Abstract
Objective
The objective is to find whether serum uric acid (SUA) levels are associated with the progression of chronic kidney disease (CKD) remains uncertain, and follow-up data among the elderly population are relatively lacking, especially in China. The aim of the present study was to reveal the association between baseline SUA levels, changes in SUA levels, and renal failure in Chinese elderly adults.
Methods
In this retrospective cohort study, 425 subjects (age range 71–100 years) were analyzed and divided into quartiles based on baseline SUA levels (Q1: <4.8; Q2: <5.7; Q3: <6.5; and Q4: ≥6.5 mg/dl). CKD was defined as estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2. We used multiple linear and logistic regressions to compare the risk of renal dysfunction among the different SUA level groups.
Results
The prevalence of hyperuricemia was 24.24% in the elderly subjects. In the multivariable analysis, the odds ratio (OR) for the development of CKD increased with the increase in SUA quartiles at baseline (1.00 vs. 1.79 (95% CI, 1.00–3.22), 3.4 (95% CI, 1.79–6.47), and 6.79 (95% CI, 3.45–13.75), respectively; P for linear trend <0.001), and a per unit increase in baseline SUA levels gave an OR of 1.76 (95% CI, 1.45–2.14) for renal failure. At the same time, a change in SUA levels had a stronger inverse correlation with a change in eGFR in females (r = −0.318, P < 0.001) than in males (r = −0.187, P < 0.01). In a linear regression analysis, a 1 mg/dl increase in SUA levels was associated with an additional 1.25 (95% CI, −1.83 to −0.67) ml/min/1.73 m2 decrease in eGFR over a 3-year period.
Conclusion
Elevated baseline SUA levels and changes in SUA levels were associated with a decline in eGFR and an increased risk of CKD in an elderly Chinese population.
1. Introduction
Chronic kidney disease (CKD) has become a global public health problem. In China, patients with CKD account for 4.86% of all hospitalized patients, and their median cost and length of hospital stay are higher than those for patients without CKD [1]. Among the end-stage renal disease population, elderly individuals over 65 years constituted the most rapidly growing and the largest age group [2, 3]. The combination of high prevalence and age-related comorbidities might increase the burden on public medical resources. Thus, early detection and intervention for potential risk factors are essential for preventing or delaying the development of CKD and reducing its complications.
Serum uric acid (SUA) is generated from the metabolism of purine nucleotides, and approximately two-thirds of SUA is excreted via the kidneys [4]. Over the last decades, hyperuricemia (HUA) has been considered to be an independent risk factor for the occurrence and progression of CKD [5–8], and uric acid has a “J-shaped” relationship with all-cause mortality in CKD patients [9]. Meanwhile, sufficient evidence has confirmed the clinical benefits of urate-lowering therapy in slowing CKD progression [10]. However, many studies on the association between elevated uric acid levels and CKD have yielded inconsistent results [9, 11]. It is still unclear whether elevated uric acid is simply a marker of renal insufficiency, strongly associated with adverse outcomes in CKD, or both.
Almost all of these studies were focused on adults, and follow-up data among the elderly population are relatively lacking, especially in China. In a cohort study including 1410 elderly residents from Beijing, Zhang reported an adjusted OR of 1.19 in the association between incident CKD and each 1 mg/dl increase in the SUA level [12]. Another study based on a general population in China also showed similar results but with a weak association [13]. In addition, Asians seemed to have a stronger positive association between SUA levels and CKD than non-Asians, despite a lack of statistical significance in the heterogeneity [14]. In short, we aimed to describe the relationship between SUA levels and CKD in an elderly Chinese population-based sample. This study might play an important role in the preservation of renal function in elderly Chinese individuals with hyperuricemia (HUA) and provide clinicians with more knowledge about the risk factors associated with CKD.
2. Materials and Methods
2.1. Study Design
All participants in this study received two comprehensive health examinations in both 2018 and 2021, which were conducted at the Zhejiang Province People's Hospital. We excluded 38 subjects who had used diuretics or urate-lowering drugs at baseline and 21 subjects for having a past history of the following: a baseline eGFR <15 ml/min/1.73 m2; gout; malignancies; acute cardiovascular and cerebrovascular disease; infectious disease; or other life-threatening diseases. Another 29 subjects were excluded due to loss to follow-up. Consequently, a total of 425 subjects (224 males and 201 females, age range 71–100 years) were enrolled in this study. The Zhejiang Provincial People's Hospital Ethics Committee approved the protocol for this study (2020QT179).
