Increased serum uric acid-to-urinary urate excretion ratio with the kidney function decline in male CKD patients without diabetes: a retrospective cohort study

Abstract

Background

The relationship between uric acid and chronic kidney disease (CKD) progression remains unclear. To study the association between the serum uric acid-to-24-hour-urinary urate excretion ratio (SUER) and kidney events in patients experiencing chronic kidney disease (CKD) progression.

Methods

A retrospective cohort study involving 165 CKD patients with estimated glomerular filtration rates (eGFRs) between 15 and 150 mL/min/1.73 m² was conducted at Huadong Hospital, Fudan University (Shanghai, P. R. China). The exposure variable was the SUER, whereas the outcome was a renal endpoint event, defined as a 50% decrease in eGFR from baseline, initiation of renal replacement therapy, or death during follow-up. Both univariate and multivariate logistic regression analyses were performed in the entire cohort and in male subgroups with or without diabetes mellitus. Forest plots were drawn to visualize the odds ratios (ORs) derived from multivariate regression analysis, and receiver operating characteristic (ROC) curves were constructed. And we divided the male non-diabetic population into low UACR group and high UACR group based on the median UACR, and conducted a univariate analysis of the differential variables. P < 0.05 was considered to indicate statistical significance.

Results

The general population aged 56.45 ± 15.76 years, and of which 65 (39.39%) CKD patients are females. The SUER was not the risk of experiencing renal endpoint events in the overall population (OR = 1.05; 95% CI: 0.680, 1.621; P = 0.826), but was an associated factor of renal endpoint events in males without diabetes (OR = 2.196; 95%CI:1.191,4.052; P = 0.012).

Conclusions

An increased SUER may be an indicator for kidney function decline in male CKD patients without diabetes. Further studies should focus on subgroup analyses of CKD patients particularly in male CKD patients without diabetes to evaluate whether uric acid-lowering measures are warranted.

Clinical trial number

Not applicable.

Background

The incidence and prevalence of chronic kidney disease (CKD) have steadily increased in recent years, with the relationship between hyperuricaemia status and CKD progression attracting substantial attention [1]. However, the effect of serum uric acid (SUA) on CKD progression remains unclear. A cohort study revealed that hyperuricaemia increases the risk of CKD development [2], yet asymptomatic hyperuricaemia is not an indication for urate-lowering therapy (ULT) [3]. Some studies have linked elevated UA to kidney function decline in both CKD patients and healthy individuals [4–6], whereas others have reported no significant association in advanced CKD patients [7].

Uric acid in the human body has two main forms: soluble in serum and urine and crystallized in urine. Basic research suggests that UA crystals, rather than elevated SUA levels alone, may contribute to kidney function decline [8]. However, studies indicate that hyperuricaemia status even within the normal range is associated with the risk of developing various diseases, including cardiovascular conditions, insufficient evidence exists to support the benefit of preventing asymptomatic hyperuricaemia on that risk [9]. Moreover, most studies on this topic focus exclusively on SUA levels, often neglecting the role of the kidneys in UA excretion. Research has suggested that locally high UA levels in renal cells or related urinary UA crystals and urinary stones, rather than SUA levels, are detrimental in CKD progression [10]. Although 24 h urinary urate excretion (UUE) has been investigated, low levels of UUE are thought to be a predictor of early kidney function decline in healthy individuals [11]. However, UUE alone cannot fully reflect the UA load in the kidneys, and it is influenced by diet [12]. Both the SUA level and the renal UA load are influenced by the dynamic regulation of UA production, glomerular filtration, and tubular reabsorption [4]. Investigating the renal UA load may provide a better understanding of the relationship between UA and kidney function decline and help explain the varying clinical outcomes of different ULT, such as the inhibition of UA production or the promotion of UA excretion [13, 14]. However, currently there is no good index to reflect renal UA load, as most markers such as the uric acid clearance rate (Cur), and fractional excretion of uric acid (FEUA) are all influenced by creatinine levels and fail to predict GFR decline calculated by creatinine. A clinical study revealed that FEUA would compensatively increase due to changes in serum creatinine (SCr). Cur reflects the ability of the kidneys to clear uric acid and can be used to identify “excretion-reduced type” hyperuricemia in CKD [15]. In fact, Cur is rarely used to clinically evaluate the uric acid excretion capacity. Similar to the Cur, the SUER combines the renal preload of uric acid and the total uric acid excretion to reflect the uric acid local retention in the kidneys, thereby facilitating the prediction of whether CKD will progress. SUER is a more accurate and convenient index calculated according to SUA and UUE, not affected by SCr.

