly increased) to A3 (ACR >30 mg/mmol  <300 mg/g, severely increased). To exclude acute kidney injury, repeated measurements of these parameters are required before CKD can be diagnosed and categorized. Investigation into the cause of CKD includes assessment of the clinical context, social and environmental factors, personal and family history as well as medications, and is complemented by further diagnostic tests [6].

Figure 1: Chronic Kidney Disease (CKD) classification by Glomerular Filtration Rate (GFR) and albuminuria. Risk categories are assigned to the respective disease stages. Individuals with GFR values ≥60 mL/min per 1.73 m² in the absence of significantly increased albumin excretion (category A1) are at low risk for adverse cardiovascular and kidney events. If there are no signs of kidney injury, there is no evidence of CKD (green). Other categories are related to CKD and are associated with moderately increased risk (yellow), high risk (orange), or very high risk (red) for adverse outcomes. Adapted from [6,7].

Diagnostic gaps

It has been demonstrated in population-based studies that CKD is significantly underdiagnosed. Without CKD screening as part of the studies, around half of those with the condition would not have been diagnosed [8,9]. The multinational, observational REVEAL-CKD study collected comprehensive data on people living with stage 3 CKD between 2015 and 2020 in developed countries. The recently published results show that the prevalence of undiagnosed stage 3 CKD ranges from 61.6-95.5% across countries, with lower rates of diagnosis in women (vs. men) and older individuals (vs. younger individuals). In a U.S. sub-database of the study, the median time for undiagnosed individuals with stage 3 CKD to get diagnosed was 4.75 (4.68-4.82) years [5,10]. This complete lack or delay of diagnosis and concomitant interventions allows unrestrained progression of CKD, which is linked to an increased risk of cardiovascular events, hospitalization, and death [11]. Particularly sobering is the low rate of UACR testing (overall prevalence of 1.8 - 5.5% across countries), even in a postdiagnosis monitoring setting (0.05 measurements per person-year) when guidelines recommend a frequency of at least once per year in high risk populations [5, 6, 12]. In people with type 2 diabetes (T2D) the detection of CKD appears to be comparatively low. Only 1.1% (stage 1), 4.9% (stage 2), 18% (stage 3), 52.9% (stage 4), and 58.8% (stage 5) of individuals with CKD were diagnosed in a U.S. study, respectively. Interestingly, the rate for UACR testing was also found to be poor (15 months prior to the study 52.9% of individuals without UACR measurement), which might explain low detection rates of early CKD stages [13].

Risk Factors for CKD and Implications for Screening

CKD becomes symptomatic mainly in late stages, while early disease can often be only detected by screening. Therefore, risk factors play an important role in identifying individuals with CKD (Figure 2).

Figure 2: Risk factors for the incidence and progression of chronic kidney disease (CKD). Among the risk factors, there are modifiable and non-modifiable components.

Among all risk factors, diabetes and hypertension are the most prominent (14). Globally, diabetes ranks first [14] with a threefold increase in the risk of CKD [15,16] and a prevalence of CKD among individuals with type 2 diabetes (T2D) ranging from 6.0-39.3 % [17]. However, in some regions, e.g., East Asia, hypertension is the number one risk [14,18]. Not surprisingly, people with both conditions are at greater risk of developing CKD than those with just one condition (18). Due to the close link between kidney and heart, cardiovascular diseases (CVDs) are inevitably another potent risk factor for CKD, as reflected by the high prevalence of CVD in CKD of up to 47.2% [19-23]. Other common factors associated with an increased risk of CKD include obesity, dyslipidemia, smoking, and a history of acute kidney injury [16, 24, 25]. However, this list can be extended with less common or socio-economic-related risk factors, e.g., multisystem diseases affecting the kidney (e.g., systemic lupus erythematosus and human immunodeficiency virus) and environmental exposure to nephrotoxins [26-28].

Non-modifiable risk factors comprise gender, age, ethnicity, and other genetic determinants. While the prevalence of CKD is higher in women, the progression of CKD appears to be faster in men and older individuals [29-31].

The American Diabetes Association (ADA) and KDIGO have agreed that individuals with type 1 diabetes should be screened annually starting five years from diagnosis and people affected by T2D should be screened yearly directly after diagnosis [32]. Additionally, conclusions of a KDIGO controversies conference imply that people with hypertension and/or CVD should also be targeted in screening and that the examination of individuals with other risk factors for CKD should be based on individualized clinical assessment and shared decision-making [33].

