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Hôpital Lariboisière, service de Rhumatologie, F-75010 Paris, FranceInserm, UMR1132, Hôpital Lariboisière, F-75010 Paris, FranceUniversité Paris Diderot, Sorbonne Paris Cité, F-75205 Paris, France
School of Medicine, University of Limerick, Limerick, IrelandHealth Research Institute (HRI), University of Limerick, Limerick, IrelandDepartment of Nephrology, University Hospital Limerick, Limerick, Ireland
SUA exhibits a nonlinear relationship with mortality in Irish patients
•
Mortality risks of SUA differs between men and women.
•
Optimal SUA values for best survival in men are 304-454 μmol/l.
•
Optimal SUA values for best survival in women are < 409 μmol/l.
•
Substantial reductions in survival are associated with extremes of SUA
Abstract
Background
Elevation of serum uric acid (SUA) is associated with increased mortality; however, controversy exists regarding the nature of the relationship and differences between men and women. We explored relationships of SUA levels with all-cause mortality in a large cohort of patients within the Irish health system.
Methods
A retrospective cohort study of 26,525 participants was conducted using data from the National Kidney Disease Surveillance System. SUA was modelled in increments of 59.48 µmol/L (1 mg/dL), Cox's proportional hazards model estimated hazard ratios (HRs) and 95% Confidence Intervals (CI), median lifetimes were also computed separately for men and women. Mortality patterns were further explored using penalised splines.
Results
There were 1,288 (4.9%) deaths over a median follow-up of 5.1 years. In men, the risk of mortality was greatest for the lowest (<238 µmol/L) and highest (>535 µmol/L) categories [HR 2.35 (1.65–3.14) and HR 2.52 (1.87–3.29) respectively]; the corresponding median lifetimes for men were reduced by 9.5 and 11.7 years respectively compared to the referent. In women, mortality risks were elevated for SUA >416 mol/L [HR 1.69 (1.13–2.47) and beyond; the corresponding median lifetime for women were reduced by 5.9 years compared to the referent. Spline analysis revealed a U-shaped association between SUA and mortality in men, while for women, the pattern of association was J-shaped.
Conclusion
Mortality patterns attributed to SUA differ between men and women. Optimal survival was associated with SUA concentrations of 304–454 µmol/L for men and < 409 µmol/L for women.
It is widely considered that serum uric acid (SUA), the final breakdown product of purine metabolism in humans, may represent a major cardiovascular risk factor and contribute to adverse health outcomes and mortality [
Serum uric acid is an independent predictor for all major forms of cardiovascular death in 28,613 elderly women: a prospective 21-year follow-up study.
Centola M., Maloberti A., Castini D., et al. Impact of admission serum acid uric levels on in-hospital outcomes in patients with acute coronary syndrome. Eur J Intern Med. Published online 2020. doi:10.1016/j.ejim.2020.07.013.
Increased serum uric acid level predicts poor prognosis in mildly severe chronic heart failure with reduced ejection fraction. An analysis from the MECKI score research group.
]. Elevated concentrations of SUA have been implicated in the development of hypertension, metabolic syndrome, type 2 diabetes, coronary artery disease, left ventricular hypertrophy, atrial fibrillation, myocardial infarction, stroke, heart failure and chronic kidney disease [
]. Furthermore, large prospective observational studies have found a strong positive association between high levels of SUA and all-cause mortality suggesting a potentially causal relationship and a possible target for intervention. Nevertheless, several studies have suggested that the relationship of SUA with major outcomes is not linear in shape and varies across studies [
]. Moreover, several recent studies have shown that patients with low SUA levels experienced higher mortality risks suggesting that low SUA levels may portend a poor prognosis in specific populations [
Relationship between serum uric acid and mortality among hemodialysis patients: retrospective analysis of Korean end-stage renal disease registry data.
The true nature of the relationship between uric acid and mortality is important to clarify as treatment strategies that lower SUA may, on one hand, provide substantial benefits or, on the other hand, confer additional risk. At physiological levels, uric acid has both anti-oxidant [
]. Under normal circumstances, uric acid (as hydrogen urate) may function as an antioxidant and studies have shown that low levels of SUA damage the endothelium and induce oxidative stress–related disease such as hypertension, diabetes mellitus, and kidney disease [
]. Thus, depending on the prevailing conditions, SUA may confer a beneficial or adverse function. The evidence to date raises suspicions that the relationship between SUA and mortality is not straightforward and may vary by sex, health status and degree of comorbidity [
Serum uric acid is an independent predictor for all major forms of cardiovascular death in 28,613 elderly women: a prospective 21-year follow-up study.
Centola M., Maloberti A., Castini D., et al. Impact of admission serum acid uric levels on in-hospital outcomes in patients with acute coronary syndrome. Eur J Intern Med. Published online 2020. doi:10.1016/j.ejim.2020.07.013.
Increased serum uric acid level predicts poor prognosis in mildly severe chronic heart failure with reduced ejection fraction. An analysis from the MECKI score research group.
The principal objectives of this study were to: examine the relationship between SUA and all-cause mortality among patients within the Irish health system; compare the shape of this relationship for men and women; and identify SUA threshold values for mortality and the optimal SUA range with greatest survival benefit.
2. Methods
2.1 Data source
We utilised data from the National Kidney Disease Surveillance System (NKDSS), which monitors trends and outcomes of kidney disease in the Irish Health System [
Prevalence and variation of Chronic Kidney Disease in the Irish health system: initial findings from the National Kidney Disease Surveillance Programme.