2.2. Clinical and Laboratory Data
Every subject was required to complete a questionnaire including information on demographic characteristics and medical history. After an overnight fast, they were examined in the morning by trained nurses. The concentrations of SUA, serum albumin, fasting plasma glucose, hemoglobin A1c (HbA1c), hemoglobin, serum creatinine (Scr), blood urea nitrogen (BUN), total cholesterol (TC), triglycerides (TGs), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and C-reactive protein (CRP) were measured by using a 717A automatic biochemical analyzer (Hitachi H7600). Urine creatinine (Ucr) and urine albumin (UALB) were measured through an automatic urine analyzer (Sysmex AX4280) and an automatic protein analyzer (Siemens BNII). The urinary albumin-to-creatinine ratio (U-ACR, mg/g) was calculated as UALB/Ucr. Body mass index (BMI) was defined as body weight (kilogram, kg) divided by the square of height (meter, m2). Blood pressures were measured by using a standard sphygmomanometer after the subjects rested for 15 minutes.
2.3. Diagnostic Criteria
HUA was defined as SUA>7 mg/dl in men and >6 mg/dl in women with a normal purine diet. All subjects were divided into quartiles based on their baseline SUA levels (Q1: <4.8; Q2: <5.7; Q3: <6.5; and Q4: ≥6.5 mg/dl). The estimated glomerular filtration rate (eGFR) (ml/min/1.73 m2) was calculated by the CKD-Epidemiology Collaboration (CKD-EPI) equation [15]. CKD was defined as renal dysfunction (eGFR<60 ml/min/1.73 m2) [16], and albuminuria was diagnosed if the urinalysis showed a urine dipstick of 1+ or greater, or U-ACR was >30 mg/g [17]. The changes in eGFR and SUA were calculated by the following equations: ∆eGFR = eGFR2018-eGFR2021 and ∆SUA= SUA2018-SUA2021. Hypertension was defined as a systolic or diastolic blood pressure ≥140 or ≥90 mmHg, respectively, or the current use of antihypertensive drugs [18]. Diabetes mellitus was defined as a fasting blood glucose level ≥7.0 mmol/l or using antidiabetic medication [19].
2.4. Statistical Analysis
All analyses were performed by SPSS v. 22. Continuous variables are reported as the means±standard deviations or interquartile ranges (IQRs), and categorical variables are reported as percentages. Continuous and categorical variables were compared by the T test and chi-square test, respectively. Statistical differences among the groups were compared with a one-way analysis of variance (ANOVA) or the Kruskal–Wallis test. In further analyses, multivariate logistic regression analysis was used to calculate odds ratios (ORs) between the baseline SUA level, changes in SUA levels, and CKD, after adjustment for confounding variables. Values with a P < 0.05 were used to define statistical significance.
3. Results
3.1. Baseline Characteristics
The prevalence of HUA was 24.24% in the total population, and the prevalence of HUA was higher in females than in males (27.86% vs. 20.98%, respectively; P < 0.001). Among all 425 subjects, the prevalence of diabetes, hypertension, and chronic cardiovascular disease was 36.24%, 80.47%, and 60.24%, respectively.
3.2. Levels of Baseline Variables in Each SUA Quartile
Subjects were divided into quartiles (Q1-Q4) by SUA levels at baseline, and the baseline characteristics are presented in Table 1. The mean values of age, BMI, TGs, blood urea nitrogen, serum creatinine, and the prevalence of CKD increased significantly with an increase in SUA levels (P < 0.05), while the mean values of baseline eGFR, follow-up eGFR, TC, and HDL-C decreased significantly (P < 0.05). Pearson's correlation coefficient showed that the baseline eGFR was inversely correlated with the SUA level at baseline (r = −0.371, P < 0.001).
Table 1.
