Abstract
Background
Serum uric acid to serum creatinine ratio (SUA/Scr) has emerged as a new biomarker, which is significantly associated with several metabolic diseases. However, no study has investigated the association between SUA/Scr and mortality among patients on continuous ambulatory peritoneal dialysis (CAPD).
Methods
In this multicenter retrospective cohort study, we enrolled CAPD patients in eight tertiary hospitals in China from 1 January 2005 to 31 May 2021. Cox proportional hazard models were used to determine the relationship between SUA/Scr and mortality.
Results
A total of 2480 patients were included; the mean age was 48.9 ± 13.9 years and 56.2% were males. During 12648.0 person-years of follow-up, 527 (21.3%) patients died, of which 267 (50.7%) deaths were caused by cardiovascular disease. After multivariable adjustment for covariates, per unit increase in SUA/Scr was associated with a 62.9% (HR, 1.629 (95% confidence interval (CI) 1.420–1.867)) and 73.0% (HR, 1.730 (95% CI 1.467–2.041)) higher risk of all-cause and cardiovascular mortality. Results were similar when categorized individuals by SUA/Scr quartiles. Compared with the lowest quartile of SUA/Scr, the highest and the second highest quartile of SUA/Scr had a 2.361-fold (95% CI 1.810–3.080) and 1.325-fold (95% CI 1.003–1.749) higher risk of all-cause mortality, as well as a 3.701-fold (95% CI 2.496–5.489) and 2.074-fold (95% CI 1.387–3.100) higher risk of cardiovascular mortality. Multivariable-adjusted spline regression models showed nonlinear association of SUA/Scr with mortality in CAPD patients.
Conclusions
Higher levels of SUA/Scr were associated with higher risk of all-cause and cardiovascular mortality in CAPD patients.
Keywords: Continuous ambulatory peritoneal dialysis, serum uric acid, serum creatinine, all-cause mortality, cardiovascular mortality
Introduction
Peritoneal dialysis (PD) is a recognized substitute treatment for individuals with end-stage renal failure. The number of PD patients reported by the Chinese National Renal Data System in 2017 was 86,264 and increasing annually [1]. Although PD treatment improved significantly in recent decades, patients with PD treatment have high mortality. According to a 2017 study of the global epidemiology of PD, the 5-year patient survival ranged from 48.4% to 64% [2]. Cardiovascular disease (CVD), which accounts for 52.7% of all deaths, is the leading cause of mortality among PD patients [3,4]. Therefore, identifying predictors of mortality in dialysis patients remains an important research area.
Serum uric acid (SUA) is a purine metabolic byproduct produced by the breakdown of either dietary or endogenous purines. For decades, the potential causal association between SUA and the risk of CVD or death has been a focus of clinical and academic concern [5]. It has been reported that increased SUA levels are independently and significantly associated with risk of cardiovascular mortality [6]. However, there are contradicting data, it has been reported that high SUA levels may prevent the occurrence of certain diseases such as Parkinson or lower SUA levels associated with an increased risk of mortality [7–9]. This disparity possibly since endogenous SUA concentration is predominantly determined by renal clearance function. Therefore, a novel biomarker known as the SUA to serum creatinine ratio (SUA/Scr) has arisen and is regarded as a better predictor of net SUA production. According to various research, SUA/Scr is strongly linked to several metabolic diseases, such as metabolic syndrome [10], chronic renal disease [11] and β-cell function [12] in diabetics, and fatty liver disease in healthy individuals [13,14]. These unfavorable effects are all recognized CVD risk factors and may be involved in the pathophysiology of the disease.
However, research on the influence of SUA/Scr on all-cause and cardiovascular mortality is limited, and no study has been conducted to evaluate the association between SUA/Scr and the risk of death in PD patients. Thus, we sought to examine the connection between SUA/Scr with all-cause and cardiovascular mortality in continuous ambulatory peritoneal dialysis (CAPD) patients in the present study.
Methods
Study design and participants
This was a retrospective cohort study of patients for whom CAPD was the initial and sole renal replacement therapy from eight tertiary hospitals in China between 1 January 2005 and 31 May 2021. Patients under 18 years old, with less than 3 months of follow-up, with preexisting CVD, with history of gout, with uric acid lowering drugs, missing baseline SUA, Scr, or other baseline covariates were excluded. The previous medical history was collected by trained staff using a standard questionnaire, and it was defined as self-reported history of physician-diagnosed. The history of CVD included coronary heart disease, stroke, and peripheral arterial disease. Ethical approval mandatory for this study was obtained from Ethics Committee at Dongguan Tungwah Hospital (2021-KY-021). Informed consent was obtained from all individual participants included in the study.