Furthermore, sex differences in UA metabolism contribute to a greater prevalence of hyperuricaemia in men than in women [16]. A clinical study indicated that compared with those without diabetes mellitus, individuals with diabetes mellitus have greater UUE and FEUA [17].

Given that CKD patients often have multiple comorbidities that influence disease progression, the aim of this study was to explore the relationship between SUER and CKD progression through subgroup analyses, with the goal of providing evidence for the potential benefits of ULT.

Methods

Study population

This retrospective cohort study included 165 CKD patients admitted to Huadong Hospital, Fudan University (Shanghai, P. R. China), between 2015 Aug and 2024 Oct. The follow-up period of this study was defined from patients’ first admission to the occurrence of the outcome event or the last follow-up. It ranged from 1 month to 94 months, with a median follow-up time of 28 months, and complete follow-up data were obtained for all 165 patients. The inclusion criteria were as follows: (1) CKD diagnosis based on the KDIGO guidelines; (2) age ≥ 18 years; and (3) available follow-up data. The exclusion criteria were as follows: (1) an estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m²; (2) prior or current use of drugs affecting UA metabolism, such as UA-lowering drugs, diuretics, sodium-glucose co-transporter 2 inhibitors (SGLT2i) and immunosuppressants; and (3) undergoing haemodialysis, peritoneal dialysis, or kidney transplantation. The study protocol was approved by the ethics committee of Huadong hospital affiliated to Fudan University (No 2019K063).

Clinical characteristics collection

Patient demographic data, such as sex and age, were extracted from the medical records. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m²). Fasting peripheral venous blood and 24-hour urine samples were collected to measure SUA, UUE, SCr, total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and urinary albumin-to-creatinine ratio (UACR) levels. The eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula. The SUER was defined as the ratio of the SUA level to the 24-hour UUE rate and measured at the baseline.

The 24-hour urine samples were mainly collected during the participants’ hospitalization. We provided each participant with a 5-L container containing preservatives for urine collection and instructed them on proper 24-hour urine collection methods. The first morning void at 7:00 AM on the day prior to collection was discarded, and all subsequent urine was collected until the first morning void at 7:00 AM the following day. The total 24-hour urine volume was recorded; the samples were thoroughly mixed, and a 10 mL aliquot was sent to the Clinical Laboratory of Huadong Hospital for biochemical analysis on the same day.

Outcomes and group criteria

The study’s primary endpoint was a renal composite event, defined as a ≥ 50% decrease in eGFR from baseline, initiation of renal replacement therapy, or death. Patients were divided into event and non-event groups based on the occurrence of renal composite events. In subgroup analyses, male patients were further classified into diabetic and nondiabetic groups.

Statistical analysis

Missing values were imputed using multiple imputation, and the accuracy of this method was verified. Continuous variables are expressed as the mean ± standard deviation (SD) or median ± interquartile range (IQR) depending on their distribution. Categorical data are presented as frequencies and percentages. Comparisons of continuous variables between groups were made using t tests or rank sum tests, whereas categorical data were compared using chi-square tests. Univariate and multivariate logistic regression analyses were used to explore factors associated with kidney function decline. Forest plots were used to display the odds ratios (ORs) derived from multivariate regression analysis. Receiver operating characteristic (ROC) curves were generated to evaluate the ability of the SUER and other indicators to predict kidney function decline. A p value of < 0.05 was considered to indicate statistical significance. Statistical analysis was performed using SPSS 27.0 and R 4.4.1.

