Serum uric acid-to-creatinine ratio as a predictor for the severity of coronary artery lesions
Authors: Tingfen Wang, Tingyu Wang, Runfeng Zhang
Published: 2026

ABSTRACT
AbstractObjectiveThis study aimed to explore the correlation between the serum uric acid-to-creatinine ratio (SUA/Scr) and the severity of coronary artery lesions in coronary heart disease (CHD) patients, and evaluate its predictive value for lesion severity.ResultsAmong 528 CHD patients, SUA/Scr showed a stepwise increase with worsening coronary lesion severity, with significant differences in all pairwise comparisons (all P < 0.05). Multivariate logistic regression revealed SUA/Scr as an independent risk factor for severe lesions (OR = 101.844, 95% CI 29.076 ~ 356.726, P < < 0.001). ROC analysis demonstrated superior predictive efficacy of SUA/Scr (AUC = 0.840, cutoff 5.35, sensitivity 80.60%, specificity 75.20%) compared to SUA or Scr alone. SUA/Scr is closely associated with coronary lesion severity and serves as an independent predictor with valuable clinical utility.Keywords: Coronary artery lesions, Serum uric acid-to-creatinine ratio, Predictive value

Introduction

Coronary heart disease (CHD) is a leading cause of death worldwide, with its core pathological basis being coronary artery stenosis caused by atherosclerosis. The severity of coronary lesions directly determines treatment strategies and prognostic outcomes [1]. Early and accurate assessment of lesion severity is of great clinical significance for optimizing treatment plans and reducing the risk of adverse cardiovascular events. Currently, coronary angiography is the gold standard for evaluating lesion severity, but it has limitations such as invasiveness and high cost. Thus, there is an urgent need to identify convenient, non-invasive biomarkers for auxiliary assessment.

Atherosclerosis is essentially a chronic inflammatory process [2]. As the end product of purine metabolism, serum uric acid (SUA) contributes to atherosclerosis by inducing oxidative stress and activating inflammatory cascades such as the NLRP3 inflammasome, and has been confirmed to be positively associated with the development and progression of coronary lesions [3]. However, SUA levels are easily affected by renal function—impaired renal function often leads to elevated SUA. Serum creatinine (Scr) is a classic indicator of renal function, and the derived metabolic marker SUA/Scr can correct for the impact of renal function on uric acid excretion, more objectively reflecting the net uric acid production level [4]. Nevertheless, research on the correlation between SUA/Scr and the severity of coronary lesions remains limited. Therefore, this study aims to explore the association between SUA/Scr and coronary lesion severity, analyze its predictive value, and provide a new reference for early risk stratification and clinical assessment of CHD.

Materials and methods

Study population

This was a retrospective cross-sectional study, all data were collected from medical records without follow-up.enrolled 528 patients diagnosed with CHD who underwent their first coronary angiography in the Department of Cardiovascular Medicine, Mianyang Third People’s Hospital, from January to December 2023. Among them, 335 were male and 193 were female. General data (e.g., age, history of hypertension) and biochemical indicators (e.g., renal function, blood lipids) were extracted from medical records.

Inclusion criteria: ① Age ≥ 18 years; ② Hospitalized due to myocardial ischemia symptoms such as chest pain or tightness and underwent the first coronary angiography; ③ Meets the diagnostic criteria for CHD: at least one major coronary artery or its main branch with stenosis ≥ 50% confirmed by coronary angiography [5]; ④ Completed the included biochemical tests before angiography; ⑤ Complete clinical data.

Exclusion criteria: ① Complicated with other cardiovascular diseases such as valvular heart disease or congenital heart disease; ② Suffering from severe infectious diseases or having a history of kidney transplantation; ③ History of myocardial infarction, cardiac surgery within 3 months, or previous coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI); ④ Used drugs affecting uric acid, blood lipids, or renal function within 7 days before admission; ⑤ Other conditions affecting inflammation or hemodynamic status.

Data collection

General data

Including gender, age, smoking history (defined as smoking > 1 cigarette per day for more than 1 year), history of hypertension, and history of hyperlipidemia.