Measurement of SUA/Scr levels
Fasting blood samples were obtained the next morning in the laboratory division of each tertiary hospital following an overnight fast of 8–12 h. As per the manufacturer’s recommendations, SUA and Scr concentrations were measured using a commercial kit (Roche Diagnostics (Shanghai) Ltd, Shanghai, China), and an automated biochemical analyzer (Roche Cobas c501, Mannheim, Germany). The ratio of SUA/Scr was obtained by dividing the SUA concentration (mmol/L) by the Scr concentration (mmol/L).
Assessment of outcomes
The primary and secondary endpoints of this study were defined as cardiovascular and all-cause mortality, respectively. Based on the admission medical information, we established the reasons for death. If patients died outside of hospitals, we identified the cause of death by questioning family members over the phone to confirm the circumstances of the death, supplemented with information from PD center medical records. Death from sudden cardiac death, heart failure, hemorrhagic or thromboembolic stroke, malignant arrhythmia, or acute myocardial ischemia were all considered to be cardiovascular mortality, which was based on the International Classification of Diseases Clinical Modification, 9th Revision and was confirmed by cardiologists.
Participants in the study contributed follow-up time between the time of enrollment and the date of their death, transferring to hemodialysis (HD), receiving kidney transplantation, loss to follow-up, transferring to another dialysis facility, or administrative censoring at the end of follow-up (31 December 2022), whichever occurred first.
Assessment of covariates
Baseline demographic and clinical features were collected at the time of enrollment, which was defined as one month before the patients first received CAPD treatment, including age, gender, body mass index (BMI), comorbidities, and medical use. The biochemical indicators tested at the time of enrollment included hemoglobin, serum albumin, high-sensitivity C-reactive protein (hs-CRP), cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). The estimated glomerular filtration rate (eGFR) was obtained for Chinese patients using a modified modification of diet in renal disease equation at the time of enrollment. That is eGFR (mL/min/1.73 m2) = 175 × Scr (mg/dL)−1.234 × age−0.179 × 0.79 (if female) [15]. The diagnosis of hypertension and diabetes mellitus (DM) was made according to the latest local guidelines [16,17].
Statistical analysis
Subjects were divided into four groups based on the quartiles of SUA/Scr: ≤0.39, 0.40–0.53, 0.54–0.71, and ≥0.72. Kruskal–Wallis h test and χ2 test were used to compare the differences in characteristics between four SUA/Scr ratio categories. Bonferroni’s correction was further performed for multiple comparisons to correct the type I error.
Survival curves were estimated using the Kaplan–Meier method and compared by the log-rank test. The associations between SUA/Scr and mortality were evaluated using the Cox proportional hazard model. The analysis was performed considering four models: model 1: unadjusted; model 2: adjusted for age, gender, BMI, DM, hypertension, CAPD centers, and the protopathy; model 3: adjusted for model 2 + hemoglobin, serum albumin, cholesterol, triglycerides, LDL-C, HDL-C, and hs-CRP; model 4: adjusted for model 3 + medicine use (including CCB, α-blocker, β-blocker, ACEI/ARB, diuretic, statin, and aspirin). The hazard ratio (HR) and 95% confidence interval (CI) of incident cardiovascular and all-cause mortality per standard deviation (SD) increase in SUA/Scr were calculated using a multivariable Cox proportional hazard model where SUA/Scr was regarded as a continuous variable. A Cox proportional hazard regression with cubic spline functions model and smooth curve fitting (penalized spline method) were conducted to address the nonlinearity of SUA/Scr and mortality in CAPD patients. Receiver operating characteristic (ROC) analysis was used to assess the value of SUA/Scr for predicting mortality in CAPD patients.
To validate the robustness of our results, sensitivity analyses were performed. First, we performed sensitivity analyses by using the competing risk model of Fine and Gray by considering transferred to HD, underwent kidney transplants, transferred to other dialysis facilities, and lost to follow-up as competing events for all-cause mortality. Besides, non-cardiovascular mortality, transferred to HD, underwent kidney transplants, transferred to other dialysis facilities, and lost to follow-up considered as competing events for cardiovascular mortality (model 5). Second, we further performed sensitivity analyses by excluding individuals less than 2 years follow-up (model 6) and those with diuretic or statin therapy (which may influence SUA levels, model 7) at baseline, respectively, to assess the robustness of our findings. Subgroup analysis was performed according to age (<60 or ≥60 years), gender (male or female), hypertension (yes or no), DM (yes or no), BMI (<24 or ≥24 kg/m2), serum albumin (<36 or ≥36 g/L), hs-CRP (≤2.0 or >2.0 mg/L), and the protopathy, including chronic glomerulonephritis (yes or no), diabetic nephropathy (yes or no), and hypertensive nephropathy (yes or no), and tested for potential interactions of these covariates with SUA/Scr separately. SPSS software (SPSS Inc., Chicago, IL) was utilized for all analyses. Statistical significance was defined as a two-sided p value <.05.