Baseline characteristics of the participants according to the SUA quartiles at baseline.
| Characteristics | SUA quartiles | P for trend | |||
|---|---|---|---|---|---|
| Q1 (n = 105) | Q2 (n = 110) | Q3 (n = 104) | Q4 (n = 106) | ||
| Age (years) | 85.8 ± 4.1 | 86.7 ± 3.7 | 86.6 ± 4.0 | 87.5 ± 3.7 | 0.017∗ |
| Female (n, %) | 72 (68.6) | 52 (47.3) | 45 (43.3) | 32 (30.2) | <0.001∗ |
| SBP (mmHg) | 132.3 ± 12.3 | 130.1 ± 11.9 | 134.9 ± 13.7 | 133.6 ± 14.6 | 0.053 |
| DBP (mmHg) | 66.0 ± 8.3 | 66.3 ± 7.8 | 68.2 ± 7.9 | 68.4 ± 8.4 | 0.061 |
| BMI (kg/m2) | 23.3 ± 3.3 | 23.6 ± 3.1 | 25.0 ± 2.9 | 24.7 ± 3.6 | <0.001∗ |
| TC (mg/dl) | 4.6 ± 1.0 | 4.4 ± 0.9 | 4.4 ± 0.8 | 4.2 ± 1.0 | 0.018∗ |
| TGs (mg/dl) | 1.1 ± 0.4 | 1.1 ± 0.5 | 1.4 ± 0.8 | 1.3 ± 0.7 | <0.001∗ |
| HDL-C(mmol/l) | 1.5 ± 0.4 | 1.4 ± 0.4 | 1.3 ± 0.3 | 1.2 ± 0.3 | <0.001∗ |
| LDL-C (mmol/l) | 2.5 ± 0.8 | 2.3 ± 0.7 | 2.3 ± 0.7 | 2.3 ± 0.7 | 0.349 |
| Fasting plasma glucose (mmol/l) | 5.5 ± 1.4 | 5.5 ± 1.0 | 5.7 ± 1.5 | 5.5 ± 1.1 | 0.578 |
| HbA1c, % | 6.2 ± 1 | 6.1 ± 0.9 | 6.2 ± 0.8 | 6.2 ± 0.8 | 0.843 |
| Hemoglobin (g/l) | 127.1 ± 13.9 | 126.2 ± 14.2 | 126.9 ± 14.0 | 126.7 ± 15.9 | 0.972 |
| Albumin (g/l) | 40 ± 4.1 | 39.4 ± 3.9 | 40.2 ± 3.8 | 39.8 ± 4.2 | 0.546 |
| C-reactive protein (mg/l) | 1.4 (0.7,3.1) | 1.4 (0.8,3.0) | 2.0 (0.9,3.2) | 1.8 (1.0,2.9) | 0.14 |
| Blood urea nitrogen (mmol/l) | 6.3 ± 1.7 | 6.8 ± 1.7 | 7.1 ± 1.7 | 8.3 ± 2.5 | <0.001∗ |
| Serum creatinine (umol/l) | 84.2 ± 17.2 | 93.3 ± 21.2 | 98.3 ± 19.8 | 109.5 ± 20.6 | <0.001∗ |
| Albuminuria (n, %) | 3 (2.86) | 6 (5.45) | 9 (8.65) | 8 (7.55) | 0.312 |
| Baseline SUA (mg/dl) | 4.0 ± 0.5 | 5.2 ± 0.3 | 6.1 ± 0.3 | 7.5 ± 0.8 | <0.001∗ |
| Follow-up SUA (mg/dl) | 4.6 ± 1.2 | 5.4 ± 1.0 | 5.5 ± 1.3 | 6.4 ± 1.9 | <0.001∗ |
| Baseline eGFR (ml/min/1.73 m2) | 61.5 ± 11.6 | 57.9 ± 12.2 | 54.8 ± 11.2 | 49.7 ± 11.2 | <0.001∗ |
| Follow-up eGFR (ml/min/1.73 m2) | 55.7 ± 11.9 | 53.2 ± 11.9 | 50.8 ± 12.0 | 47.2 ± 13.6 | <0.001∗ |
| CKD (n, %) | 44 (41.90) | 60 (54.55) | 71 (68.27) | 82 (77.36) | <0.001∗ |
| Hypertension (n, %) | 84 (80) | 86 (78.2) | 83 (79.8) | 89 (84.0) | 0.745 |
| Chronic cardiovascular disease (n, %) | 63 (60) | 66 (60) | 62 (59.6) | 65 (61.3) | 0.995 |
| Diabetes (n, %) | 33 (31.4) | 43 (39.1) | 34 (32.7) | 44 (41.5) | 0.351 |
| Alcohol intake (n, %) | 7 (6.7) | 3 (2.7) | 5 (4.8) | 7 (6.6) | 0.515 |
| Current smoke (n, %) | 3 (2.86) | 0 (0.00) | 4 (3.85) | 2 (1.89) | 0.153 |
| ACEI/ARB usage (n, %) | 40 (38.1) | 31 (28.2) | 43 (41.3) | 55 (51.9) | 0.005∗ |
Note. Systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), triglycerides (TGs), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), hemoglobin A1c (HbA1c), serum uric acid (SUA), estimated glomerular filtration rate (eGFR), chronic kidney disease (CKD), angiotensin-converting enzyme inhibitors/angiotensin receptor blocker (ACEI/ARB).