Laboratory data

Biochemical indicators measured for the first time after admission, including SUA, Scr, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). The SUA/Scr ratio was calculated as SUA (µmol/L) divided by Scr (µmol/L).

Coronary angiography results

Evaluated by at least two experienced interventional cardiologists. The Gensini score was used to assess the severity of coronary lesions, calculated as: Gensini score = basic score for stenosis degree × weight coefficient for stenosis location, with the total score being the sum of scores for all lesions. A higher score indicates more severe lesions [6]. The specific scoring criteria are shown in Table 1.

Table 1Gensini scoring criteriaStenosis degreeBasic scoreStenosis locationWeight coefficient≤ 25%1Left main coronary artery5.0> 25% to ≤ 50%2Proximal left anterior descending artery or proximal circumflex artery2.5> 50% to ≤ 75%4Mid left anterior descending artery1.5> 75% to ≤ 90%8Distal left anterior descending artery or distal circumflex artery1.0> 90% to ≤ 99%16Right coronary artery, first diagonal branch, obtuse marginal branch, posterior descending artery1.0Occlusion32Second diagonal branch, posterior lateral branch0.5

Gensini scoring criteria

Statistical analysis

SPSS 27.0 statistical software was used for data analysis, with a significance level of α = 0.05 (P < 0.05 was considered statistically significant). Categorical data (e.g., proportion of males, prevalence of hypertension/hyperlipidemia/smoking) were expressed as “n (%)” and compared using the Pearson χ² test. Continuous data (e.g., age, SUA, Scr, SUA/Scr) were tested for normality using the Shapiro–Wilk test. Given the relatively large sample size, the Kolmogorov–Smirnov test was additionally applied to validate the normality assumption. All variables showed a non-normal distribution and were therefore expressed as median (interquartile range). Intergroup comparisons were performed using non-parametric tests: Kruskal-Wallis H test for overall comparisons, and Mann-Whitney U test with Bonferroni correction for pairwise comparisons.

Results

Comparison of clinical data among the three groups

Overall intergroup comparisons showed that with the progression of lesion severity from mild to severe, SUA, SUA/Scr, BNP, and CTnl levels increased gradually, with statistically significant differences (all P < 0.05). However, there were no significant differences in gender composition, prevalence of hypertension/hyperlipidemia/smoking, age, Scr, LDL-C, HDL-C, TG, or TC among the three groups (all P ≥ 0.05) (Table 2).

Table 2Comparison of clinical indicators among patients with different coronary lesion severitiesClinical indicatorMild lesion group(n = 156)Moderate lesion group(n = 155)Severe lesion group(n = 217)Test statistic(χ²/H)P ValueMale [n (%)]95 (60.9%)93 (60.0%)148 (68.2%)3.350.19History of hypertension [n (%)]101 (64.7%)94 (60.6%)133 (61.3%)0.660.72History of hyperlipidemia [n (%)]62 (39.7%)58 (37.4%)85 (39.2%)0.200.91Smoking history [n (%)]63 (40.4%)54 (34.8%)100 (46.1%)4.770.09Age (years)69.00 (58.00, 75.00)69.00 (59.00, 77.00)70.00 (57.00, 76.00)4.540.80SUA (µmol/L)332.00 (267.25, 398.75)346.50 (287.00, 417.00)392.50 (315.25, 448.50)100.00< 0.001Scr (µmol/L)64.50 (55.00, 80.00)64.00 (56.50, 75.00)68.00 (57.00, 78.00)2.570.28SUA/Scr (µmol/L per µmol/L)4.74 (4.24, 5.74)5.26 (4.68, 6.32)6.12 (5.01, 7.25)173.11< 0.001LDL-C (mmol/L)2.5650 (1.97, 3.43)2.7200 (2.06, 3.45)2.8100 (2.08, 3.51)2.330.31HDL-C (mmol/L)1.1100 (0.91, 1.36)1.0700 (0.89, 1.33)1.0200 (0.85, 1.26)6.000.05TG (mmol/L)1.4950 (1.03, 2.34)1.4000 (0.97, 2.07)1.3800 (0.94, 2.11)1.530.47TC (mmol/L)4.2450 (3.60, 5.16)4.2800 (3.56, 5.13)4.3900 (3.77, 5.18)2.630.27BNP (ng/L)218.24 (68.96, 1384.14)247.38 (99.24, 864.48)526.80 (189.64, 1248.32)54.61< 0.001CTnl (ng/L)52.86 (7.93, 4068.94)209.28 (16.38, 1081.75)325.60 (42.18, 1560.90)81.23< 0.001