Results
Demographic and clinical characteristics of CAPD patients
A total of 4128 incident CAPD patients were included, from which 61 (1.5%) patients under the age of 18 years, 114 (2.8%) patients on CAPD for less than 3 months, 965 (23.4%) with a history of CVD, 267 (6.5%) without a baseline SUA/Scr ratio, 150 (3.6%) without other baseline covariates, 3 (0.1%) with a history of gout, and 88 (2.1%) with uric acid lowering drugs were excluded. As a result, a total of 2480 patients were included in the final primary analysis (Figure 1). Of the 2480 subjects, the mean age was 48.9 ± 13.9 years and 56.2% were male, 87.3% had hypertension, and 17.2% had diabetes. The main causes of ESRD were chronic glomerulonephritis (1480, 60.0%), diabetic nephropathy (330, 13.3%), hypertension nephropathy (304, 12.3%), and other reasons (167, 6.7%), while there were 192 (7.7%) patients with unknown causes (Table 1).
Figure 1.
Flow diagram of CAPD patients included CAPD: continuous ambulatory peritoneal dialysis; CVD: cardiovascular disease; HD: hemodialysis.
Table 1.
Baseline characteristics of CAPD patients according to quartiles of SUA/Scr.
| Characteristics | Overall (n = 2480) | Q1 (≤0.59) (n = 620) | Q2 (0.60–0.79) (n = 620) | Q3 (0.80–1.04) (n = 620) | Q4 (≥1.05) (n = 620) | p |
|---|---|---|---|---|---|---|
| SUA/Scr | 0.79 (0.59, 1.04) | 0.49 (0.41, 0.54) | 0.69 (0.64, 0.74) | 0.90 (0.85, 0.97) | 1.30 (1.14, 1.54) | <.001 |
| Age, years | 48.9 ± 13.9 | 43.7 ± 13.1 | 48.6 ± 12.8* | 49.9 ± 13.9* | 53.3 ± 14.2*,#,& | <.001 |
| Male, n (%) | 1393 (56.2) | 384 (61.9) | 345 (55.6) | 327 (52.7)* | 337 (54.4)* | .007 |
| BMI, kg/m2 | 22.2 ± 3.3 | 22.3 ± 3.2 | 22.2 ± 3.2 | 22.2 ± 3.4 | 22.0 ± 3.4 | .725 |
| SBP, mmHg | 145 ± 24 | 147 ± 22 | 145 ± 23 | 143 ± 26 | 145 ± 24 | .061 |
| DBP, mmHg | 87 ± 15 | 88 ± 15 | 87 ± 15 | 86 ± 15* | 85 ± 15* | .001 |
| Hypertension, n (%) | 2166 (87.3) | 553 (89.2) | 540 (87.1) | 533 (86.0) | 540 (87.1) | .384 |
| DM, n (%) | 426 (17.2) | 79 (12.7) | 75 (12.1) | 107 (17.3) | 165 (26.6)*,#,& | <.001 |
| Protopathy, n (%) | <.001 | |||||
| Chronic glomerulonephritis | 1480 (60.0) | 386 (62.3) | 386 (62.3) | 375 (60.5) | 340 (54.8) | |
| Diabetic nephropathy | 330 (13.3) | 46 (7.4) | 65 (10.5) | 88 (14.2) | 131 (21.1) | |
| Hypertensive nephropathy | 304 (12.3) | 83 (13.4) | 64 (10.3) | 68 (11.0) | 89 (14.4) | |
| Others | 167 (6.7) | 33 (5.3) | 42 (6.8) | 46 (7.4) | 46 (7.4) | |
| Unknown cause | 192 (7.7) | 72 (11.6) | 63 (10.2) | 43 (6.9) | 14 (2.3) | |
| Cholesterol, mmol/L | 4.54 ± 1.34 | 4.50 ± 1.32 | 4.38 ± 1.27 | 4.62 ± 1.35# | 4.65 ± 1.41# | .001 |
| Triglycerides, mmol/L | 1.61 ± 1.24 | 1.42 ± 1.26 | 1.54 ± 1.09 | 1.70 ± 1.16* | 1.79 ± 1.39*,# | <.001 |
| LDL-C, mmol/L | 2.67 ± 0.99 | 2.69 ± 0.95 | 2.56 ± 0.94 | 2.68 ± 0.99 | 2.74 ± 1.08# | .011 |
| HDL-C, mmol/L | 1.18 ± 0.44 | 1.21 ± 0.45 | 1.16 ± 0.45 | 1.16 ± 0.41 | 1.19 ± 0.46 | .149 |
| Hemoglobin, g/L | 92 ± 23 | 90 ± 22 | 92 ± 22 | 93 ± 23 | 95 ± 23* | .003 |
| Serum albumin, g/L | 35.4 ± 5.5 | 35.6 ± 5.4 | 35.6 ± 5.3 | 35.7 ± 5.5 | 34.9 ± 5.9 | .033 |