3.3. Multivariate Regression Analysis of the Association between Baseline SUA, eGFR, and CKD
In Model 1, the OR for the progression of CKD increased as the quartiles for baseline SUA levels increased from the first to fourth quartiles (1.00 vs. 1.72, 3.29, and 5.4, respectively; P for linear trend<0.001) (Table 2). In Model 3, this association remained unchanged after adjusting for potential risk factors (age, sex, BMI, TC, TGs, HDL-C, diabetes, hypertension, chronic cardiovascular disease, ACEI/ARB usage). At the same time, the ORs for hyperuricemia and per 1 mg/dl increase in baseline SUA levels for the development of CKD were 3.68 (95% CI: 2.03–6.66) and 1.76 (95% CI: 1.45–2.14), respectively. In the multivariable linear regression analysis adjusted for the above confounders, the baseline SUA levels were inversely correlated with the baseline eGFR (B = -3.58, SE 0.43, P < 0.001).
Table 2.
Logistic regression analysis of baseline SUA levels and the development of CKD.
| SUA quartiles | Odds ratio (95% confidence interval) | |||
|---|---|---|---|---|
| Unadjusted | Model 1 | Model 2 | Model 3 | |
| Q1 (<4.8 md/dl) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Q2 (<5.7 mg/d) | 1.72 (1.00–2.96) | 1.93 (1.09–3.40) | 1.82 (1.02–3.25) | 1.79 (1.00–3.22) |
| Q3 (<6.5 mg/dl) | 3.29 (1.85–5.84) | 3.96 (2.13–7.35) | 3.53 (1.87–6.67) | 3.40 (1.79–6.47) |
| Q4 (≥6.5 mg/dl) | 5.4 (2.92–9.98) | 6.76 (3.44–13.25) | 6.43 (3.21–12.87) | 6.79 (3.45–13.75) |
| P for linear trend | <0.001∗ | <0.001∗ | <0.001∗ | <0.001∗ |
| SUA (per 1 mg/dl increase) | 1.66 (1.40–1.96) | 1.78 (1.47–2.15) | 1.74 (1.43–2.11) | 1.76 (1.45–2.14) |
| Normal SUA | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Hyperuricemia | 3.68 (2.11–6.40) | 3.58 (2.03–6.31) | 3.41 (1.91–6.09) | 3.68 (2.03–6.66) |
Model 1 was adjusted for age, sex, and BMI. Model 2 was adjusted for Model 1, TGs, TC, HDL. Model 3 was adjusted for Model 2, diabetes, hypertension, chronic cardiovascular disease, ACEI/ARB usage.
3.4. Interactive Association of eGFR2018, eGFR2021, ∆eGFR, and ∆SUA
We performed linear regression analyses to investigate the relationship of changes in SUA levels with declines in eGFR. Figure 1 shows a significantly negative association between changes in SUA levels and eGFR in both males (r = −0.187, P < 0.01) and females (r = −0.318, P < 0.001). After adjusting for confounding factors (sex, age, BMI, TC, TGs, HDL-C, baseline eGFR, diabetes, hypertension, chronic cardiovascular disease, and ACEI/ARB usage), we found that a 1 mg/dl increase in the SUA level over 3 years was connected with an additional 1.25 ml/min/1.73 m2 decline in eGFR (Table 3).
Figure 1.
Correlations between changes in SUA levels from 2018 to 2021 and changes in eGFR during the same period in females and males. ∆eGFR = eGFR2018-eGFR2021; ∆SUA= SUA2018-SUA2021.