]. The principal data sources include; regional laboratory information systems, which capture a comprehensive list of laboratory results from inpatients and outpatients within a designated health region; dialysis registers which capture clinical data on patients who progress to End Stage Kidney Disease (ESKD); and mortality data files from the national Central Statistics Office (CSO). The final merged dataset captured information on demographic characteristics, county of residence, primary location of patient supervision, multiple laboratory measures of health status, dialysis indicator variables and death.
2.2 Cohort participants
Patients who entered the health system from University Hospital Group Limerick (Midwest) in the Republic of Ireland, between January 1st, 2006 and December 31st, 2012, were included and followed until December 31st, 2013. The analysis was restricted to adult participants, 18 years of age or older, who had valid SUA measurements with concurrent biochemistry profiles and had vital status through 31st December 2013.
2.3 Outcome
The primary outcome was all-cause mortality (ICD-9 001.x–999.x or ICD-10 A00.x–Z99.x) as determined from national records provided by the CSO. The CSO oversees the collection and analysis of national data on mortality in the Republic of Ireland. The date of death and primary cause of death were available from the national mortality files.
2.4 Exposure
The primary exposure was SUA concentration recorded at first measurement within the health system for each patient. Serum uric acid (µmol/L) was measured using the uricase-peroxidase enzymatic method on an auto analyser in the laboratory data systems during the study period. Baseline characteristics for each participant were recorded at first entry into the health system during the recruitment period. Data were captured on age, sex, county of residence, health region, location of medical supervision, and an extensive range of blood biomarkers which indicated the presence and severity of clinical disease. Fasting plasma glucose and glycosylated haemoglobin (HbA1c) were used to detect diabetes; plasma total cholesterol, triglycerides served as markers of dyslipidaemia; alanine aminotransferase (ALT), total bilirubin, alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT) and serum albumin measured hepatic function; while serum albumin also served as an measure of acute illness. White blood cells (WBC), lymphocytes, and neutrophils, c-reactive protein, erythrocyte-sedimentation rate served as markers of inflammation. Lastly, serum urea and creatinine were measures of renal function. Serum creatinine was measured using the modified kinetic Jaffe method and creatinine values were calibrated to be traceable to an isotope dilution mass spectrometry (IDMS) reference measurement procedure to ensure standardization. Serum creatinine values were used to determine estimated glomerular filtration rate (eGFR) in ml/min per 1.73 m2, for patients using equations derived by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) [
A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.
Annals of Internal Medicine.1999; 130 (doi:199903160-00002 [pii]): 461-470
]. Chronic Kidney Disease was defined according to the Kidney Disease Dialysis Quality Outcome Initiative (KDOQI) guidelines based on eGFR measurements [
]. The location of medical supervision was defined as the location where the creatinine test was ordered by the supervising physician and categorised as; inpatient facility (IP), outpatient facility (OP), general practice (GP) and emergency room (ER).
2.5 Statistical analysis
Serum uric acid was classified according to increments of 59.48 µmol/L (or 1 mg/dL) for men and women. Baseline characteristics of all subjects and by category were summarised and described using percentages for categorical data, mean and standard deviation for continuous variables or median and interquartile range for continuous variables with skewed distribution. Group comparisons for continuous variables were performed using the Kruskal Wallis test while group comparisons for categorical variables were performed with the Chi-square test.
Mortality rates were calculated for the entire cohort by strata of SUA expressed as deaths per 1000 person-years. The association of SUA with mortality was explored separately for men and women using sex-specific strata. Cox proportional hazard regression was used to model relationships of SUA with all-cause mortality adjusting for baseline characteristics and using age as the time scale. For men, the stratum (357–416 µmol/L) was used as the reference group given that it appeared to have the lowest mortality from the crude mortality analyses, while for women the (297–357 µmol/L) stratum was used as the reference. Patients were followed until death or end of study date; 31st December 2013. Covariates for adjustment included demographic factors, and core laboratory health indicators including eGFR estimated at baseline, plasma lipid levels, serum albumin, haemoglobin and ALT levels. Associations of SUA with mortality were expressed as hazard ratios (HR) with 95% Confidence Intervals (CI) in univariate and multivariable models. Schoenfeld tests assessed the proportional hazards assumption of the Cox models. The median survival age and corresponding 95% confidence intervals (via 1000 bootstrap replicates) were computed from the unadjusted and adjusted Cox models across each SUA category for men and for women; further details can be found in supplementary materials. To further examine the continuous association between SUA levels and mortality, we fitted a penalised spline model for SUA where the optimal spline smoothing parameter was selected by minimising the Akaike information criterion (AIC). All statistical analysis was performed using R program (version 4.0; http://www.r-project.org/).
2.6 Sensitivity analysis
A sensitivity analysis was conducted to explore the robustness of observed relationships. We investigated whether the presence of CKD as defined by an eGFR threshold of less than 60 ml/min/1.73 m2 modified the relationship between SUA and mortality as SUA has been reported to play a causal role in kidney injury and the presence of hyperuricemia may reflect poor renal function [
]. Effect modification was explored by including cross-product interaction terms in the Cox models that examined the impact of baseline covariates on the SUA-mortality relationship.
2.7 Ethics approval
The study was approved by the Ethics Committee at University Hospital Limerick.
3. Results
3.1 Baseline characteristics of the population
The construction of the final study cohort from the Midwest region of Ireland is shown in Fig. 1 according to the STROBE criteria. The distributions of demographic characteristics and laboratory measures across sex-specific strata of SUA are listed separately for men (Table 1) and for women (Table 2). Of the 26,525 Patients, 53% were male and the mean (SD) baseline age was 53.8 (15.5) years. Serum uric acid levels were higher in men than in women and most of patients were seen in general practice or primary care setting.