Results

Baseline characteristics

The study cohort included 165 CKD patients with eGFRs between 15 and 150 mL/min/1.73 m², who were categorized into the event group (n = 128) and the nonevent group (n = 37) on the basis of renal endpoint occurrence. The baseline characteristics of the patients are summarized in Table 1. The median eGFR was 54.56 mL/min/1.73 m², with higher SCr (182.80 µmol/L) and UACR (176.41 mg/mmol) in the event group than in the nonevent group. The event group also had a greater proportion of patients with hypertension (n = 32, 86.49%) and diabetes (n = 18, 48.65%). The SUER (1.87) and SUA levels (423.11 umol/L) were greater and UUE (224.47 mg/d/1.73 m²) was lower in the event group than in the nonevent group. These indicators likely influenced baseline kidney function. Other demographic indicators and clinical laboratory indicators are also presented in the table. These findings suggest that the SUER may be linked to the progression of CKD.

Table 1.

Baseline characteristics of CKD patients divided by the incidence of events

Variables	Total (n = 165)	Nonevent (n = 128)	Event (n = 37)	P
Age, year	56.45 ± 15.76	55.85 ± 16.61	58.51 ± 12.35	0.291
BMI, kg/m2	24.22 ± 4.33	23.85 ± 4.14	25.47 ± 4.79	0.058
Female, n, (%)	65 (39.39)	48 (37.50)	17 (45.95)	0.354
Hypertension, n, (%)	118 (71.52)	86 (67.19)	32 (86.49)	0.022*
Diabetes mellitus, n, (%)	48 (29.09)	30 (23.44)	18 (48.65)	0.003**
TC, mmol/L	4.64 (3.88, 5.40)	4.58 (3.83, 5.25)	4.96 (4.35, 5.96)	0.068
TG, mmol/L	1.60 (1.00, 2.30)	1.50 (1.00, 2.30)	2.10 (1.20, 2.60)	0.036*
LDL, mmol/L	2.62 (2.09, 3.42)	2.58 (2.09, 3.38)	2.70 (2.38, 3.61)	0.330
HDL, mmol/L	1.23 (1.08, 1.51)	1.23 (1.08, 1.55)	1.27 (1.09, 1.44)	0.783
SUA, µmol/L	394.19 ± 99.28	385.82 ± 100.98	423.11 ± 88.43	0.044*
UUE, mg/d/1.73 m2	226.41 (174.91, 298.32)	227.39 (176.37, 302.21)	224.47 (141.87, 266.26)	0.471
SUER	1.73 (1.23, 2.38)	1.70 (1.14, 2.34)	1.87 (1.46, 2.74)	0.120
UACR, mg/mmol	71.34 (7.59, 235.38)	44.50 (3.86, 185.98)	176.41 (71.60, 452.29)	< 0.001**
SCr, µmol/L	114.10 (82.00, 182.80)	101.90 (77.68, 140.38)	182.80 (141.00, 225.30)	< 0.001**
eGFR, ml/min/1.73 m2	54.56 (30.00, 84.55)	61.34 (40.12, 90.88)	28.67 (21.86, 41.59)	< 0.001**

CKD: chronic kidney disease; *P<0.05;**P<0.01

Relationship between the SUER and kidney outcome in the general population

To explore the impact of the SUER on kidney function, we screened several factors with significant differences (P < 0.05) and related factors that may affect kidney function, such as age and BMI (Table 1). Univariate analysis was performed to identify factors that may influence renal endpoint events (Table 2). Although the SUA, SCr and UACR were all significantly associated with the outcome, the OR values were all 1.01. Hypertension and diabetes status were also associated with an increased risk of kidney failure (OR = 3.13, P = 0.027; OR = 3.09, P = 0.004). However, a high SUER did not increase the risk of kidney function decline in the general population (OR = 1.21, P = 0.203).

Table 2.

Univariate analysis of the associations between indicators and kidney outcome in total people

Variables	OR (95% CI)	P
Hypertension	3.13 (1.14 ~ 8.60)	0.027*
Diabetes mellitus	3.09 (1.44 ~ 6.64)	0.004**
Age, year	1.01 (0.99 ~ 1.04)	0.365
BMI, kg/m2	1.10 (1.00 ~ 1.21)	0.059
TG, mmol/L	1.20 (0.96 ~ 1.49)	0.104
SCr, µmol/L	1.01 (1.01 ~ 1.02)	< 0.001**
SUA, µmol/L	1.01 (1.01 ~ 1.01)	0.046*
SUER	1.21 (0.90 ~ 1.64)	0.203
UACR, mg/mmol	1.01 (1.01 ~ 1.01)	< 0.001**