Table 3.
Linear regression of ∆SUA and ∆eGFR.
| B | SE | SE β | 95% CI | t | P | |
|---|---|---|---|---|---|---|
| Model 1 | −1.58 | 0.30 | −0.25 | −2.17∼ −0.99 | −5.26 | <0.001 |
| Model 2 | −1.25 | 0.30 | −0.20 | −1.83∼ −0.67 | −4.23 | <0.001 |
Note. eGFR: estimated glomerular filtration rate, SE: standard error, CI: confidence interval. Model 1 was adjusted for age, sex, and BMI. Model 2 was adjusted for model 1 plus TGs, TC, HDL, baseline eGFR, diabetes, hypertension, chronic cardiovascular disease, and ACEI/ARB usage.
4. Discussion
We demonstrated that elevated baseline SUA levels and changes in SUA levels were associated with a decline in eGFR and an increased risk of CKD among elderly Chinese individuals after multivariable adjustment, and this association was even observed in the normal range of SUA. In addition, there were sex differences in uric acid levels: women had a higher prevalence of HUA and a stronger inverse correlation in the relationship between the changes in SUA levels and eGFR than men.
In our study, participants in the fourth SUA quartile were 6.79 times more likely to develop CKD than those in the first quartile, and a per unit increase in the baseline SUA level indicated an OR of 1.76 (95% CI, 1.45–2.14) for renal failure. In addition, the OR for CKD significantly increased with baseline SUA levels, even within the normal range (Q2∼Q3, <6.5 mg/dl). This indicated that a mild elevation within the normal range of SUA might be a risk factor for renal dysfunction. Our findings were in accordance with those of previous studies [6,12–14,20]. In a study containing 4,546 volunteers with a 4-year follow-up, Wu N et al. determined that the OR for incident kidney disease increased to 2.73 (95% CI, 1.65–4.50) for individuals in the fourth SUA quartile (>5.1 mg/dl) compared to those in the first quartile [14]. Storhaug et al. found that a 1 mg/dl increase in the baseline SUA level was associated with 1.16-fold odds of renal dysfunction after a 13-year follow-up (95% CI, 1.04–1.29) [20]. To our knowledge, the effect value in our study was greater than those in the above experiments [12–14]. The possible reasons for this were age heterogeneity and age-related comorbidities [4], which might interact with uric acid to strengthen the link.
In the analysis of the longitudinal data, we observed that changes in SUA levels were inversely correlated with changes in eGFR, and a 1 mg/dl increase in the SUA level was associated with an additional 1.25 ml/min/1.73 m2 decrease in eGFR during the 3-year follow-up after adjusting for possible factors. Consistently, Ye M et al. revealed that the time-mean SUA could increase the risk of developing CKD by 6.32-fold [21]. A retrospective study reported a similar result that an increased SUA level indicated a higher risk of deterioration in kidney function, with an adjusted OR of 1.639, while a decreased SUA level helped to slow the deterioration of renal function [22]. In addition to the baseline SUA levels, longitudinal SUA changes were also positively associated with the risk of CKD among middle-aged and elderly Chinese [14]. Additionally, many trials have demonstrated that urate-lowering therapy can delay the progression of renal insufficiency [10]. Thus, when we evaluated the effect of SUA on renal failure at follow-up, we should have taken the longitudinal SUA change into account at the same time, not just the baseline SUA level or a one-time measurement.
Furthermore, we found that sex differences might play an important role in the association. Musacchio E et al. revealed that age-dependent UA increases were markedly different in males and females, with the latter showing a steeper trend [23]. In a previous study involving community-dwelling elderly individuals in China, Yang et al. found that women had a higher prevalence of HUA in the age subgroup older than 70 years, which was similar to our results [24]. In our study, women also showed a stronger negative correlation between changes in the uric acid level and eGFR. As we analyzed an elderly population including postmenopausal women, estrogenic hormones that enhance renal urate excretion might be, at least in part, the reason for the discrepancy [25, 26].