Fig. 1Strobe diagram for the retrospective cohort study from 2006–2013. The final dataset captured information on demographic characteristics, county of residence, and primary location of patient supervision, measured laboratory parameters and mortality.
eGFR: Estimated glomerular filtration rate (ml/min per 1.73 m2) was based on the Chronic Kidney Disease Collaborative (CKD-EPI) equation [15]. SI: International System of Units.
13,922
93.74 (20.93)
93.33 (23.27)
91.02 (22.74)
88.50 (24.99)
85.36 (27.46)
80.13 (29.70)
68.46 (40.95)
<0.001
eGFR Category
eGFR >=90
6,651
59.37
57.78
52.01
46.8
40.92
32.35
24.21
eGFR 60-89
6,056
36.57
38.06
42.67
45.45
47.02
49.49
36.2
eGFR 30-59
1,097
3.84
3.8
5
7.25
11.2
15.66
31.22
eGFR 15-29
100
0
0.25
0.27
0.38
0.86
1.82
7.92
eGFR < 15
18
0.23
0.1
0.05
0.13
0
0.68
0.45
<0.001
Inflammatory Markers (Median (IQR))
C-Reactive Protein (mg/L)
631
7.00 (12.00)
7.00 (17.75)
7.00 (13.00)
6.00 (8.00)
8.00 (13.00)
8.00 (9.75)
9.00 (9.00)
0.272
ESR (mm/hr)
2,641
7.00 (12.00)
7.00 (8.75)
6.00 (7.00)
6.00 (7.00)
7.00 (8.00)
11.00 (11.00)
14.00 (18.00)
<0.001
White blood count (x109/L)
12,551
6.62 (2.87)
6.64 (2.61)
6.47 (2.39)
6.58 (2.26)
6.69 (2.28)
6.94 (2.39)
7.47 (2.79)
<0.001
Lymphocyte count (x109/L)
12,551
1.68 (0.88)
1.78 (0.80)
1.80 (0.75)
1.84 (0.75)
1.88 (0.74)
1.82 (0.76)
1.79 (0.88)
<0.001
Neutrophil count (x109/L)
12,551
4.00 (2.28)
3.83 (1.88)
3.71 (1.73)
3.78 (1.68)
3.81 (1.71)
4.05 (1.91)
4.43 (2.26)
<0.001
Nutritional and Metabolic Markers (Mean (SD))
Serum Albumin (g/L)
9,593
38.57 (5.11)
39.97 (3.71)
40.34 (3.44)
40.67 (3.33)
40.44 (3.42)
39.67 (3.90)
38.28 (4.49)
<0.001
Haemoglobin (g/dl)
12,551
14.21 (1.65)
14.70 (1.30)
14.90 (1.16)
14.99 (1.18)
14.93 (1.22)
14.82 (1.35)
14.23 (1.69)
<0.001
Serum Calcium (mmol/L)
8,945
2.30 (0.11)
2.32 (0.09)
2.32 (0.09)
2.33 (0.08)
2.33 (0.09)
2.32 (0.09)
2.31 (0.13)
<0.001
Serum Phosphorus (mmol/L)
8,420
1.13 (0.23)
1.11 (0.23)
1.08 (0.21)
1.08 (0.20)
1.08 (0.20)
1.09 (0.21)
1.17 (0.29)
<0.001
Serum Potassium (mmol/L)
11,693
4.52 (0.48)
4.59 (0.49)
4.55 (0.45)
4.56 (0.46)
4.56 (0.44)
4.56 (0.45)
4.55 (0.52)
0.148
Lipid Markers (Mean (SD))
Total Cholesterol (mmol/L)
13,922
4.73(1.13)
4.89 (1.07)
5.05 (1.07)
5.16 (1.08)
5.19 (1.10)
5.22 (1.11)
5.05 (1.27)
<0.001
Triglycerides (mmol/L)
13,922
1.30 (0.85)
1.36 (1.03)
1.48 (0.97)
1.64 (1.07)
1.86 (1.15)
2.06 (1.28)
2.34 (1.47)
<0.001
Glycaemic Markers (Median (IQR))
HbA1c (%)
3,094
7.30 (3.25)
6.36 (2.60)
6.00 (1.40)
5.90 (1.10)
5.90 (0.98)
5.99 (0.90)
6.15 (1.24)
<0.001
Glucose (mmol/L)
8,860
5.20 (1.45)
5.10 (1.10)
5.00 (0.90)
5.10 (0.80)
5.10 (0.80)
5.20 (0.80)
5.30 (1.00)
<0.001
Markers of Liver function (Median (IQR))
Alanine transaminase (IU/L)
13,285
25.00 (14.00)
25.00 (13.00)
28.00 (14.00)
30.00 (17.00)
32.00 (18.00)
32.00 (21.75)
32.00 (21.00)
<0.001
Alkaline phosphatase (IU/L)
13,415
69.50 (27.00)
67.00 (23.00)
66.00 (23.00)
66.00 (23.00)
66.00 (23.00)
66.50 (24.00)
71.00 (26.00)
<0.001
γ-glutamyltransferase (IU/L)
13,382
26.00 (22.00)
24.00 (18.00)
26.00 (20.00)
29.00 (21.00)
34.00 (27.00)
37.00 (31.00)
46.00 (51.00)
<0.001
Total bilirubin (µmol/L)
13,133
12.00 (6.00)
13.00 (6.00)
14.00 (6.00)
14.00 (7.00)
14.00 (7.00)
14.00 (6.00)
14.00 (6.00)
<0.001
a Location of medical supervision refers to the location of patient when the laboratory test was conducted.
b eGFR: Estimated glomerular filtration rate (ml/min per 1.73 m2) was based on the Chronic Kidney Disease Collaborative (CKD-EPI) equation [15]. SI: International System of Units.
eGFR: Estimated glomerular filtration rate (ml/min per 1.73 m2) was based on the Chronic Kidney Disease Collaborative (CKD-EPI) equation [15], SI: International System of UnitsSerum uric acid and Mortality in Men.