| hs-CRP, mg/L | 3.3 (1.3, 9.9) | 3.2 (1.0, 9.1) | 3.3 (1.2, 10.0) | 3.3 (1.5, 9.2) | 3.6 (1.5, 11.7)*,#,& | .002 |
| eGFR, mL/min/1.73 m2 | 5.3 (4.0, 7.3) | 3.5 (2.9, 4.6) | 4.7 (3.8, 5.9)* | 5.9 (4.9, 7.2) | 8.3 (6.6, 10.9)*,#,& | <.001 |
| Scr, mg/dL | 9.4 ± 3.6 | 13.0 ± 3.6 | 10.1 ± 2.6* | 8.4 ± 2.1*,# | 6.3 ± 2.0*,#,& | <.001 |
| SUA, mg/dL | 7.3 ± 2.1 | 6.0 ± 1.7 | 6.9 ± 1.7* | 7.6 ± 1.9*,# | 8.5 ± 2.4*,#,& | <.001 |
| Medicine use | ||||||
| CCB, n (%) | 1824 (73.5) | 469 (75.6) | 461 (74.4) | 447 (72.1) | 447 (72.1) | .399 |
| α-Blocker, n (%) | 620 (25.0) | 196 (31.6) | 188 (30.3) | 125 (20.2)*,# | 111 (17.9)*,# | <.001 |
| β-Blocker, n (%) | 1032 (41.6) | 298 (48.1) | 275(44.4) | 233 (37.6)* | 226 (36.5)*,# | <.001 |
| ACEI/ARB, n (%) | 919 (37.1) | 249 (40.2) | 231 (37.3) | 227 (36.6) | 212 (34.2) | .187 |
| Diuretic, n (%) | 145 (5.8) | 30 (4.8) | 39 (6.3) | 22 (3.5) | 54 (8.7)*,& | .001 |
| Statin, n (%) | 287 (11.6) | 62 (10.0) | 82 (13.2) | 63 (10.2) | 80 (12.9) | .143 |
| Aspirin, n (%) | 173 (7.0) | 36 (5.8) | 35 (5.6) | 43 (6.9) | 59 (9.5) | .027 |
| CAPD centers, n (%) | <.001 | |||||
| 1 | 287 (11.6) | 37 (6.0) | 62 (10.0) | 90 (14.5) | 98 (15.8) | |
| 2 | 802 (32.3) | 132 (21.3) | 149 (24.0) | 225 (36.3) | 296 (47.7) | |
| 3 | 50 (2.0) | 4 (0.6) | 15 (2.4) | 12 (1.9) | 19 (3.1) | |
| 4 | 258 (10.4) | 79 (12.7) | 72 (11.6) | 55 (8.9) | 52 (8.4) | |
| 5 | 412 (16.6) | 152 (24.5) | 142 (22.9) | 86 (13.9) | 32 (5.2) | |
| 6 | 99 (4.0) | 18 (2.9) | 23 (3.7) | 33 (5.3) | 25 (4.0) | |
| 7 | 115 (4.6) | 39 (6.3) | 32 (5.2) | 25 (4.0) | 19 (3.1) | |
| 8 | 457 (18.4) | 159 (25.6) | 125 (20.2) | 94 (15.2) | 79 (12.7) |
Q: quartiles; SUA: serum uric acid; Scr: serum creatinine; BMI: body mass index; SBP: systolic blood pressure; DBP: diastolic blood pressure; DM: diabetes mellitus; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; hs-CRP: high-sensitivity C-reactive protein; eGFR: estimated glomerular filtration rate; CCB: calcium channel blocker; ACEI: angiotensin-converting enzyme inhibitor; ARB: angiotensin II receptor blocker; CAPD: continuous ambulatory peritoneal dialysis.
Compared with Q1 group, p < .05.
Compared with Q2 group, p < .05.
Compared with Q3 group, p < .05.
Clinical characteristics of CAPD patients among different SUA/Scr groups
The median SUA/Scr levels in CAPD patients were 0.79 (0.59, 1.04), and we categorized the included sample into four groups based on the quartiles of baseline SUA/Scr levels (Table 1). Compared to patients in the lowest quartile, those with higher quartiles of SUA/Scr were older and more likely to be female. In addition, compared with the lowest quartile of SUA/Scr, patients with higher quartiles of SUA/Scr had higher rates of DM, higher levels of cholesterol, triglycerides, LDL-C, hemoglobin, hs-CRP, eGFR, and SUA, as well as a lower rate of α-blocker and β-blocker use, and lower levels of DBP, HDL, and Scr. However, there was no significant variance between the quartiles in terms of the percentage of hypertension, CCB, ACEI/ARB, and statin use, and levels of BMI, and SBP.