However, the link between uric acid and kidney failure remains controversial. In a study by Chang YH et al., uric acid played a pathogenic role only when the value exceeded 6.3 mg/dl, and a lower uric acid level might be beneficial to the improvement of renal function in participants with diabetic nephropathy [27]. Based on a Japanese general population containing 5507 participants, Tada K et al. reported that there was no statistically significant correlation between SUA levels and the progression of CKD [28]. Srivastava A et al. compared the relationship in different CKD stages and found a potentially protective effect between higher UA levels and renal dysfunction in participants with CKD stage 4 or 5 [9]. The conflicting results for the association might be due to differences in study design, including recruited subjects, the calculation of eGFR, the duration of follow-up, and the definitions of outcomes.
A series of experimental studies proposed several possible underlying mechanisms [29–32]: (1) UA crystals may cause direct kidney toxicity by depositing within the kidney; (2) elevated uric acid might induce intrarenal oxidative stress and mitochondrial dysfunction, leading to damage to endothelial cells, smooth muscle cells, kidney tubular cells, and activation of the renin-angiotensin system; and (3) SUA might be a risk factor for metabolic syndrome, diabetes, and hypertension, which could accelerate the development of CKD [32]. Eventually, hyperuricemia might cause glomerular and renal tubulointerstitial injury, leading to a decline in eGFR and albuminuria [33]. However, because of the small sample size and the particularity of the population, we could not clarify the association between uric acid levels and albuminuria.
As a retrospective cohort study, the present study had several limitations. First, the small sample size and the retrospective nature of the study may weaken the potential causality between SUA levels and CKD. Second, we could not eliminate the possible effects of medication that affected uric acid metabolism on the present findings. Third, we had no information about the family history of kidney disease or underlying kidney disease, which should be obtained by renal biopsy and ultrasonography. Finally, the conclusions of this study are not applicable in other ethnic populations because of the sample's demographics.
5. Conclusion
This study demonstrated that elevated baseline SUA levels and changes in SUA levels were associated with increased odds of CKD and declining eGFR among elderly Chinese individuals after adjusting for possible confounding factors. Early and appropriate management of SUA levels might slow the development of future declines in eGFR, but we need further large-scale prospective trials to elucidate this issue.
Acknowledgments
The authors would like to thank all study subjects for participating in the present study as well as all volunteers for assisting in collecting the samples and data. This work was funded and supported by the Clinical Research Application Program of Zhejiang Province (Grant number: 2022505395).
Data Availability
The datasets used and/or analyzed in this study are available from the corresponding author on reasonable request.
Ethical Approval
This study protocol was approved by the Ethics Committee of Zhejiang Provincial People's Hospital (2020QT179).
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Authors' Contributions
All authors conceived and designed the experiments. Bo Gao and Xiuxiu Lai planned and coordinated the study and designed the protocol. Xiuxiu Lai, Qingyan Zhu, Yan Zhu, and Gongmin Zhou acquired and analyzed the data. Xiuxiu Lai and Haijia Lai performed the statistical analysis. All authors contributed to the interpretation of results and act as guarantors for the integrity of the data and the accuracy of the data analysis. All authors reviewed the manuscript.
References
- 1.Yang C., Gao B., Zhao X., et al. Executive summary for China kidney disease network (CK-net) 2016 annual data report. Kidney International . 2020;98(6):1419–1423. doi: 10.1016/j.kint.2020.09.003. [DOI] [PubMed] [Google Scholar]
- 2.Aucella F., Corsonello A., Leosco D., Brunori G., Gesualdo L., Antonelli-Incalzi R. Beyond chronic kidney disease: the diagnosis of Renal Disease in the Elderly as an unmet need. A position paper endorsed by Italian Society of Nephrology (SIN) and Italian Society of Geriatrics and Gerontology (SIGG) Journal of Nephrology . 2019;32(2):165–176. doi: 10.1007/s40620-019-00584-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Perkowska-Ptasinska A., Deborska-Materkowska D., Durlik M. The current management of kidney disease in the elderly. Minerva Med . 2018;109(1):41–52. doi: 10.23736/S0026-4806.17.05351-4. [DOI] [PubMed] [Google Scholar]