12,603
100.75 (26.48)
97.49 (24.17)
91.54 (26.53)
84.31 (29.25)
76.15 (30.40)
67.83 (32.79)
46.34 (29.58)
<0.001
eGFR Category
>90
6,029
69.82
65.68
53.26
40.11
28.01
17.70
7.50
60-90
5,088
27.03
30.85
40.99
46.75
48.90
43.00
22.50
30-60
1,370
2.89
3.39
5.57
12.62
21.70
35.80
53.44
15-30
104
0.00
0.00
0.18
0.50
1.32
2.88
15.31
<15
12
0.26
0.08
0.00
0.03
0.07
0.62
1.25
<0.001
Inflammatory Markers (Median (IQR))
C-Reactive Protein (mg/L)
814
5.50 (15.75)
7.00 (11.00)
5.00 (7.00)
6.00 (7.00)
7.00 (7.00)
5.00 (9.50)
8.50 (7.75)
0.018
ESR (mm/hr)
2,733
9.00 (11.00)
9.00 (8.00)
9.00 (10.00)
12.00 (11.00)
13.00 (13.00)
17.00 (14.00)
23.00 (30.25)
<0.001
White blood count (x109/L)
11,785
6.40 (2.67)
6.22 (2.52)
6.26 (2.42)
6.51 (2.48)
6.87 (2.38)
6.97 (2.72)
7.30 (2.65)
<0.001
Lymphocyte count (x109/L)
11,785
1.76 (0.71)
1.77 (0.76)
1.82 (0.75)
1.90 (0.79)
1.93 (0.80)
1.86 (0.85)
1.76 (0.96)
<0.001
Neutrophil count (x109/L)
11,785
3.76 (2.28)
3.62 (1.93)
3.59 (1.86)
3.71 (1.85)
4.02 (1.81)
4.01 (2.12)
4.44 (2.15)
<0.001
Nutritional and Metabolic Markers (Mean (SD))
Serum Albumin (g/L)
9,960
39.17 (3.88)
39.57 (3.17)
39.56 (3.21)
39.44 (3.13)
39.10 (3.31)
38.41 (3.35)
37.65 (4.06)
<0.001
Haemoglobin (g/dl)
11,785
12.94 (1.32)
13.21 (1.09)
13.40 (1.07)
13.49 (1.13)
13.52 (1.19)
13.34 (1.42)
12.87 (1.63)
<0.001
Serum Calcium (mmol/L)
9,357
2.30 (0.08)
2.31 (0.09)
2.32 (0.09)
2.33 (0.09)
2.33 (0.11)
2.34 (0.11)
2.33 (0.12)
<0.001
Serum Phosphorus (mmol/L)
8,562
1.21 (0.22)
1.21 (0.20)
1.21 (0.20)
1.21 (0.21)
1.20 (0.21)
1.21 (0.20)
1.24 (0.23)
0.647
Serum Potassium (mmol/L)
10,653
4.50 (0.46)
4.48 (0.45)
4.52 (0.45)
4.51 (0.46)
4.48 (0.46)
4.48 (0.52)
4.51 (0.57)
0.013
Lipid Markers (Mean (SD))
Total Cholesterol (mmol/L)
12,603
5.03 (0.99)
5.16 (0.96)
5.31 (1.03)
5.40 (1.09)
5.36 (1.13)
5.31 (1.16)
5.14 (1.25)
<0.001
Triglycerides (mmol/L)
12,603
1.01 (0.69)
1.02 (0.62)
1.16 (0.70)
1.43 (0.84)
1.58 (0.78)
1.76 (1.00)
1.83 (0.95)
<0.001
Glycaemic Markers (Median (IQR))
HbA1c (%)
2,256
5.70 (1.62)
5.60 (0.80)
5.70 (0.90)
5.80 (1.00)
6.00 (1.20)
6.20 (1.08)
6.30 (1.28)
<0.001
Glucose (mmol/L)
7,872
4.70 (0.60)
4.70 (0.70)
4.80 (0.60)
4.90 (0.70)
5.10 (0.80)
5.30 (1.10)
5.50 (1.25)
<0.001
Markers of Liver function (Median (IQR))
Alanine transaminase (IU/L)
12,033
18.00 (7.00)
18.00 (8.00)
20.00 (9.00)
22.00 (11.00)
23.00 (13.00)
23.00 (13.00)
20.00 (12.25)
<0.001
Alkaline phosphatase (IU/L)
12,179
57.00 (27.00)
59.00 (24.00)
62.00 (26.00)
68.00 (27.00)
70.00 (25.50)
73.00 (29.00)
77.00 (27.00)
<0.001
γ-glutamyltransferase (IU/L)
12,154
16.00 (10.00)
16.00 (10.00)
18.00 (13.00)
21.00 (15.00)
24.00 (20.00)
26.00 (19.50)
26.00 (23.00)
<0.001
Total bilirubin (µmol/L)
11,970
10.00 (5.00)
11.00 (5.00)
11.00 (5.00)
12.00 (5.00)
12.00 (5.50)
12.00 (5.00)
12.00 (5.00)
<0.001
a Location of medical supervision refers to the location of patient when the laboratory test was conducted.
b eGFR: Estimated glomerular filtration rate (ml/min per 1.73 m2) was based on the Chronic Kidney Disease Collaborative (CKD-EPI) equation [15], SI: International System of UnitsSerum uric acid and Mortality in Men.