*P<0.05;**P<0.01

To exclude the influence of confounding factors, confounding factors were included stepwise to build a model to analyse the relationship between the SUER and kidney function decline, as shown in Table 3. The effect of the SUER on the risk of renal failure was not statistically significant in the model 3 (OR = 1.05, P = 0.826). A forest plot showing the relationships between all the factors and the risk of experiencing renal endpoint events is shown in Fig. 1a. The ROC curve confirmed that the UACR (AUC = 0.746) and SCr (AUC = 0.744) were better indicators of kidney function decline than the SUER (AUC = 0.580) was, as shown in Fig. 1b. In the general CKD population, the SUER is not associated with kidney function decline.

Table 3.

The association between the SUER and the risk of experiencing kidney outcomes in total population

Event, n	Deaths	RRT	50% reduction in eGFR
37	3	22	36

	OR (95% CI)		P
Unadjusted	1.215 (0.900–1.640)		0.203
Model 1	1.206 (0.853–1.707)		0.289
Model 2	1.266 (0.881–1.820)		0.202
Model 3	1.050 (0.680–1.621)		0.826

Notes: Model 1 was adjusted for BMI and age. Model 2 was adjusted for BMI, age, diabetes mellitus status and hypertension status. Model 3 was adjusted for BMI, age, hypertension status, diabetes mellitus status, SCr level and the UACR. RRT: renal replacement therapy; eGFR: estimated Glomerular Filtration Rate. OR: odds ratio; 95%CI: 95% confidence intervals

Fig. 1.

Relationships between the SUER and kidney outcome in the whole CKD cohort. (a) Multivariate logistic regression and forest plot of the SUER and kidney outcomes. (b) ROC curves of the SUER, the UACR, and SCr levels. SUER: serum uric acid-to-24-hour-urinary urate excretion ratio; SCr: serum creatinine; UACR: urinary albumin-to-creatinine ratio; OR: odds ratio; 95% CI: 95% confidence interval; AUC: area under the curve

Subgroup analysis in males

Previous clinical studies focused only on SUA or UA excretion, and the conclusions were conflicting. Little attention has been given to the load on the kidneys. Therefore, we classified the population into subgroups to further explore the relationship between the SUER and kidney function. In male patients, a significant relationship between the SUER and kidney outcome was observed in those without diabetes (Table 4). According to the unadjusted model, the OR of the SUER for kidney outcome was 1.757 (95% CI: 1.070, 2.888; P = 0.026). It is important to emphasize that in the subgroup of male CKD patients without diabetes, the number of endpoint events for kidney outcomes was merely 7. After adjusting for the confounder UACR, a greater SUER remained significantly associated with an increased risk of experiencing renal endpoint events in men without diabetes (OR = 2.196, 95% CI: 1.191, 4.052; P = 0.012). In men with diabetes, it seems that SUER is not the associated factor of the renal function decline. The forest plot shows the OR values and P values for men with and without diabetes in adjusted model (Fig. 2a, b). As shown in Fig. 2c, the ROC curve revealed that the SUER (AUC = 0.770) had better diagnostic efficacy than did the UACR (AUC = 0.665) and SCr (AUC = 0.700) in this subgroup. Moreover, by combining the ROC curve and the calculation formula of Youden’s Index (J = Sensitivity + Specificity – 1), we determined that when SUER was 1.87, the J value reaches its maximum (sensitivity = 0.86; specificity = 0.62; J = 0.86 + 0.62-1 = 0.48). At this point, the cut-off value of the SUER was 1.87 and the optimal Youden’s Index was 0.48, suggesting that a higher SUER is associated with an increased risk of kidney function decline in this population. The subgroup analysis implied that the SUER is an associated factor for the kidney function decline in male CKD patients without diabetes.

Table 4.

The association between the SUER and the risk of experiencing kidney outcomes in subgroups

Male (n = 100)	Non-diabetes mellitus (n = 71)		Diabetes mellitus (n = 29)
Events, n (%)	7 (9.85)		13 (44.83)

	OR (95% CI)	P	OR (95% CI)	P
Unadjusted	1.757 (1.070–2.888)	0.026*	0.537 (0.136–2.114)	0.374
Adjusted	2.196 (1.191–4.052)	0.012*	0.408 (0.077–2.162)	0.291

Notes: Adjusted for the UACR. OR: odds ratio; 95% CI: 95% confidence interval. *P<0.05;**P<0.01

Fig. 2.