Association between SUA/Scr and mortality in CAPD patients
During 12648.0 person-years of follow-up (median 4.83 (2.88, 7.03) years), 527 (21.3%) patients died, 249 (10.0%) patients transferred to HD, 144 (5.8%) underwent kidney transplants, 24 (1.0%) patients transferred to other dialysis facilities, and 55 (2.2%) were lost to follow-up. Of 527 deaths, 267 (50.7%) were caused by CVD, 71 (13.5%) by infectious disease, 14 (2.7%) by gastrointestinal bleeding, 15 (2.8%) by malignancy, 71 (13.5%) by other reasons, and 89 (16.9%) were due to unknown causes (Figure 1). The incidence of all-cause mortality significantly increased with a higher SUA/Scr quartile, peaking at 69.4/1000 person-years in the highest SUA/Scr quartile (Table 2). A similar pattern was observed in cardiovascular mortality, with an incidence of 37.6/1000 person-years in the highest SUA/Scr quartile (Table 2).
Table 2.
Incidence rate of death in CAPD patients according to quartiles of SUA/Scr.
| Outcomes | Overall (n = 2480) | Q1 (≤0.59) (n = 620) | Q2 (0.60–0.79) (n = 620) | Q3 (0.80–1.04) (n = 620) | Q4 (≥1.05) (n = 620) |
|---|---|---|---|---|---|
| Person-years | 12648.0 | 3273.6 | 3019.4 | 3230.2 | 3112.4 |
| All-cause mortality | |||||
| Number of events | 527 | 88 | 93 | 130 | 216 |
| Events per 1000 person-years | 41.7 | 26.9 | 30.8 | 40.0 | 69.4 |
| Cardiovascular mortality | |||||
| Number of events | 267 | 38 | 36 | 76 | 117 |
| Events per 1000 person-years | 21.1 | 11.6 | 11.9 | 23.5 | 37.6 |
SUA: serum uric acid; Scr: serum creatinine; Q: quartiles; CAPD: continuous ambulatory peritoneal dialysis.
Kaplan–Meier’s survival analysis showed that both all-cause and cardiovascular mortality were substantially higher in the highest SUA/Scr quartile (both p < .001, Figure 2). Compared with the first quartile, the unadjusted HRs (model 1) for all-cause mortality were 1.161 (95% CI 0.867–1.553), 1.491 (95% CI 1.138–1.955), and 2.597 (95% CI, 2.027–3.328) for the second, third, and fourth quartiles, respectively (Table 3). After adjustments for variables, the final model (model 4) showed that the highest and the second highest quartile of SUA/Scr had a 2.361-fold (95% CI 1.810–3.080) and 1.325-fold (95% CI 1.003–1.749) higher risk of all-cause mortality than the lowest quartile. Similar patterns were seen in the relationship between SUA/Scr and cardiovascular mortality (Table 3). In model 4, the third and fourth quartiles of SUA/Scr had a 2.074-fold (95% CI 1.387–3.100) and 3.701-fold (95% CI 2.496–5.489) higher risk of cardiovascular mortality than the lowest quartile.
Figure 2.
Kaplan–Meier’s survival analysis for all-cause (A) and cardiovascular (B) mortality curves among CAPD patients grouped by SUA/Scr. CAPD: continuous ambulatory peritoneal dialysis; SUA: serum uric acid; Scr: serum creatinine.
Table 3.
Association between baseline SUA/Scr with all-cause and cardiovascular mortality in CAPD patients.
| Outcomes | Model 1 HR (95% CI) |
Model 2 HR (95% CI) |
Model 3 HR (95% CI) |
Model 4 HR (95% CI) |
|---|---|---|---|---|
| All-cause mortality | ||||
| SUA/Scr ratio per 1 SD increase | 1.641 (1.460, 1.844) | 1.568 (1.379, 1.783) | 1.637 (1.428, 1.878) | 1.629 (1.420, 1.867) |
| Quartiles of SUA/Scr ratio | ||||
| Q1, ≤0.59 (n = 620) | Ref | Ref | Ref | Ref |
| Q2, 0.60–0.79 (n = 620) | 1.161 (0.867, 1.553) | 1.112 (0.829, 1.490) | 1.110 (0.827, 1.488) | 1.110 (0.828, 1.489) |
| Q3, 0.80–1.04 (n = 620) | 1.491 (1.138, 1.955) | 1.386 (1.051, 1.827) | 1.349 (1.022, 1.782) | 1.325 (1.003, 1.749) |
| Q4, ≥1.05 (n = 620) | 2.597 (2.027, 3.328) | 2.450 (1.881, 3.191) | 2.400 (1.840, 3.130) | 2.361 (1.810, 3.080) |
| p Value for trends | <.001 | <.001 | <.001 | <.001 |
| Cardiovascular mortality | ||||
| SUA/Scr ratio per 1 SD increase | 1.732 (1.486, 2.019) | 1.696 (1.442, 1.994) | 1.730 (1.467, 2.041) | 1.730 (1.467, 2.041) |
| Quartiles of SUA/Scr ratio | ||||
| Q1, ≤0.59 (n = 620) | Ref | Ref | Ref | Ref |
| Q2, 0.60–0.79 (n = 620) | 1.040 (0.659, 1.641) | 1.071 (0.677, 1.693) | 1.088 (0.687, 1.721) | 1.088 (0.687, 1.721) |
| Q3, 0.80–1.04 (n = 620) | 2.019 (1.368, 2.981) | 2.062 (1.385, 3.069) | 2.074 (1.387, 3.100) | 2.074 (1.387, 3.100) |
| Q4, ≥1.05 (n = 620) | 3.248 (2.253, 4.684) | 3.511 (2.383, 5.172) | 3.701 (2.496, 5.489) | 3.701 (2.496, 5.489) |
| p Value for trends | <.001 | <.001 | <.001 | <.001 |
SUA: serum uric acid; Scr: serum creatinine; Q: quartiles; SD: standard deviation; HR: hazard ratio; CI: confidence interval; CAPD: continuous ambulatory peritoneal dialysis.