Among men, an increase in SUA level was positively associated with decreasing renal function, rising inflammatory markers (c-reactive protein, white blood cell count) and increasing concentration of total cholesterol, triglycerides, ALT and GGT levels. Serum uric acid concentration did not increase linearly with age in men, rather patients in the lowest and highest SUA strata were on average older in age. Similarly, serum albumin and haemoglobin concentrations were lower at the extremes of the SUA categories while glycaemic markers and neutrophil levels were conversely higher at the extreme levels.
In contrast to men, SUA levels increased linearly with age in women. Increasing SUA levels were positively associated with reduced renal function and serum albumin levels in women. SUA was associated with increased levels of inflammatory markers, serum calcium, triglycerides, fasting glucose, HbA1c, ALT, ALP and GGT levels. Women in the lower and higher SUA strata had lower haemoglobin and cholesterol levels.
Over a median follow-up of 5.12 years (IQR, 3.06 to 6.59), there were 1,288 (4.9%) deaths among a cohort of 26,525 participants.
3.2 Serum uric acid and mortality in men
For men, crude death rates were greatest in the lowest (<238 µmol/L) and highest SUA categories (>535 µmol/L) at 26.8 and 29.5 deaths per 1000 person-years respectively compared with 8.3 deaths per 1000 person-years in the 357–416 µmol/L category (Table 3). In the unadjusted analysis, men in the lowest and highest strata experienced increased risk of mortality with HR 2.35 (1.65–3.14) and HR 2.52 (1.87–3.29) respectively compared to the referent group. (357–416 µmol/L) With adjustment for measures of anaemia, nutrition, liver and kidney function, the association was attenuated but the U-shaped pattern with mortality persisted (Table 3); HR 2.32 (1.53–3.27) for SUA < 238 µmol/L and HR 2.79 (1.91–4.02) for SUA > 535 µmol/L.
Table 3Relationship of Serum Uric Acid with All-Cause Mortality among Irish Men and Women in the Health System.
Men
Uric Acid Category
Conventional Units
<4 mg/dL
4-5 mg/dL
5-6 mg/dL
6-7 mg/dL
7-8 mg/dL
8-9 mg/dL
>9 mg/dL
SI Units
<238 µmol/L
238-297 µmol/L
297-357 µmol/L
357-416 µmol/L
416-476 µmol/L
476-535 µmol/L
>535 µmol/L
Observations
443
1,973
4,099
3,985
2,099
881
442
Person years
2015.8
9448.5
19388.3
18828.3
9816.6
3857.6
1900.4
Deaths
54
119
180
156
99
61
56
Crude Mortality rate per 1,000 pyrs.
26.8
12.6
9.3
8.3
10.1
15.8
29.5
Hazard Ratio for all-cause mortality (95% CI)
Unadjusted
2.35 (1.65-3.14)
1.3 (1.03-1.63)
1.05 (0.86-1.3)
1.00 (Reference)
1.12 (0.87-1.42)
1.5 (1.08-1.95)
2.52 (1.87-3.29)
Multivariate Adjusted a
2.32 (1.53-3.27)
1.24 (0.91-1.65)
1.19 (0.91-1.51)
1.00 (Reference)
1.25 (0.9-1.66)
1.34 (0.89-1.94)
2.79 (1.91-4.02)
Reduction in Median Survival Time, years (95% CI)
Unadjusted
−7.96 (-4.26, -11.32)
−2.43 (-0.17, -4.88)
−0.50 (1.77, -2.94)
0
−1.05 (1.65, -3.72)
−3.50 (-0.69, -6.18)
−8.70 (-5.41, -11.8)
Multivariate Adjusted a
−9.52 (-4.38, -15.53)
−2.31 (1.18, -7.22)
−1.82 (1.20, -6.82)
0
−2.40 (1.16, -7.09)
−3.20 (1.14, -8.63)
−11.69 (-7.27, -16.92)
Women
Uric Acid Category
Conventional Units
<3 mg/dL
3-4 mg/dL
4-5 mg/dL
5-6 mg/dL
6-7 mg/dL
7-8 mg/dL
>8 mg/dL
SI Units
<178µmol/L
178-238 µmol/L
238–297 µmol/L
297–357 µmol/L
357–416 µmol/L
416–476 µmol/L
>476 µmol/L
Observations
381
2,538
4,487
3,027
1,364
486
320
Person years
1768.0
12018.5
21143.8
14405.5
6612.0
2250.5
1390.7
Deaths
15
64
148
129
87
58
62
Crude Mortality rate per 1,000 pyrs.