Relationships between the SUER and kidney outcome in the male CKD cohort. a, b Multivariate logistic regression and forest plot of the SUER and kidney outcomes in males with diabetes and without diabetes; c ROC curve of the SUER, UACR, and SCr in males without diabetes. SUER: serum uric acid-to-24-hour-urinary urate excretion ratio; SCr: serum creatinine; UACR: urinary albumin-to-creatinine ratio; OR: odds ratio; 95% CI: 95% confidence interval; AUC: area under the curve

Given the importance of UACR in research on CKD populations, to further eliminate the influence of this confounding factor, we divided the male non-diabetic population into low UACR group and high UACR group based on the median UACR value (41.88 mg/mmol). Through the analysis of baseline data from the two groups, we screened all potential factors (TC, TG, LDL, HDL and SUER) and performed univariate regression analyses for the low-UACR and high-UACR groups respectively in the Table 5. The results showed that SUER was the indicator for the progression of renal function in low-UACR group of non-diabetic male patients (OR = 1.97; 95% CI: 1.03, 3.80; P = 0.042), while other indicators did not have statistical significance.

Table 5.

Univariate analysis of the associations between indicators and kidney outcome in low-UACR and high-UACR groups of non-diabetic male patients

Male + Non - diabetes mellitus (n = 71)	Low-UACR (n = 37)		High-UACR (n = 34)
Event, n, (%)	3 (8.1)		4 (11.76)

Variables	OR (95% CI)	P	OR (95% CI)	P
TC, mmol/L	0.75 (0.16 ~ 3.55)	0.715	0.91 (0.49 ~ 1.69)	0.767
TG, mmol/L	1.97 (0.44 ~ 8.76)	0.376	1.33 (0.83 ~ 2.12)	0.238
LDL, mmol/L	0.40 (0.05 ~ 3.26)	0.392	0.64(0.25 ~ 1.62)	0.345
HDL, mmol/L	1.63 (0.01 ~ 234.69)	0.847	1.94 (0.24 ~ 15.51)	0.533
SUER	1.97 (1.03 ~ 3.80)	0.042*	1.56(0.61 ~ 3.94)	0.352

*P<0.05;**P<0.01

Differences in men without diabetes

To verify whether an increased SUER is associated with the risk of renal decline in men without diabetes, we divided men without diabetes into an event group and a nonevent group according to the occurrence of endpoint events. The results of the difference analysis are shown in Table 6. The SUER was the only significantly different factor between the two groups (M ± IQR = 1.68 (1.17, 2.23); 2.77 (2.07, 4.20); P = 0.021). The finding suggested that a higher SUER may be associated with kidney function decline in CKD patients without diabetes.

Table 6.

Differences between patients with and without kidney events in men without diabetes

Variables	Total (n = 71)	Nonevent (n = 64)	Event (n = 7)	P
Age, year	56.23 ± 16.15	55.81 ± 16.68	60.00 ± 10.13	0.519
BMI, kg/m2	23.46 ± 4.56	23.45 ± 4.68	23.52 ± 3.79	0.972
Hypertension, n, (%)	48 (67.61)	42 (65.62)	6 (85.71)	0.514
TC, mmol/L	4.56 (3.82, 5.28)	4.58 (3.83, 5.25)	3.86 (3.57, 5.29)	0.643
TG, mmol/L	1.50 (1.00, 2.20)	1.50 (1.00, 2.23)	1.30 (1.10, 2.15)	0.954
LDL, mmol/L	2.57 (2.00, 3.42)	2.62 (2.10, 3.45)	1.87 (1.69, 2.58)	0.112
HDL, mmol/L	1.17 (1.00, 1.38)	1.15 (0.99, 1.37)	1.28 (1.19, 1.43)	0.173
SUA, µmol/L	411.17 ± 100.78	404.69 ± 100.78	470.43 ± 85.44	0.102
UUE, mg/d/1.73 m2	250.60 ± 108.06	257.72 ± 107.30	185.46 ± 99.19	0.093
SUER	1.71 (1.21, 2.37)	1.68 (1.17, 2.23)	2.77 (2.07, 4.20)	0.021*
UACR, mg/mmol	41.88 (3.81, 147.53)	41.29 (3.32, 141.54)	55.60 (23.80, 380.01)	0.158
SCr, µmol/L	101.90 (83.05, 152.60)	101.70 (81.40, 139.85)	182.80 (119.60, 221.35)	0.081
eGFR, ml/min/1.73 m2	66.00 (41.23, 89.37)	68.88 (51.29, 92.77)	34.40 (29.13, 61.56)	0.084