Model 1: unadjusted crude HR; model 2: adjusted for age, sex, BMI, DM, hypertension, centers, and protopathy; model 3: model 2 plus hemoglobin, serum albumin, cholesterol, triglycerides, LDL, HDL, and hs-CRP; model 4: model 3 plus medicine use (including CCB, α-blocker, β-blocker, ACEI/ARB, diuretic, statin, and aspirin).
The adjusted HRs per unit higher SUA/Scr level for all-cause and cardiovascular mortality were 1.629 (95% CI 1.420–1.867) and 1.730 (95% CI 1.467–2.041), respectively. Multivariable-adjusted spline regression models showed nonlinear association of SUA/Scr ratio with all-cause and cardiovascular mortality in CAPD patients (Figure 3). In addition, there was positively, nonlinearly association of SUA with all-cause and cardiovascular mortality, and there were negatively, nonlinearly association of Scr with all-cause mortality, while negatively, linearly association of Scr with cardiovascular mortality in CAPD patients (Supplementary Table S1 and Supplementary Figure S1).
Figure 3.
Multivariable-adjusted hazard ratio for all-cause (A) and cardiovascular (B) mortality by baseline SUA/Scr in CAPD patients. Solid red line indicates estimated HR, the pink area indicates confidence interval, the dotted line is the reference line of HR = 1. Multivariable-adjusted HRs were estimated after adjustment for age, sex, BMI, DM, hypertension, centers, protopathy, hemoglobin, serum albumin, cholesterol, triglycerides, LDL, HDL, hs-CRP, and medicine use (including CCB, α-blocker, β-blocker, ACEI/ARB, diuretic, statin, and aspirin). SUA: serum uric acid; Scr: serum creatinine; HR: hazard ratio; CI: confidence interval; CAPD: continuous ambulatory peritoneal dialysis.
The optimal cutoff value of SUA/Scr for predicted all-cause mortality was 0.87, with a sensitivity of 57.3%, a specificity of 63.4%, a NPV of 29.7, a PPV of 84.6, and an AUC of 0.634 (95% CI 0.606–0.661, p < .05). The optimal cutoff value of SUA/Scr for predicted cardiovascular mortality was 0.81, with a sensitivity of 70.4%, a specificity of 55.2%, a NPV of 15.9, a PPV of 91.8, and an AUC of 0.650 (95% CI 0.615–0.685, p < .05, Supplementary Table S2).
Sensitivity analyses
All sensitivity analyses using Fine–Gray models (model 5), excluding individuals less than 2 years follow-up (n = 360, model 6) and those with diuretic or statin therapy at baseline (n = 401, model 7) generated similar findings with the primary analysis (Table 4).
Table 4.
Sensitivity analysis on the association between baseline SUA/Scr with all-cause and cardiovascular mortality in CAPD patients.
| Outcomes | Model 5 SHR (95% CI) |
Model 6 HR (95% CI) |
Model 7 HR (95% CI) |
|---|---|---|---|
| All-cause mortality | |||
| SUA/Scr ratio per 1 SD increase | 1.585 (1.371, 1.833) | 1.725 (1.472, 2.022) | 1.556 (1.335, 1.813) |
| Quartiles of SUA/Scr ratio | |||
| Q1, ≤0.59 | Ref | Ref | Ref |
| Q2, 0.60–0.79 | 1.103 (0.826, 1.472) | 1.034 (0.738, 1.448) | 1.192 (0.873, 1.630) |
| Q3, 0.80–1.04 | 1.367 (1.035, 1.804) | 1.172 (0.852, 1.612) | 1.267 (0.937, 1.713) |
| Q4, ≥1.05 | 2.301 (1.755, 3.016) | 2.309 (1.709, 3.119) | 2.230 (1.666, 2.986) |
| p Value for trends | <.001 | <.001 | <.001 |
| Cardiovascular mortality | |||
| SUA/Scr ratio per 1 SD increase | 1.671 (1.384, 2.016) | 1.996 (1.634, 2.437) | 1.688 (1.414, 2.015) |
| Quartiles of SUA/Scr ratio | |||
| Q1, ≤0.59 | Ref | Ref | Ref |
| Q2, 0.60–0.79 | 1.108 (0.700, 1.753) | 1.019 (0.603, 1.722) | 1.165 (0.717, 1.894) |
| Q3, 0.80–1.04 | 2.252 (1.492, 3.399) | 1.856 (1.176, 2.931) | 2.025 (1.321, 3.104) |
| Q4, ≥1.05 | 3.501 (2.308, 5.311) | 3.686 (2.375, 5.720) | 3.385 (2.223, 5.156) |
| p Value for trends | <.001 | <.001 | <.001 |
SUA: serum uric acid; Scr: serum creatinine; Q: quartiles; SD: standard deviation; HR: hazard ratio; CI: confidence interval; CAPD: continuous ambulatory peritoneal dialysis.