Since individuals are often being cared for because of other diseases/risk factors that have already been identified, primary care is predestined for CKD screening and offers the opportunity to intervene early in the course of the disease.

Diagnostic tools GFR assessment

GFR is a measure of the kidney’s ability to filter blood plasma and is the sum of the filtering capacities of the single nephrons. It is mostly determined indirectly as an estimate derived from measurements of a blood sample. The determination is based on endogenous filtration markers, such as creatinine and cystatin C, which in healthy individuals show stable serum levels. Creatinine originates from a muscular degradation process and therefore levels depend on muscle mass, whereas cystatin C is a ubiquitously expressed protein, rendering it a more uniform marker across populations and a superior biomarker [34-36]. However, due to economic and availability reasons, creatinine is currently the preferred indicator for initial investigations [37]. Two methods are commonly used to measure serum creatinine: the Jaffe technique, which is a colorimetric approach, and enzymatic assays. Comparison of the two methods shows that the Jaffe technique produces greater measurement inaccuracies and therefore can lead to more misclassifications [38,39].

Generally, it can be assumed that decreasing kidney function and GFR is coupled with an increase in serum concentrations of the endogenous marker molecules, yet other determinants than glomerular filtration influence the absolute values. To account for this, estimation equations have been developed that incorporate demographic and clinical variables, enabling more precise estimates of GFR (eGFR) to be reported [40]. Established formulas are the creatinine and/or cystatin C based equations of the Chronic Kidney Disease Epidemiology Collaboration (CKDEPI). The European Kidney Function Consortium (EKFC) has published another creatinine-based formula for the entire age spectrum, which has been supplemented by a cystatin C formula, both of which have a high degree of accuracy [41, 42]. CKDEPI and EKFC formulas outperform the previously developed Modification of Diet in Renal Disease (MDRD) formula in terms of accuracy and should be preferably used in routine clinical practice [41,43]. Moreover, formulas that include both biomarkers yield better estimates [44]. Measuring GFR (mGFR) via plasma or urinary clearance of exogenous filtration markers is the gold standard, but complex and time-consuming therefore only useful when it is essential to know the exact kidney function (Figure 3) [45].

Figure 3: Suggested protocol for glomerular filtration rate (GFR) assessment according to KDIGO. Estimated GFR (eGFR) is determined from blood samples and requires confirmatory measurements

For CKD diagnosis a confirmatory measurement after three months is recommended, if an eGFR <60 mL/min/1.73 m² is detected to rule out transient falls in the parameter [7].

Albuminuria assessment

The urine of healthy people contains no or only very little amounts of albumin, thus its presence in urine is an indicator of a defective glomerular filtration barrier, with 30 mg per day representing the cut-off value for pathological urinary albumin excretion [46].

Albuminuria is associated with the progression of CKD and increased risk for cardiovascular events, thus is an important prognostic marker [47,48]. According to the KDIGO classification, stage 1-2 CKD can only be diagnosed by persistent albuminuria or other markers of kidney impairment, but not by reduced eGFR alone. The simplest method of detecting albuminuria is to use urinary dipsticks, but also the most inaccurate approach as their sensitivity for moderately increased albuminuria is rather weak [49]. They are therefore more suitable for preliminary investigations and should be followed by more detailed testing. Quantitative results obtained by normalization of urinary albumin to urinary creatinine (urine albumin-to-creatinine ratio, UACR) from spot urine samples are more meaningful. International guidelines for CKD recommend UACR for technical, standardization, and precision reasons [6, 50]. If screening for CKD reveals a UACR ≥30 mg/g, re-testing in three months is suggested to confirm persistent albuminuria for diagnosis [7]. Transient increases in urinary albumin can be caused by e.g., menstruation, febrile illness, acute hyperglycemia, uncontrolled hypertension, exercise, urinary tract infections, and heart failure [51, 52]. It should be noted that the detection of severely increased albuminuria (UACR >300 mg/g) requires prompt consultation with a nephrologist [6, 7]. The gold standard for assessing albuminuria is a 24-hour urine collection, but this is laborious, so determining ratios from a spot urine sample, preferably a morning void mid-stream sample, is a more practical option.