*P<0.05;**P<0.01

Discussion

Renal UA can damage tubular cells and impact kidney function, but whether the UA load of the kidneys contributes to CKD progression remains unclear. To gain a better clinical insight of the relationship between the SUER and CKD progression, we conducted a retrospective study. Our study, which included 165 CKD patients whose follow-up data revealed eGFRs ranging from 15 to 150 mL/min/1.73 m², revealed that although the SUER was not significantly associated with kidney function decline in the overall CKD population, it emerged as a significant predictor in male CKD patients without diabetes. This highlights the importance of considering both sex and diabetes status when evaluating the role of UA in CKD progression and provides evidence for implementing ULT. Moreover, the UACR level should also serve as a reference indicator for determining whether to administer ULT in male non-diabetic populations.

FEUA has traditionally been used to evaluate renal UA excretion. Our data, which are consistent with those of previous studies, show that FEUA tends to increase with increasing SCr levels in CKD patients, whereas overall renal excretion capacity decreases [18]. However, in the present study, we found FEUA is influenced by multiple factors, making it susceptible to confounding. On the basis of the FEUA, we identified another indicator reflecting the UA load in the kidneys, called the SUER. Unlike the FEUA, the SUER incorporates both SUA levels and UUE, potentially offering a more dynamic and precise measure of renal UA load.

In our analysis, the SUER was not associated with kidney function decline in the overall population, likely due to the complex pathophysiological conditions of CKD patients, many of whom have comorbidities such as diabetes and hypertension [19]. Effective management of these conditions is crucial for slowing CKD progression [20, 21]. In the male non-diabetic subgroup, however, the SUER was significantly associated with CKD progression, suggesting that sex-specific and disease-specific factors influence the relationship between UA metabolism and kidney function. Women are less prone to hyperuricaemia than men are due to the protective effects of oestrogen, which inhibits xanthine oxidase activity and reduces UA production [22, 23]. This protective effect diminishes after menopause, but hormone replacement therapy can mitigate the cardiovascular risks associated with elevated SUA levels [24].

Diabetes itself is a major factor in kidney function decline, which may mask the effects of the SUER in diabetic patients. Urinary glucose is closely related to urinary UA, and diabetes can affect UA metabolism. Elevated blood glucose levels promote UA excretion, affecting both SUA and FEUA [25]. Additionally, hyperuricaemia secondary to metabolic syndrome or diabetes may not reliably predict CKD development [26]. These findings underscore the need for precision medicine approaches when evaluating the role of UA in CKD progression. A clinical trial also found the ULT would decrease the incidence of new onset CKD with DM and without hypertension, which highlighted the main cause of CKD progression and choice of ULT medicine [27]. Notably, both our data and findings from previous studies have shown that, in CKD patients, the relationship between SUER and renal function is also associated with the level of UACR. Additionally, ULT may be more effective in CKD patients with low UACR or negative proteinuria [28]. Given the emerging trend towards precision typing in CKD management [29] and the present findings, it is critical to recognize population-specific differences in UA metabolism, such as those influenced by sex [22], age [30], and regional factors [31], and administer ULT to CKD patients without other severe diseases and with low UACR level.

An elevated SUER may indicate higher SUA levels, lower UUE, or a combination of both, leading to UA retention in the kidneys. Conversely, a moderate SUER suggests an adequate renal capacity to excrete excess UA. Changes in the SUER can reflect two forms of kidney damage—impaired filtration or increased tubular reabsorption—aligning with the “low filtration” and “high reabsorption” phenotypes of hyperuricaemia [32]. Our calculated SUER cut-off value indicates that when the SUER exceeds this threshold 1.87, the renal UA load is likely elevated, indicating that interventions are warranted. Experimental studies have shown that renal UA, whether in soluble or crystalline form, can impair kidney function through inflammatory pathways [33, 34], oxidative stress [35] and tubular cell apoptosis [36]. Potential strategies include reducing UA production, enhancing excretion [37], and targeting local inflammation [38].

