Serum uric acid/creatinine ratio provides insights into the severity of coronary artery lesions and emerges as a potential predictor

Serum uric acid/creatinine ratio provides insights into the severity of coronary artery lesions and emerges as a potential predictor | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Serum uric acid/creatinine ratio provides insights into the severity of coronary artery lesions and emerges as a potential predictor Tingfen Wang, Tingyu Wang, Runfeng Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9040816/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: With changes in lifestyle, the incidence of chronic metabolic diseases and cardiovascular diseases has increased year by year, posing a major public health threat to human health. Coronary heart disease (CHD) is one of the most common cardiovascular diseases in clinical practice, with its mortality rate consistently ranking among the highest globally. Therefore, timely and accurate assessment of coronary artery lesions play a crucial role in reducing mortality and improving prognosis in CHD patients. Objective: To investigate the correlation between the serum uric acid-to-creatinine ratio (SUA/Scr) and the severity of coronary artery disease, and to evaluates its potential clinical value in predicting disease severity and risk stratification. This study aims to provide experimental evidence and theoretical support for early warning, disease assessment, and the development of individualized prevention and treatment strategies for CHD. Methods: This retrospective study included 528 patients with CHD who underwent initial coronary angiography due to chest pain or chest tightness at the Department of Cardiovascular Medicine, Mianyang Third People's Hospital, from January and December 2023. Gensini scores were calculated based on coronary angiography results, and patients were divided into three groups: mild lesion group (Gensini score < 20, n=156), moderate lesion group (20 ≤ Gensini score < 40, n=155), and severe lesion group (Gensini score ≥ 40, n=217). General clinical data and biochemical indicators were collected, and the SUA/Scr ratio were calculated. Differences in SUA, Scr, and SUA/Scr among the three groups were compared. Multivariate ordinal logistic regression analysis was used to identify independent risk factors for coronary lesions. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive efficacy of SUA, Scr, and SUA/Scr for moderate-to-severe coronary lesions. Results: Intergroup comparisons showed no significant difference in Scr levels among the three groups ( P > 0.05). No significant difference in SUA levels was observed between the mild and moderate lesion groups ( P > 0.05); however, SUA levels in both groups were significantly lower than those in the severe lesion group (both P < 0.05). In contrast, the SUA/Scr ratio progressively increased with the severity of coronary lesions, and pairwise comparisons among the three groups (all P < 0.05). Multivariate binary logistic regression analysis revealed that, after adjusting for confounding factors, SUA/Scr ratio remained an independent risk factor for severe coronary lesions, with OR=101.844, P < 0.05. ROC curve analysis showed that the area under the curve (AUC), optimal cutoff value, sensitivity, and specificity of SUA/Scr were 0.840, 5.35, 80.60%, and 75.2%, respectively—values that were all higher than those obtained when SUA or Scr was used individually. Conclusion: SUA/Scr ratio is closely associated with the severity of coronary artery lesions in CHD patients and serves as an independent predictor of coronary artery disease, holding significant clinical value in assessing the severity of coronary lesions. Coronary artery lesions Serum uric acid-to-creatinine ratio Predictive value Figures Figure 1 Introduction Coronary heart disease (CHD) is one of the leading causes of death worldwide, with its core pathological feature being coronary artery stenosis caused by atherosclerosis. The extent of coronary lesions directly determines treatment strategies and prognostic outcomes [ 1 ] . Early and accurate assessment of disease severity holds significant clinical importance for optimizing treatment strategies and reducing the risk of adverse cardiovascular events. Currently, coronary angiography is the gold standard for evaluating the severity of coronary lesion, but it has limitations such