Comparison of clinical indicators among patients with different coronary lesion severities

Pairwise comparisons of indicators among groups

To further clarify the characteristics of indicator differences among groups, pairwise comparisons (mild vs. moderate, mild vs. severe, moderate vs. severe) were performed using the Mann-Whitney U test with Bonferroni correction (corrected α = 0.05/12 ≈ 0.0042). The results showed that SUA/Scr, BNP, and CTnl had statistically significant differences in all pairwise comparisons (all P < 0.0042 after correction). SUA showed significant differences between the mild vs. severe and moderate vs. severe groups (both P < 0.0042 after correction), but no significant difference between the mild vs. moderate groups , indicating that the significant increase in SUA mainly occurs during the progression from moderate to severe lesions (Table 3).

Table 3Statistical results of pairwise comparisons of indicators among different coronary lesion severity groupsComparison groupIndicatorMann-Whitney U valueWilcoxon W valueZ valueCorrected Asymptotic Significance(Two-Tailed)Mild vs. ModerateSUA (µmol/L)11,53423,780– 7.010.483SUA/Scr9044.521290.5– 3.841< 0.001BNP (ng/L)10,05322,299– 2.5690.01CTnl (ng/L)8691.520937.5– 4.293< 0.001Mild vs. SevereSUA (µmol/L)836020,606– 8.34< 0.001SUA/Scr536917,615– 11.251< 0.001BNP (ng/L)956121,807– 7.171< 0.001CTnl (ng/L)775019,996– 8.954< 0.001Moderate vs. SevereSUA (µmol/L)814620,236– 8.481< 0.001SUA/Scr6112.518202.5– 10.47< 0.001BNP (ng/L)12202.524292.5– 4.514< 0.001CTnl (ng/L)12313.524403.5– 4.417< 0.001

Statistical results of pairwise comparisons of indicators among different coronary lesion severity groups

Further grouped comparisons

Based on pairwise comparison results, SUA showed no significant difference between the mild and moderate groups, while core indicators such as SUA/Scr, BNP, and CTnl exhibited gradient differences across all groups. Additionally, the significant increase in SUA began during the progression from moderate to severe lesions, indicating high homogeneity in indicator characteristics between mild and moderate lesions. Therefore, the mild and moderate lesion groups were merged into the mild-to-moderate lesion group for subsequent comparative analysis with the severe lesion group.

Based on pairwise comparison results, SUA showed no significant difference between the mild and moderate groups, while core indicators such as SUA/Scr, BNP, and CTnl exhibited gradient differences across all groups. Additionally, the significant increase in SUA began during the progression from moderate to severe lesions, indicating high homogeneity in indicator characteristics between mild and moderate lesions. Therefore, the mild and moderate lesion groups were merged into the mild-to-moderate lesion group for subsequent comparative analysis with the severe lesion group.

There were no significant differences in the proportion of males, smoking rate, age, Scr, LDL-C, TG, TC, or HDL-C between the mild-to-moderate and severe lesion groups (all P > 0.05). However, SUA, SUA/Scr, BNP, and CTnl showed statistically significant differences (all P < 0.05) (Table 4).

There were no significant differences in the proportion of males, smoking rate, age, Scr, LDL-C, TG, TC, or HDL-C between the mild-to-moderate and severe lesion groups (all P > 0.05). However, SUA, SUA/Scr, BNP, and CTnl showed statistically significant differences (all P < 0.05) (Table 4).