8.5
5.3
7.0
9.0
13.2
25.8
44.6
Hazard Ratio for all-cause mortality (95% CI)
Unadjusted
1.46 (0.75-2.36)
0.96 (0.69-1.29)
1.03 (0.80-1.30)
1.00 (Reference)
1.07 (0.80-1.39)
1.79 (1.23-2.41)
1.89 (1.34-2.57)
Multivariate Adjusted a
1.77 (0.86-2.93)
1.15 (0.81-1.60)
1.17 (0.88-1.54)
1.00 (Reference)
1.15 (0.83-1.54)
1.69 (1.13-2.47)
1.59 (1.02-2.33)
Reduction in Median Survival Time, years (95% CI)
Unadjusted
−2.81 (2.61, -7.7)
0.43 (3.23, -2.12)
−0.19 (1.87, -2.35)
0
−0.45 (1.98, -2.78)
−4.73 (-1.58, -8.15)
−5.24 (-2.04, -8.98)
Multivariate Adjusted a
−5.98 (1.30, -13.84)
−1.60 (3.08, -8.28)
−1.85 (1.47, -8.28)
0
−1.70 (2.83, -8.28)
−5.90 (-0.97, -12.32)
−5.14 (0.00, -11.68)
Median survival time was determined by Cox regression estimate of the survival function using age as a time scale. Multivariate models a were adjusted for baseline covariates of eGFR, Cholesterol, Triglycerides, Haemoglobin, Albumin and Alanine Aminotransferase (ALT). Triglycerides and ALT were logarithmically transformed, haemoglobin and albumin were modelled as tertiles. To estimate the median reduction in lifetime's, the adjusted covariates were set to their mean values for continuous variables and the mode for categorical variables. SI; International System of Units.Sensitivity Analysis.
The estimated median age of survival for men in each stratum are shown in Fig. 2 and Table 3. Compared to the referent group, men in the lowest and highest strata had the lowest adjusted median ages of survival with a corresponding reduction in the median lifetime of 9.52 (4.38, 15.53) and 11.7 years (7.27, 16.92) respectively.
Fig. 2Estimated survival curves using age as time scale for the unadjusted association between SUA strata and all-cause mortality in men (a) and women (b). Estimated survival curves for the association between SUA strata and all-cause mortality in men (c) and women (d) adjusting for eGFR, Cholesterol, Triglycerides, Haemoglobin, Albumin & Alanine Aminotransferase. Triglycerides and ALT were logarithmically transformed, haemoglobin and albumin were modelled as tertiles. To estimate the median lifetime's, the adjusted covariates were set to their mean values for continuous variables and the mode for categorical variables.
When SUA was modelled as a continuous variable using penalised spline regression models, a non-linear U-shaped association persisted (p-value for test of linearity <0.001) (Fig. 3). This U‐shaped association between SUA levels with all‐cause mortality remained consistent after adjusting for confounding. In the fully adjusted model, the risk of mortality was significantly higher for SUA levels > 454 µmol/L with a HR of 1.15 (1.00–1.33) and for SUA levels <304 µmol/L with a HR of 1.12 (1.00–1.25) compared to a reference value of 370 µmol/L.
Fig. 3The unadjusted & multivariable-adjusted hazard ratios for all-cause mortality by serum uric acid level among Men and Women. The top panel contains the distribution of uric acid as a percentage of the population (Bindwidth=10 µmol/L. Solid line (—) denotes Hazard ratio and dash line (- - -) denotes 95% confidence intervals (CIs). Filled circles denote statistical significance (P<0.05) compared with the reference (blue circle). Estimates are based on unadjusted and adjusted penalised spline models for the association between SUA and all-cause mortality with age as the time scale. Hazard ratios were adjusted for eGFR, Cholesterol, Triglycerides, Haemoglobin, Albumin & Alanine Aminotransferase.
In women, unlike men, crude death rates were highest for patients with SUA levels in the 416-476 µmol/L and >476 µmol/L strata at 25.8 and 44.6 deaths per 1000 person-years. In the unadjusted analysis, these higher SUA groups had an elevated risk of mortality with HR 1.79 (1.23–2.41) and HR 1.89 (1.34–2.57) respectively compared to the referent (297–357 µmol/L); with adjustment, the association was attenuated with HR 1.69 (1.13–2.47) and HR 1.59 (1.02–2.33).
Fig. 2 and Table 3 illustrate the estimated survival curves and median age of survival for each strata group in women. Mirroring the hazard ratios, the 416–476 µmol/L and >476 µmol/L groups had the lowest adjusted median lifetimes with reductions of 5.9 years (0.97, 12.32) and 5.1 years (0.00, 11.68) respectively compared to the referent group.
When SUA was modelled as a continuous variable using penalised splines, the uric acid-mortality association was non-linear and followed a J-shaped pattern. With adjustment for confounding, the magnitude of the association was attenuated such that the risk of mortality was significantly elevated only for women with SUA values exceeding 409 µmol/L, HR 1.14 (1.00–1.40) compared to a reference value of 321 µmol/L.
3.4 Sensitivity Analysis
To explore the robustness of our results, we further examined whether the relationship between SUA and mortality differed by the presence of absence of CKD, where CKD was defined as eGFR less than 60 mL/min./1.73 m2). Elevated levels of SUA remained an independent risk factor for all-cause mortality in patients with and without CKD. For men with or without CKD the p-value for the interaction = 0.57, while for women the p-value for the interaction = 0.15.
4. Discussion
In this large population-based study within the Irish health system, we have demonstrated that SUA concentrations are associated with elevated mortality risk in men and in women. The pattern of association between SUA and mortality differed between sexes. For men, the shape of the association was predominantly U-shaped with significantly elevated risk of mortality at the extremes of SUA with thresholds of < 304 and > 454 µmol/L. For women, the pattern of association was J-shaped with elevated risk of mortality for SUA levels beyond 409 µmol/L. The patterns of risk were not explained following adjustment for a large number of cardio-metabolic and inflammatory indicators. The findings of the present study have a number of important clinical implications. First, it provides a detailed analysis of the shape of the mortality pattern in men and in women and suggests that sex-differences exist with regard to SUA associated-mortality risk and threshold values. Second, it describes the range of SUA levels associated with optimal survival for patients and for the first time highlights important reductions in survival times associated with values outside these ranges.