Model 5: sensitivity analysis using competing risk model; model 6: sensitivity analysis excluding individuals less than 2 years follow-up (n = 360); model 7: sensitivity analysis excluding individuals with diuretic or statin therapy at baseline (n = 401); models 5–7 were fully adjusted for age, sex, BMI, DM, hypertension, centers, protopathy, hemoglobin, serum albumin, cholesterol, triglycerides, LDL, HDL, hs-CRP, and medicine use (including CCB, α-blocker, β-blocker, ACEI/ARB, diuretic, statin, and aspirin).
Subgroup analyses
Among subgroup analyses, when participants were stratified by age, gender, hypertension, DM, BMI, serum albumin, hs-CRP, and the protopathy, the association between SUA/Scr with all-cause and cardiovascular mortality remained consistent. None of the selected covariates was a significant effect modifier of the connection between SUA/Scr and all-cause, as well as cardiovascular mortality in CAPD patients (Figure 4).
Figure 4.
Subgroup association of baseline SUA/Scr with all-cause (A) and cardiovascular (B) mortality. DM: diabetes mellitus; BMI: body mass index; hs-CRP: high-sensitivity C-reactive protein.
Discussion
In this retrospective cohort analysis, we discovered that SUA/Scr was a distinct risk factor for death in subjects with CAPD. Those in the highest SUA/Scr quartile had a 2.4-fold higher risk of all-cause and 3.7-fold higher risk of cardiovascular mortality than those in the lowest quartile, even after multiple covariates were considered. This is the first research that, to our knowledge, has investigated the link between SUA/Scr and mortality in a sizable, multicenter, representative sample of CAPD patients.
CVD continues to be the leading cause of death among PD patients. Our figures show a 50.7% rate, which is comparable to the global average [18]. There were several traditional CVD and non-CVD risk factors that explain the entire risk of mortality in this population. A recent meta-analysis on risk factors of mortality in PD patients showed that there were multiple factors that could affect the risk of mortality in PD patients, such as age, primary CVDs, DM, and high level of alkaline phosphatase, which showed significant positive associations with elevated risk of all-cause and cardiovascular mortality, while the absolute serum level of SUA required to improve survival in PD patients should be verified further [19]. The Framingham Heart Study was the first to demonstrate a causal link between SUA levels and the risk of adverse cardiovascular events in a general population [20]. There are various possible reasons for the association between SUA levels and increased cardiovascular risk, including the presence of shared risk factors and the direct interaction of uric acid with several metabolic pathways connected to CVD [21]. However, whether uric acid has a causal role in kidney and CVDs in PD patients is still inconclusive though it seems to be associated with hypertension, DM, metabolic syndrome, progression of chronic kidney disease and CVDs in the general population [22–24]. Meanwhile, subsequent studies showed that the connection between SUA levels and mortality in subjects with PD is inconsistent. For instance, multiple investigations revealed that rising SUA levels were a distinct risk element for cardiovascular and all-cause death in the PD group [25,26]. A recent study from Chinese cohort reported that higher serum SUA level can predict higher risk of technique failure (such as transferring to HD and mortality) in CAPD patients [27]. However, urate-lowering treatment with allopurinol did not slow the decline of eGFR in diabetic and non-diabetic patients, and no evidence of clinically meaningful effects with respect to secondary outcomes such as fatal or nonfatal cardiovascular events was found [28,29]. In addition, Lai et al. discovered that among women receiving CAPD, there was an inverse relationship between the higher SUA level with cardiovascular and all-cause death [30]. Besides, high SUA levels were associated with greater appendicular skeletal muscle mass index (ASMI) in PD patients, and independently predicted lower all-cause mortality in lower ASMI PD populations [31], which indicated that the ASMI may affect the association between SUA and all-cause PD mortality. Additionally, another study reported that SUA levels were very modestly related to all-cause and cardiovascular death in PD subjects [32]. On the other hand, Sugano et al. found a U-shaped connection between SUA levels and all-cause death among PD patients [33], which was like our study, we found that SUA was positively, nonlinearly association with mortality in CPAD patients. In short, the impact of SUA on the survival of PD patients has long been debated and paradoxical. In addition, it has been reported that higher Scr is associated with higher mortality among general population [34], whereas lower Scr is associated with higher mortality in HD patients [35]. In PD patients, we found that Scr is negatively associated with mortality in CAPD patients, which was consistent with previous research [36].