as invasiveness and high cost. Thus, there is an urgent need to identify convenient, non-invasive biomarkers to assist in evaluation. Atherosclerosis is fundamentally a chronic inflammatory process [ 2 ] . As the product of purine metabolism, serum uric acid (SUA) promotes the development and progression of atherosclerosis through inflammatory cascades of the NLRP3 inflammasome, and has been confirmed to be positively associated with the occurrence and progression of coronary lesions [ 3 ] . However, SUA levels are susceptible to renal function—impaired renal function often leads to elevated SUA levels. Serum creatinine (Scr) is a classic indicator for assessing renal function, and the metabolic ratio of SUA/Scr derived from it can correct for the impact of renal function on uric acid excretion, thereby more objectively reflecting the production level of net uric acid [ 4 ] . Nevertheless, research on the correlation between SUA/Scr ratio and the severity of coronary lesions remains limited. Therefore, this study aims to explore the correlation between SUA/Scr ratio and the severity of coronary lesion, analyze its predictive value, and provide new reference evidence for early risk stratification and clinical assessment of CHD. Materials and Methods 1. Study Population This retrospective study included 528 patients with CHD who underwent coronary angiography for the first time at 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 initial coronary angiography; ③ Meeting the diagnostic criteria for CHD: at least one segment of major coronary artery or branch of the coronary showing stenosis ≥ 50% confirmed by coronary angiography [ 5 ] ; ④ Completed required biochemical tests before angiography; ⑤ Complete clinical data. Exclusion criteria: ① Coexisting other cardiovascular diseases, such as valvular heart disease or congenital heart disease; ② History of severe infectious diseases or renal transplantation; ③ History of myocardial infarction, cardiac surgery within 3 months, or previous coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI); ④ Use of medications affecting uric acid, blood lipids, or renal function within 7 days before admission; ⑤ Other conditions that may influence inflammatory status or hemodynamic condition. 2. Data Collection 2.1 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. 2.2 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). 2.3 Coronary Angiography Results Evaluated by at least two experienced interventional cardiologists. The severity of coronary artery lesions was evaluated using the Gensini score, calculated as: Gensini score = basic score for stenosis degree × weight coefficient for stenosis location; the total score is the sum of scores for all lesions. Higher scores indicate more severe lesions [ 6 ] . Detailed scoring criteria are presented in Table 1 . Table 1 Gensini Scoring Criteria Stenosis Degree Basic Score Stenosis Location Weight Coefficient ≤ 25% 1 Left main coronary artery 5.0 > 25% to ≤ 50% 2 Proximal left anterior descending artery or proximal circumflex artery 2.5 > 50% to ≤ 75% 4 Mid left anterior descending artery 1.5 > 75% to ≤ 90% 8 Distal left anterior descending artery or distal circumflex artery 1.0 > 90% to ≤ 99% 16 Right coronary artery, first diagonal branch, obtuse marginal branch, posterior descending artery 1.0 Occlusion 32 Second diagonal branch, posterior lateral branch 0.5 3. Statistical Analysis Data analysis was performed using SPSS 27.0 statistical software, with a significance level set at 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 \((\text{e.g.,}\text{}\text{age,}\text{}\text{SUA,}\text{}\text{Scr,}\text{}\text{SUA/Scr}\) ) were first assessed for normality using the Shapiro-Wilk test. Since all data failed to follow a normal distribution, they were presented as "median (interquartile range)". Intergroup comparisons were performed using non-parametric tests: the Kruskal-Wallis H test was used for overall comparisons, and the Mann-Whitney U test with Bonferroni correction was used for pairwise comparisons. Results 3.1. Comparison of Clinical Data Among the Three Groups Overall intergroup comparisons showed that with progressive severity of disease form mild to severe, SUA, SUA/Scr, BNP, and CTnl levels gradually increased, exhibiting statistically significant differences (all P < 0.05). However, no significant differences were observed 