To the best of our knowledge, it remains unproven whether SUA is an independent risk factor for mortality and what specific threshold values if any are associated with elevated risk. In this cohort study, we explored this hypothesis among patients within the Irish health system while taking into consideration concurrent risks from a wide range of valid cardio-metabolic and renal indicators. Our analysis revealed significantly higher risks of mortality in men with SUA > 424 µmol/L and for women with SUA > 352 µmol/L in unadjusted models. Interestingly, these cut-points are comparable to published sex-specific cut-offs for defining hyperuricaemia in the general population [>416 (7 mg/dL) μmol/L in men and >357 μmol/L (6 mg/dL)) in women. With adjustment for a large set of metabolic biomarkers, the risks were marginally attenuated but nevertheless remained significant at thresholds of 454 µmol/L (7.6 mg/dL) and 409 µmol/L (6.9 mg/dL) for men and women, respectively. By adjusting for potential confounders and modelling SUA both as categorical [59.4 8 µmol/L (1 mg/dL) increments] and as a nonlinear continuous variable, our large cohort study confirmed that hyperuricemia was independently associated with mortality in both men and women. Whether these mortality risk thresholds extend to other specific patient populations warrants additional investigation. A recent study by Virdis et al reported a linear association of SUA with mortality and sex-specific thresholds of 321 μmol/L (5.4 mg/dL) and 279 μmol/L (4.7 mg/dL) in men and women respectively, values which were significantly lower than our reported thresholds [
]. We speculate that these reported differences in SUA thresholds for mortality between studies may reflect inherent differences in the underlying population at risk and the relative extent of adjustment for confounders.
To date studies of the relationship between SUA and mortality have yielded conflicting results and have fuelled debate to whether both low and high levels of SUA are deleterious to an individual's health [
Relationship between serum uric acid and mortality among hemodialysis patients: retrospective analysis of Korean end-stage renal disease registry data.
Gwag H Bin, Yang JH, Park T.K., et al. Uric Acid Level Has a U-shaped Association with Clinical Outcomes in Patients with Vasospastic Angina. 2017;16(12).
]. Among women, our findings confirm the presence of a J-shaped pattern of association suggesting that only high levels of SUA are deleterious to health. Despite adjustment for measures of kidney function, hyperlipidaemia, anaemia, serum albumin and surrogate markers of obesity, metabolic syndrome, and inflammation [
Kim C., Park J., Lee K., Kim J., Kim H. Association of serum γ -glutamyltransferase and alanine aminotransferase activities with risk of type 2 diabetes mellitus independent of fatty liver. 2009;(March 2008):64–69. doi:10.1002/dmrr.
Ko S., Baeg M.K., Han K., Ko S., Ahn Y. Increased liver markers are associated with higher risk of type 2 diabetes. 2015;21(24):7478–7487. doi:10.3748/wjg.v21.i24.7478.
], the mortality risks remained significant for women with elevated levels of SUA. For men, we observed a U-shaped association between SUA and mortality; even with adjustment for these core valid measures of cardio-metabolic dysregulation, higher mortality was also observed with low SUA levels. These patterns of association extend the findings of Cho et al, and Tseng et al reported in South Korean and Taiwanese cohorts [
Unlike previous published studies, this is the first study to yield detailed survival statistics for SUA concentrations among men and women. Importantly, we reveal that for Irish men in the health system, the median survival age was reduced by 9.5 and 11.7 years respectively for SUA values in the lowest and highest strata versus the normal range. Similarly, for women, we found that the median survival in the highest strata was reduced by 5 years compared to women with SUA in the normal range. Our study has drawn attention to the fact that extreme SUA levels are associated diminished patient survival taking other mortality risk factors into consideration. These findings might suggest that targeting SUA levels to normal ranges should be a principal goal to extend patient survival. However, whether this would confer an absolute survival benefit in all patient subgroups remains to be proven from appropriately designed clinical trials [
Whether uric acid contributes directly to mortality or is a surrogate of ambient disease remains an active area of debate as the factors often associated with low and high uric acid levels may independently contribute to death risk. As carefully designed clinical trials continue to explore the implications of lowering SUA levels with intensive urate lowering therapy on outcomes, we would caution against the unconditional lowering of SUA in the management for hyperuricemia [
]. We suggest that optimal SUA levels should fall between 304 and 454 µmol/L for men and below 409 µmol/L for women as these ranges were associated with the greatest survival.
The relative contribution of uric acid's antioxidant properties and its role in endothelial dysfunction may explain the U or J-shaped association between SUA levels and mortality observed in this study. It has been reported that increased SUA levels are associated with increased anti-oxidant capacity [
]. However, these protective, antioxidant effects may be overwhelmed by other, more harmful, effects of serum uric acid at markedly elevated levels. Oxidative stress with activation of the renin–angiotensin system in human vascular endothelial cells is a key mechanism of uric acid induced endothelial dysfunction [
Gwag H Bin, Yang JH, Park T.K., et al. Uric Acid Level Has a U-shaped Association with Clinical Outcomes in Patients with Vasospastic Angina. 2017;16(12).