Table 4Comparison of clinical data between mild-to-moderate and severe coronary lesion groupsClinical IndicatorMild-to-Moderate Lesion Group(n = 311)Severe Lesion Group(n = 217)Test Statistic(χ²/Z)P ValueMale [n (%)]188 (60.5%)148 (68.2%)3.320.068History of hypertension [n (%)]195 (62.7%)133 (61.3%)1.080.742History of hyperlipidemia [n (%)]120 (38.6%)85 (39.2%)0.0180.892Smoking history [n (%)]117 (37.6%)100 (46.1%)3.7810.052Age (years)69.00 (58.00, 76.00)70.00 (57.00, 76.00)– 0.1280.898SUA (µmol/L)332.00 (267.25, 398.75)392.50 (315.25, 448.50)– 9.994< 0.001Scr (µmol/L)64.50 (55.00, 80.00)68.00 (57.00, 78.00)– 1.4870.137SUA/Scr (µmol/L per µmol/L)4.74 (4.24, 5.74)6.12 (5.01, 7.25)– 12.907< 0.001LDL-C (mmol/L)2.5650 (1.97, 3.43)2.8100 (2.08, 3.51)– 1.3090.19HDL-C (mmol/L)1.1100 (0.91, 1.36)1.0200 (0.85, 1.26)– 1.7640.078TG (mmol/L)1.4950 (1.03, 2.34)1.3800 (0.94, 2.11)– 0.5120.609TC (mmol/L)4.2450 (3.60, 5.16)4.3900 (3.77, 5.18)– 1.6130.107BNP (ng/L)218.24 (68.96, 1384.14)526.80 (189.64, 1248.32)– 6.946< 0.001CTnl (ng/L)52.86 (7.93, 4068.94)325.60 (42.18, 1560.90)– 7.946< 0.001

Comparison of clinical data between mild-to-moderate and severe coronary lesion groups

Multivariate l

After adjusting for confounding factors such as BNP and CTnl (both significant influencing factors of coronary lesions), multivariate binary logistic regression analysis showed that only SUA/Scr had an independent and significant positive association with coronary lesion severity, being an independent risk factor for severe coronary lesions . In contrast, the potential associations of SUA and Scr when included alone in the model were likely interfered by BNP, CTnl, and each other, and were not statistically significant after correction . This suggests that compared with single indicators (SUA or Scr), SUA/Scr more stably reflects the severity of coronary lesions and can serve as an important reference indicator for assessing the risk of progression to severe coronary lesions (Table 5).

After adjusting for confounding factors such as BNP and CTnl (both significant influencing factors of coronary lesions), multivariate binary logistic regression analysis showed that only SUA/Scr had an independent and significant positive association with coronary lesion severity, being an independent risk factor for severe coronary lesions . In contrast, the potential associations of SUA and Scr when included alone in the model were likely interfered by BNP, CTnl, and each other, and were not statistically significant after correction . This suggests that compared with single indicators (SUA or Scr), SUA/Scr more stably reflects the severity of coronary lesions and can serve as an important reference indicator for assessing the risk of progression to severe coronary lesions (Table 5).

Table 5Multivariate binary logistic regression analysis of SUA, Scr, and SUA/Scr with severe coronary lesions after correcting for BNP and CTnlIndicatorB valueStandard errorWald statisticDegrees of freedomSignificanceOR Value95% Confidence Interval95% Confidence intervalLower boundUpper boundSUA1.1020.8111.84510.1743.010.61414.762Scr– 0.3610.9961.13110.7170.6970.0994.906SUA/Scr4.6230.6452.2591< 0.001101.84429.076356.726

Multivariate binary logistic regression analysis of SUA, Scr, and SUA/Scr with severe coronary lesions after correcting for BNP and CTnl

ROC curve analysis of different factors for diagnosing severe coronary lesions

ROC curve analysis was used to evaluate the predictive efficacy of SUA, Scr, and SUA/Scr for severe coronary lesions. The results showed (Table 6; Fig. 1) that the AUC of SUA/Scr was 0.840 (95% CI 0.805~0.875, P<0.05), which was significantly higher than that of SUA( AUC= 0.787, 95% CI 0.749~0.825, P<0.05) and Scr, AUC= 0.690, 95% CI 0.644~736, P<0.05.