To support early CKD diagnosis and treatment, UACR point-of-care testing (POCT, Figure 4) has been demonstrated to be effective, particularly in secondary prevention. In individuals with T2D the screening in spot urine with UACR POCT produced a diagnostic yield of 10.6% and 13.4% for newly diagnosed and suspected CKD, respectively. A change of medication based on the UACR POCT was performed in 21.6% of individuals with T2D and mostly in those with a severely increased UACR of >30 mg/ mmol. The majority of physicians involved in the study regarded UACR POCT as very important for people with diabetes (75%) and important for individuals without diabetes (75%) [53]. Thus, POCT tools should be made available in primary care to improve diagnostic rates and quality of care.

Figure 4: Urine albumin-to-creatinine ratio (UACR) point-of-care testing (POCT). The technique enables to screen fast for structural changes in the kidney to diagnose chronic kidney disease (CKD).

Further diagnostics Urinalysis

Urinalysis can give insights into the presence and cause of CKD, is simple, and therefore should be performed when screening for CKD. Chemical analysis with urinary dipstick tests can provide evidence of urinary tract infections, pH, glycosuria, hematuria, and the previously described albuminuria. Signs of the latter two are hallmarks of glomerular disease [54].

Ultrasound imaging

Studies have proven that kidney size and echogenicity correlate with kidney function [55,56]. Notably, compared to the more traditional reporting of kidney length, cortical thickness and kidney volume are better surrogates for kidney function. Cortical thinning is a more suitable indicator for the early stages of CKD, whereas a reduced kidney volume becomes apparent at later stages of CKD [56].

Risk prediction tools

For people with diagnosed CKD, risk prediction tools help to identify individuals at high risk of ESKD or adverse cardiovascular outcomes. Thus, they offer guidance for preventive therapies and referral to specialist services on a personalized level. There are numerous equations developed, however, only tools with a low bias and externally validated methods that have been verified in the population for which the application is intended should be used [57]. A recommended equation for the use in practice that predicts the two- and five-year risk for kidney failure is the Kidney Failure Risk Equation (KFRE) based on either four (age, sex, eGFR, urine ACR) or eight variables (additionally serum albumin, phosphorous, bicarbonate, and corrected calcium). Since this formula was developed for individuals with CKD stage 3-5, its calculation is only accurate for this population [58]. To evaluate cardiovascular risk in people with CKD, the QRISK3 model, and the pooled cohort equation (PCE) or the Systematic COronary Risk Evaluation 2 (SCORE2) that utilize kidney-specific parameters for calculation, can be applied [59-61]. A compilation of risk calculators including most of the listed risk models is accessible under the following link: https://www.ckdpc.org/risk-models.html) [62].

Treatment of CKD

Pre-treatment stratification

Depending on the CKD stage and the respective risk category that can be assigned after screening, further measures are taken (Figure 5). Upon diagnosis of CKD, treatment needs to be initiated immediately. Furthermore, routine monitoring to enable appropriate therapy and timely referral to specialist services are important aspects in the prevention of CKD progression. The delayed consultation with a nephrologist in people with CKD has been shown to worsen clinical outcomes [63]. Several guidelines recommend referral from stage 4 (GFR <30 ml/min per 1.73 m²) or earlier and mention numerous other criteria for referral, e.g., haematuria, abrupt or large sustained falls in GFR, severe albuminuria, resistant hypertension, or persistent hyperkalaemia [6,32,50]. For people with progressive CKD, validated prediction tools such as the KFRE can guide timely referral for planning Renal Replacement Therapy (RRT).

Figure 5: Chronic Kidney Disease (CKD) classification by glomerular filtration rate (GFR) and albuminuria, including further guidance. The numbers in the coloured boxes, which represent risk categories for adverse cardiovascular or kidney outcomes, indicate the suggested screening/monitoring frequency per year. In the absence of markers of kidney injury and normal GFR, the presence of CKD is not evident (green, low risk), with screening recommended once per year. After diagnosis, CKD is treated and monitored once per year (yellow, moderately increased risk) to four times or more per year, i.e., every 1-3 months. Further risk categories are associated with high risk (orange) or very high risk (light and dark red) for adverse outcomes. Individuals with a very high risk require referral to a nephrologist. Adapted from [6, 7, 32].