In the present study, SUER was measured once at baseline, reflecting the patients’ uric acid metabolic status at the time of enrollment. The observed association between baseline SUER and the long-term risk of kidney function decline suggests that baseline SUER may serve as a potential early warning indicator for disease progression. However, it is important to note that SUER levels may change with CKD progression. Future prospective studies could incorporate repeated measurements of SUER to further validate the impact of its dynamic changes on clinical outcomes.

This study has several limitations. First, the sample size was relatively small. Data on key lifestyle factors, such as education level, smoking, and dietary factors known to influence uric acid metabolism (specifically purine intake, alcohol consumption, and sugar-sweetened beverage consumption), were not collected or included in the analysis. However, the core variables focused on in this study, such as SCr and the UACR, provide support for the conclusions of the study. Second, as a single-center study with an older patient cohort, the findings may not be generalizable to younger populations, which provides a direction for exploring the comparison between age groups. And patients using SGLT2 inhibitors were excluded from this study to eliminate potential confounding effects of these drugs on uric acid metabolism. It also limits the external validity of the results. Specifically, our conclusions may only be applicable to CKD patients who are not receiving SGLT2i treatment, and cannot be directly generalized to those on long-term SGLT2 inhibitor therapy. Finally, due to the limited data on included participants, endpoint events and follow-up duration, subgroup analyses were restricted to sex, and we could only conduct a preliminary analysis of UACR. Moreover, we were unable to perform standard survival analysis to assess the relationship between SUER and the time to kidney function decline. Notably, there are only 7 endpoint events in the subgroup, which impairs statistical power and increases uncertainty associated with effect estimation. Further research is therefore deemed necessary to verify SUER’s potential role as a risk marker or therapeutic target. Additionally, this result suggests that future studies with larger cohorts should investigate differences in kidney outcome across CKD stages, UACR levels and other factors.

Conclusions

In conclusion, this observational study suggests an association between elevated SUER and an increased risk of kidney function decline in male CKD patients without diabetes. However, such an association was not observed in the overall population or in male diabetic patients. These preliminary findings highlight the potential need for further population-specific research to guide the management of ULT, particularly in male CKD patients without diabetes.

Abbreviations

CKD

Chronic kidney disease

SUER

Serum uric acid-to-24-hour-urinary urate excretion ratio

eGFRs

Estimated glomerular filtration rates

ORs

Odds ratios

ROC

Receiver operating characteristic

SUA

Serum uric acid

UA

Uric acid

UUE

24 h urinary urate excretion

Cur

Uric acid clearance rate

FEUA

Fractional excretion of uric acid

SCr

Serum creatinine

BMI

Body mass index

TC

Total cholesterol

TG

Triglyceride

LDL

Low-density lipoprotein

HDL

High-density lipoprotein

UACR

Urinary albumin-to-creatinine ratio

ULT

Urate-lowering therapy

Author contributions

LN: Data curation, Investigation, Formal analysis, Methodology, Software, Visualization, Writing-original draft, Validation and Writing-review & editing. RP: Data curation and Investigation, Formal analysis and Methodology. XY, MM, DZ, ST, SC and YB: Data curation and Investigation. JX: Data curation, Investigation, Conceptualization, Formal analysis, Methodology, Supervision, Validation and Writing-review & editing. FZ: Data curation, Investigation, Conceptualization. All authors approved the final manuscript.

Funding

This work was supported by the Key Specialized Disease Construction Plan of Huadong Hospital (Grant Number ZDZB2223). The funders of this study did not have any role in study design; collection, analysis, and interpretation of data; writing the report; nor in the decision to submit the report for publication.

Data availability

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

All procedures involving human participants in this study were conducted in accordance with the Declaration of Helsinki and have been approved by the Ethics Committee of Huadong Hospital, Fudan University (No 2019K063). Written informed consents were obtained from all subjects. This article does not contain any research on animals by any author.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.