ROC curve analysis was used to evaluate the predictive efficacy of SUA, Scr, and SUA/Scr for severe coronary lesions. The results showed (Table 6; Fig. 1) that the AUC of SUA/Scr was 0.840 (95% CI 0.805~0.875, P<0.05), which was significantly higher than that of SUA( AUC= 0.787, 95% CI 0.749~0.825, P<0.05) and Scr, AUC= 0.690, 95% CI 0.644~736, P<0.05.

Further determination of the optimal cutoff value and corresponding efficacy for each indicator showed that the optimal cutoff value of SUA/Scr was 5.35, with a sensitivity of 80.60% and specificity of 75.20%, and the predictive efficacy was rated as “excellent”. The optimal cutoff value of SUA was 357.00 µmol/L, with a sensitivity of 72.80% and specificity of 68.20%, and the predictive efficacy was rated as “good”. The optimal cutoff value of Scr was 64.00 µmol/L, with a sensitivity of 51.20% and specificity of 50.50%, and the efficacy was rated as “fair”.

Further determination of the optimal cutoff value and corresponding efficacy for each indicator showed that the optimal cutoff value of SUA/Scr was 5.35, with a sensitivity of 80.60% and specificity of 75.20%, and the predictive efficacy was rated as “excellent”. The optimal cutoff value of SUA was 357.00 µmol/L, with a sensitivity of 72.80% and specificity of 68.20%, and the predictive efficacy was rated as “good”. The optimal cutoff value of Scr was 64.00 µmol/L, with a sensitivity of 51.20% and specificity of 50.50%, and the efficacy was rated as “fair”.

These results suggest that compared with SUA and Scr, SUA/Scr has superior predictive value for severe coronary lesions and can serve as a potential biological indicator for evaluating the severity of coronary lesions in clinical practice.

These results suggest that compared with SUA and Scr, SUA/Scr has superior predictive value for severe coronary lesions and can serve as a potential biological indicator for evaluating the severity of coronary lesions in clinical practice.

Table 6ROC curve analysis of SUA, Scr, and SUA/Scr for predicting severe coronary lesionsVariableAUCP Value95% CIOptimal cutoff valueSpecificity (%)Sensitivity (%)SUA/Scr0.84< 0.050.805 ~ 0.8755.3575.2080.60SUA0.787< 0.050.749 ~ 0.825357.00 µmol/L68.2072.80Scr0.69< 0.050.644 ~ 0.73664.00 µmol/L50.5051.20

ROC curve analysis of SUA, Scr, and SUA/Scr for predicting severe coronary lesions

ROC curves of SUA, Scr, and SUA/Scr for predicting severe coronary lesions

Discussion

In this study of 528 CHD patients, we found that the SUA/Scr ratio was closely associated with the severity of coronary artery lesions and served as an independent predictor of severe lesions. Unlike SUA alone, which failed to distinguish between mild and moderate lesions, SUA/Scr showed a significant stepwise increase across all three Gensini score categories, with statistically significant differences in pairwise comparisons among the three groups. The area under the ROC curve for SUA/Scr (0.840) was significantly higher than that for SUA (0.787) and Scr (0.690), indicating its superior discriminatory ability. In contrast, SUA only showed significant differences between the severe lesion group and the mild/moderate lesion groups, with no statistical difference between the mild and moderate lesion groups. This suggests that SUA/Scr has better discriminatory ability for coronary lesion severity than SUA, especially reflecting differences in the early stage of lesions (progression from mild to moderate), which provides a key reference for the early risk screening and identification of CHD. Meanwhile, Scr showed no significant difference among groups with different lesion severities, further confirming that simple renal function indicators are difficult to reflect the severity of coronary lesions [7].