- 4.Maiuolo J., Oppedisano F., Gratteri S., Muscoli C., Mollace V. Regulation of uric acid metabolism and excretion. International Journal of Cardiology . 2016;213:8–14. doi: 10.1016/j.ijcard.2015.08.109. [DOI] [PubMed] [Google Scholar]
- 5.Li L., Yang C., Zhao Y., Zeng X., Liu F., Fu P. Is hyperuricemia an independent risk factor for new-onset chronic kidney disease?: a systematic review and meta-analysis based on observational cohort studies. BMC Nephrology . 2014;15(1):p. 122. doi: 10.1186/1471-2369-15-122. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Kamei K., Konta T., Hirayama A., et al. A slight increase within the normal range of serum uric acid and the decline in renal function: associations in a community-based population. Nephrology Dialysis Transplantation . 2014;29(12):2286–2292. doi: 10.1093/ndt/gfu256. [DOI] [PubMed] [Google Scholar]
- 7.Cao X., Wu L., Chen Z. The association between elevated serum uric acid level and an increased risk of renal function decline in a health checkup cohort in China. International Urology and Nephrology . 2018;50(3):517–525. doi: 10.1007/s11255-017-1732-6. [DOI] [PubMed] [Google Scholar]
- 8.Johnson R. J., Bakris G. L., Borghi C., et al. Hyperuricemia, acute and chronic kidney disease, hypertension, and cardiovascular disease: report of a scientific workshop organized by the national kidney foundation. American Journal of Kidney Diseases . 2018;71(6):851–865. doi: 10.1053/j.ajkd.2017.12.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Srivastava A., Kaze A. D., McMullan C. J., Isakova T., Waikar S. S. Uric acid and the risks of kidney failure and death in individuals with CKD. American Journal of Kidney Diseases . 2018;71(3):362–370. doi: 10.1053/j.ajkd.2017.08.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Liu X., Zhai T., Ma R., Luo C., Wang H., Liu L. Effects of uric acid-lowering therapy on the progression of chronic kidney disease: a systematic review and meta-analysis. Renal Failure . 2018;40(1):289–297. doi: 10.1080/0886022x.2018.1456463. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Nacak H., van Diepen M., Qureshi A. R., et al. Uric acid is not associated with decline in renal function or time to renal replacement therapy initiation in a referred cohort of patients with Stage III, IV and V chronic kidney disease. Nephrology Dialysis Transplantation . 2015;30(12):2039–2045. doi: 10.1093/ndt/gfv225. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Zhang L., Wang F., Wang X., Liu L., Wang H. The association between plasma uric acid and renal function decline in a Chinese population-based cohort. Nephrology Dialysis Transplantation . 2011;27(5):1836–1839. doi: 10.1093/ndt/gfr597. [DOI] [PubMed] [Google Scholar]
- 13.Wang S., Shu Z., Tao Q., Yu C., Zhan S., Li L. Uric acid and incident chronic kidney disease in a large health check-up population in Taiwan. Nephrology . 2011;16(8):767–776. doi: 10.1111/j.1440-1797.2011.01513.x. [DOI] [PubMed] [Google Scholar]
- 14.Wu N., Xia J., Chen S., et al. Serum uric acid and risk of incident chronic kidney disease: a national cohort study and updated meta-analysis. Nutrition & Metabolism . 2021;18(1):p. 94. doi: 10.1186/s12986-021-00618-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Meeusen J. W., Kasozi R. N., Larson T. S., Lieske J. C. Clinical impact of the refit CKD-EPI 2021 creatinine-based eGFR equation. Clinical Chemistry . 2022;17:p. 282. doi: 10.1093/clinchem/hvab282. [DOI] [PubMed] [Google Scholar]
- 16.Kidney Disease Improving Global Outcomes. KDIGO 2017 clinical practice guideline update for the diagnosis, evaluation, prevention, and treatment of chronic kidney disease-mineral and bone disorder (CKD-MBD) Kidney International Supplements . 2017;7(1):1–59. doi: 10.1016/j.kisu.2017.04.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Stevens P. E., Levin A. Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Annals of Internal Medicine . 2013;158(11):825–830. doi: 10.7326/0003-4819-158-11-201306040-00007. [DOI] [PubMed] [Google Scholar]
- 18.Williams B., Mancia G., Spiering W. ESC/ESH Guidelines for the management of arterial hypertension. European Heart Journal . 2018;39(33):3021–3104. doi: 10.1093/eurheartj/ehy439. [DOI] [PubMed] [Google Scholar]