Current research has found that SUA/Scr is a more accurate predictor for clinical outcomes [10–14]. Higher SUA/Scr was also reported to be associated with an elevated risk of CVD [37]. On the other hand, SUA/Scr was strongly correlated with all-cause and cardiovascular death in general, according to data from the US National Health and Nutrition Examination Survey [38]. Though Scr levels in dialysis patients, particularly those lacking residual renal function, cannot accurately represent renal function, they can nevertheless indicate nutritional status [36]. Thus, SUA/Scr values in these individuals may indicate nutrition-normalized SUA levels. According to Ding Z et al., the SUA/Scr is much more predictive of overall mortality in older HD patients than the SUA or Scr alone [39]. However, no prior research has been done to determine the predictive usefulness of SUA/Scr in CAPD subjects. Considering the contradictory impact of SUA on patients with CAPD, we initially evaluate the association between nutrition-normalized SUA (SUA/Scr) and survival status in those subjects. Our findings indicate that a high baseline SUA/Scr is a major risk element for cardiovascular and all-cause death in CAPD patients.
The molecular processes connecting SUA/Scr to mortality are thought to be the stimulation of inflammation caused by excessive uric [40]. Furthermore, SUA/Scr is related to several cardiometabolic variables, which may offer a mediation mechanism for the relationship between SUA/Scr and cardiovascular mortality [37]. On the other hand, SUA and Scr may be connected to the nutritional state among dialysis patients [36,41]. A prior study showed that protein-energy wasting was common in PD patients, and malnutrition is linked to noticeably worse outcomes in PD patients [41]. In our study, multivariate Cox regression analysis reveals that SUA/Scr remains a relevant factor for mortality even after multiple covariates were considered, and none of the covariates is a significant effect modifier of the connection between SUA/Scr and mortality in CAPD patients. All these findings indicate that SUA/Scr is a unique risk factor for mortality.
Our study had some strengths, including a large sample size, multi-center, and long follow-up period. Additionally, we analysed the association between baseline SUA/Scr levels and the risk of all-cause and cardiovascular mortality by several strict statistical methods. However, there are a few limitations to this study. First, it was a retrospective observational study and the causality between SUA/Scr and mortality cannot be determined even though we have carefully controlled possible risk variables. Second, food consumption may affect the SUA level, with 20% of the human SUA pool coming from exogenous food consumption [42]. We did not adjust food consumption, which may have an impact on SUA levels. Third, all parameters in this investigation were solely identified at baseline and without regard for changes over time. Fourth, CAPD patients was a very heterogeneous population, there were multiple factors that can also have an impact on their prognosis (such as dialysis vintage, different solutes, rate of solute exchange, type of transport status of the peritoneal membrane, residual urine volume, etc.) [19]. However, we did not adjust these factors because they were not collected in this study, and further research is needed to clarify the relationship between SUA/Scr and the risk of mortality in PD patients by fully adjusting for these factors.
Conclusions
In conclusion, we found that increased SUA/Scr was highly related to all-cause and cardiovascular mortality in CAPD patients. These findings may promote the potential use of SUA/Scr in clinical practice as a predictive marker for mortality. More high-level research with a broad population, particularly randomized controlled trials, is required for further validation.
Supplementary Material
Acknowledgements
We thank all subjects and medical staff who generously contributed to this study. We thank the Ever-green Tree Nephrology Group for his contribution to this study.
Correction Statement
This article has been corrected with minor changes. These changes do not impact the academic content of the article.
Funding Statement
This study was supported by the Social Development Science and Technology Program of Dongguan (No. 20211800901412).
Ethical approval
Ethical approval mandatory for this study was obtained from Ethics Committee at Dongguan Tungwah Hospital (2021-KY-021).
Consent form
Informed consent was obtained from all individual participants included in the study.
Author contributions
Jieping Hu: formal analysis and writing original draft. Liwen Tang, Wei Zheng, Xiaojiang Zhan, Fenfen Peng, Xiaoyang Wang, Yueqiang Wen, and Xiaoran Feng: resources and data curation. Xianfeng Wu and Qian Zhou: data verification. Xingcui Gao: revised article. Ning Su and Xingming Tang: conceptualization, investigation, and writing-review and editing. All authors read and approved the final manuscript.
Disclosure statement
The authors have no relevant financial or non-financial interests to disclose.
Data availability statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Associated Data
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Supplementary Materials
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.