]. High levels of uric acid may contribute to high mortality through direct injury to the endothelium, local and systemic vasoconstriction, secondary hypertension and progressive kidney disease [
]. Previous studies have linked elevations in inflammatory markers to elevated SUA levels. Uric acid may induce both endothelial dysfunction and vascular inflammation, which concomitantly may lead to accelerated atherosclerosis [
]. Several explanations have been proposed to elucidate a potential association between low levels of serum uric acid and mortality. Recent evidence suggests that low SUA may be a marker for poor nutritional status in certain populations [
]. Interestingly, in our study, low SUA levels were associated with a higher proportion of cancer-related mortality whereas high SUA levels were associated with higher proportion of cardiovascular-related mortality (Supplementary Figures 1 & 2.) Patients with cancer often suffer from poor nutrition, therefore, it is plausible that protein-energy wasting resulted in both low SUA levels and higher mortality among these patients. The link between low SUA and mortality may parallel that of deficiencies of antioxidant and anti-inflammatory vitamins C and D [
]. Depleted levels may enhance susceptibility to a range of age-related diseases and increase mortality risk. Therefore, paradoxically, the opposing oxidant-antioxidant properties of uric acid may explain both the U and J-shaped associations between SUA levels and mortality. Future investigations are needed to assess the biological mechanisms that may clarify the link between uric acid levels, disease progression and subsequent mortality risk.
This study has several limitations. First, we did not adjust for lifestyle factors including diet, smoking, alcohol use, physical activity and medication history, although many of these are likely to influence the clinical biomarkers included in our analysis. Data on urate-lowering medications were not available. We used a single assessment of uric acid levels at baseline and did not incorporate changes in uric acid or other changes in lifestyle factors and covariates during follow-up. Fluctuations in uric acid are multifactorial: body mass index, waist circumference, blood pressure, insulin resistance, renal disease, diet, medication use, and genetic factors are all known to contribute to the variability of uric acid levels. Elevated SUA levels are closely related to increased BMI, which is also significantly associated with various CVD risk factors which cause endothelial dysfunction, depleted vasomotor reactivity and arterial stiffness. Such pathophysiology induced by increased BMI may be greater than that of elevated SUA levels. Finally, the subjects included in this study were Irish men and women who received healthcare within the Irish health system and may not be generalisable to other populations. The estimation of the median age of survival assumes that age-specific mortality rates in the future will be similar to those today. Although it represents the best information available to us currently, it does not consider recent and future improvements in care and treatment that will impact survival.
Despite these limitations, the present study had several strengths. This is the first large-scale cohort study to examine the association of SUA level with all-cause mortality in the Irish health system. Utilisation of a 26, 525 patient cohort, comprising of a high proportion of middle aged and elderly patients with an 8-year study period provided adequate statistical power for the analysis of long-term mortality outcomes. Date of death was accurately identified from the Central Statistics Office Registry and the survival status of all participants was recorded. Using sex stratifications and providing SUA levels using strata and as a non-linear continuum, our findings are more applicable to clinical knowledge and decision making by providing reference ranges relevant to an Irish context, and will allow clinically sensible cut-points to be compared between different studies.
5. Conclusion
This study provides evidence to support non-linear associations of SUA with mortality in men and women in the Irish health system. Patients with extreme values of SUA contribute to mortality and to shortened life spans. The range of SUA values associated with greatest survival benefit and lowest mortality risk was observed between 304-454 µmol/l for men and below 409 µmol/l for women. Given that the incidence and clinical presentations for cardiometabolic diseases differ across the life course of men and women, SUA may play a role as a prognostic indicator to aid screening.
Authors’ contributions
F.J, L.D.B and K.B conducted data analyses for this study. A.G.S had full access to the study data and the analyses. C.W, F.P.R, P.R contributed to the investigation, review and editing of this study. All authors reviewed the manuscript and signed off on its accuracy.
Funding
This study is funded by the Health Research Board (HRA-2013-PHR-437 and HRA-2014-PHR-685), the Midwest Research and Education Foundation (MKid), and an unrestricted educational grant from the Menarini International Operations Luxemburg. F.J. is supported by the Irish Research Council.
Declaration of Competing Interest
The authors declare they have no competing interests.
Acknowledgments
The data in this study is collected by the Data Coordinating Centre at the University of Limerick with permission from the Health Services Executive (HSE), and the Central Statistics Office (CSO). We thank the HSE, CSO and the National Renal Office (NRO) for their unwavering support in this national initiative. Results are based on analysis of strictly controlled Research Microdata Files provided by the CSO. The CSO does not take any responsibility for the views expressed or the outputs generated from this research.
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Increased serum uric acid level predicts poor prognosis in mildly severe chronic heart failure with reduced ejection fraction. An analysis from the MECKI score research group.
Relationship between serum uric acid and mortality among hemodialysis patients: retrospective analysis of Korean end-stage renal disease registry data.
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Gwag H Bin, Yang JH, Park T.K., et al. Uric Acid Level Has a U-shaped Association with Clinical Outcomes in Patients with Vasospastic Angina. 2017;16(12).
Kim C., Park J., Lee K., Kim J., Kim H. Association of serum γ -glutamyltransferase and alanine aminotransferase activities with risk of type 2 diabetes mellitus independent of fatty liver. 2009;(March 2008):64–69. doi:10.1002/dmrr.
Ko S., Baeg M.K., Han K., Ko S., Ahn Y. Increased liver markers are associated with higher risk of type 2 diabetes. 2015;21(24):7478–7487. doi:10.3748/wjg.v21.i24.7478.
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