- 19.American Diabetes Association. Classification and diagnosis of diabetes: standards of medical care in diabetes-2018. Diabetes Care . 2018;41:S13–S27. doi: 10.2337/dc18-S002. [DOI] [PubMed] [Google Scholar]
- 20.Storhaug H. M., Toft I., Norvik J. V., et al. Uric acid is associated with microalbuminuria and decreased glomerular filtration rate in the general population during 7 and 13 years of follow-up: the Tromsø Study. BMC Nephrology . 2015;16(1):p. 210. doi: 10.1186/s12882-015-0207-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Ye M., Hu K., Jin J., Wu D., Hu P., He Q. The association between time-mean serum uric acid levels and the incidence of chronic kidney disease in the general population: a retrospective study. BMC Nephrology . 2018;19(1):p. 190. doi: 10.1186/s12882-018-0982-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Lin F., Zhang H., Huang F., Chen H., Lin C., Zhu P. Influence of changes in serum uric acid levels on renal function in elderly patients with hypertension: a retrospective cohort study with 3.5-year follow-up. BMC Geriatrics . 2016;16(1):p. 35. doi: 10.1186/s12877-016-0209-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Musacchio E., Perissinotto E., Sartori L. Veronese N., Punzi L., Zambon S., et al. Hyperuricemia, cardiovascular profile, and comorbidity in older men and women: the pro.V.A. Study. Rejuvenation Research . 2017;20(1):42–49. doi: 10.1089/rej.2016.1834. [DOI] [PubMed] [Google Scholar]
- 24.Yang Y., Zhou W., Wang Y., Zhou R. Gender-specific association between uric acid level and chronic kidney disease in the elderly health checkup population in China. Renal Failure . 2019;41(1):197–203. doi: 10.1080/0886022x.2019.1591994. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Halperin Kuhns V. L., Woodward O. M. Sex differences in urate handling. International Journal of Molecular Sciences . 2020;21(12):p. 4269. doi: 10.3390/ijms21124269. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Mumford S. L., Dasharathy S. S., Pollack A. Z., et al. Serum uric acid in relation to endogenous reproductive hormones during the menstrual cycle: findings from the BioCycle study. Human Reproduction . 2013;28(7):1853–1862. doi: 10.1093/humrep/det085. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Chang Y.-H., Lei C.-C., Lin K.-C., Chang D.-M., Hsieh C.-H., Lee Y.-J. Serum uric acid level as an indicator for CKD regression and progression in patients with type 2 diabetes mellitus-a 4.6-year cohort study. Diabetes . 2016;32(6):557–564. doi: 10.1002/dmrr.2768. [DOI] [PubMed] [Google Scholar]
- 28.Tada K., Maeda T., Takahashi K., et al. Association between serum uric acid and new onset and progression of chronic kidney disease in a Japanese general population: iki epidemiological study of atherosclerosis and chronic kidney disease. Clinical and Experimental Nephrology . 2021;25(7):751–759. doi: 10.1007/s10157-021-02042-7. [DOI] [PubMed] [Google Scholar]
- 29.Sánchez-Lozada L. G, Soto V., Tapia E. Role of oxidative stress in the renal abnormalities induced by experimental hyperuricemia. American Journal of Physiology - Renal Physiology . 2008;295(4):F1134–F1141. doi: 10.1152/ajprenal.00104.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Sanchez-Lozada L. G., Rodriguez-Iturbe B., Kelley E. E., et al. Uric acid and hypertension: an update with recommendations. American Journal of Hypertension . 2020;33(7):583–594. doi: 10.1093/ajh/hpaa044. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Sánchez-Lozada L. G., Lanaspa M. A., Cristóbal-García M., et al. Uric acid-induced endothelial dysfunction is associated with mitochondrial alterations and decreased intracellular ATP concentrations. Nephron Experimental Nephrology . 2012;121(3-4):e71–e78. doi: 10.1159/000345509. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Chen T. K., Knicely D. H., Grams M. E. Chronic kidney disease diagnosis and management. JAMA . 2019;322(13):1294–1304. doi: 10.1001/jama.2019.14745. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Russo E., Viazzi F., Pontremoli R., et al. Association of uric acid with kidney function and albuminuria: the Uric Acid Right for heArt Health (URRAH) Project. Journal of Nephrology . 2022;35(1):211–221. doi: 10.1007/s40620-021-00985-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed in this study are available from the corresponding author on reasonable request.