Multivariate binary logistic regression analysis further verified the independent predictive value of SUA/Scr. After adjusting for known influencing factors of coronary lesions such as BNP and CTnl, SUA/Scr remained an independent risk factor for severe coronary lesions, while the predictive effects of SUA and Scr alone were not statistically significant. This result indicates that compared with single indicators, SUA/Scr is less interfered by other confounding factors, and its association with coronary lesions is more stable, making it a reliable indicator for assessing the risk of progression to severe coronary lesions.

Comparison with previous studies.Our findings are consistent with existing literature. Ting-Ting Tian et al. demonstrated that serum uric acid was an independent risk factor for early-onset CHD and positively correlated with Gensini score [8]. Ayca Gumusdag et al. showed that SUA/Scr independently predicted 30-day major adverse cardiovascular and cerebrovascular events (MACCEs) in ST-segment elevation myocardial infarction (STEMI) patients [9]. Notably, Kalyoncuoglu and Gumusdag identified an optimal SUA/Scr cut-off of 5.34 for predicting no-reflow phenomenon in non-ST-segment elevation acute coronary syndrome (NSTE-ACS) patients, which is remarkably close to our cut-off of 5.35 [10]. Babak Bagheri et al. reported that while serum creatinine was associated with CHD prevalence, this association was not independent after adjustment, aligning with our finding that Scr alone has limited predictive value (AUC = 0.690) [11]. Collectively, these studies support SUA/Scr as a reliable biomarker for risk stratification inCHD patients.

Atherosclerosis is closely related to metabolic disorders [12]. As the end product of purine metabolism, SUA has been confirmed to promote vascular endothelial injury, lipid deposition, and plaque formation through mechanisms such as inducing oxidative stress and activating the NLRP3 inflammasome, and is closely associated with the occurrence and development of coronary lesions [13]. However, SUA levels are easily affected by renal function—impaired renal function can lead to pseudohyperuricemia, making the assessment of coronary lesions using SUA alone significantly limited. Scr is a classic indicator of glomerular filtration function, and SUA/Scr, constructed based on both, can correct for the interference of renal function on uric acid excretion, more objectively reflecting the net uric acid production level in the body and providing a new perspective for evaluating the association between metabolic disorders and coronary lesions [14, 15].

Limitations

This study has certain limitations: first, it is a single-center retrospective design, and the sample source has geographical limitations, which may lead to selection bias. Future multi-center, prospective studies are needed to further verify the reliability of the conclusions; second, the study did not include potential influencing factors such as uric acid metabolism-related gene polymorphisms (e.g., ABCG2 gene) and lifestyle factors (e.g., alcohol consumption, high-purine diet), which may interfere with the association analysis between SUA/Scr and coronary lesions.

In conclusion, this study confirms that SUA/Scr is closely associated with the severity of coronary lesions in CHD patients and serves as an independent predictor of severe coronary lesions, with significantly superior predictive efficacy compared to SUA or Scr alone. The detection of SUA/Scr is convenient and low-cost, and it is expected to be used as a new biological marker for clinical evaluation of coronary lesion severity, providing important reference for early warning, risk stratification, and the development of individualized prevention and treatment strategies for CHD. Future studies should further carry out large-sample, long-term follow-up prospective research to clarify the value of SUA/Scr in CHD prognosis assessment and explore the feasibility of its guiding clinical intervention.

Author contributions

Tingfen Wang: Conceptualization, Methodology, Data curation, Formal analysis, Writing - Original DraftTingyu Wang: Investigation, Data curation, ValidationRunfeng Zhang: Conceptualization, Supervision, Writing - Review & EditingAll authors have read and approved the final manuscript and take full responsibility for the integrity and accuracy of the data presented.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This retrospective study using anonymized clinical data was approved by the Ethics Committee of Mianyang Third People’s Hospital (Approval No. 2026-Shen-06). The requirement for informed consent was waived by the Ethics Committee due to the retrospective design and use of de-identified data, in accordance with the Ethical Review Measures for Life Science and Medical Research Involving Humans and the Declaration of Helsinki. All experiments were performed in accordance with relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

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References

Associated Data

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.