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 2 Comparison of Clinical Indicators Among Patients with Different Coronary Lesion Severities Clinical Indicator Mild Lesion Group (n = 156) Moderate Lesion Group (n = 155) Severe Lesion Group (n = 217) Test Statistic (χ²/H) P Value Male [n (%)] 95 (60.9%) 93 (60.0%) 148 (68.2%) 3.35 0.19 History of hypertension [n (%)] 101 (64.7%) 94 (60.6%) 133 (61.3%) 0.66 0.72 History of hyperlipidemia [n (%)] 62 (39.7%) 58 (37.4%) 85 (39.2%) 0.20 0.91 Smoking history [n (%)] 63 (40.4%) 54 (34.8%) 100 (46.1%) 4.77 0.09 Age (years) 69.00 (58.00, 75.00) 69.00 (59.00, 77.00) 70.00 (57.00, 76.00) 4.54 0.80 SUA (µmol/L) 332.00 (267.25, 398.75) 346.50 (287.00, 417.00) 392.50 (315.25, 448.50) 100.00 < 0.001 Scr (µmol/L) 64.50 (55.00, 80.00) 64.00 (56.50, 75.00) 68.00 (57.00, 78.00) 2.57 0.28 SUA/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 < 0.001 LDL-C (mmol/L) 2.5650 (1.97, 3.43) 2.7200 (2.06, 3.45) 2.8100 (2.08, 3.51) 2.33 0.31 HDL-C (mmol/L) 1.1100 (0.91, 1.36) 1.0700 (0.89, 1.33) 1.0200 (0.85, 1.26) 6.00 0.05 TG (mmol/L) 1.4950 (1.03, 2.34) 1.4000 (0.97, 2.07) 1.3800 (0.94, 2.11) 1.53 0.47 TC (mmol/L) 4.2450 (3.60, 5.16) 4.2800 (3.56, 5.13) 4.3900 (3.77, 5.18) 2.63 0.27 BNP (ng/L) 218.24 (68.96, 1384.14) 247.38 (99.24, 864.48) 526.80 (189.64, 1248.32) 54.61 < 0.001 CTnl (ng/L) 52.86 (7.93, 4068.94) 209.28 (16.38, 1081.75) 325.60 (42.18, 1560.90) 81.23 < 0.001 3.2. 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 Bonferroni-corrected Mann-Whitney U test (corrected α = 0.05/12 ≈ 0.0042). The results showed that SUA/Scr, BNP, and CTnl exhibited statistically significant differences in all pairwise comparisons (all corrected P < 0.0042). SUA levels differed significantly between the mild vs. severe and moderate vs. severe groups (both corrected P < 0.0042), but no significant difference was observed between the mild vs. moderate groups \(\text{P}\text{=0.483}\) , suggesting that the marked elevation of SUA primarily occurs during the progression from moderate to severe lesions (Table 3 ). Table 3 Statistical Results of Pairwise Comparisons of Indicators Among Different Coronary Lesion Severity Groups Comparison Group Indicator Mann-Whitney U Value Wilcoxon W Value Z Value Corrected Asymptotic Significance (Two-Tailed) Mild vs. Moderate SUA (µmol/L) 11534 23780 -7.01 0.483 SUA/Scr 9044.5 21290.5 -3.841 < 0.001 BNP (ng/L) 10053 22299 -2.569 0.01 CTnl (ng/L) 8691.5 20937.5 -4.293 < 0.001 Mild vs. Severe SUA (µmol/L) 8360 20606 -8.34 < 0.001 SUA/Scr 5369 17615 -11.251 < 0.001 BNP (ng/L) 9561 21807 -7.171 < 0.001 CTnl (ng/L) 7750 19996 -8.954 < 0.001 Moderate vs. Severe SUA (µmol/L) 8146 20236 -8.481 < 0.001 SUA/Scr 6112.5 18202.5 -10.47 < 0.001 BNP (ng/L) 12202.5 24292.5 -4.514 < 0.001 CTnl (ng/L) 12313.5 24403.5 -4.417 < 0.001 3.3. Further Grouped Comparisons Based on the comparison results, we found that there was no statistically significant difference between the mild and moderate groups of SUA, while the core indicators such as SUA/Scr, BNP, and CTnl exhibited gradient changes across all groups. Additionally, SUA showed a marked increase specifically during the transition from moderate to severe lesions, suggesting a high degree of homogeneity in biomarker profiles between mild and moderate disease stages. Therefore, we combined the mild and moderate lesion groups into a single mild-to-moderate lesion group for further 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 ). Table 4 Comparison of Clinical Data Between Mild-to-Moderate and Severe Coronary Lesion Groups Clinical Indicator Mild-to-Moderate Lesion Group (n = 311) Severe Lesion Group (n = 217) Test Statistic (χ²/Z) P Value Male [n (%)] 188 (60.5%) 148 (68.2%) 3.32 0.068 History of hypertension [n (%)] 195 (62.7%) 133 (61.3%) 1.08 0.742 History of hyperlipidemia [n (%)] 120 (38.6%) 85 (39.2%) 0.018 0.892 Smoking history [n (%)] 117 (37.6%) 100 (46.1%) 3.781 0.052 Age (years) 69.00 (58.00, 76.00) 70.00 (57.00, 76.00) -0.128 0.898 SUA (µmol/L) 332.00 (267.25, 398.75) 392.50 (315.25, 448.50) -9.994 < 0.001 Scr (µmol/L) 64.50 (55.00, 80.00) 68.00 (57.00, 78.00) -1.487 0.137 SUA/Scr (µmol/L per µmol/L) 4.74 (4.24, 5.74) 6.12 (5.01, 7.25) -12.907 < 0.001 LDL-C (mmol/L) 2.5650 (1.97, 3.43) 2.8100 (2.08, 3.51) -1.309 0.19 HDL-C (mmol/L) 1.1100 (0.91, 1.36) 1.0200 (0.85, 1.26) -1.764 0.078 TG (mmol/L) 1.4950 (1.03, 2.34) 1.3800 (0.94, 2.11) -0.512 0.609 TC (mmol/L) 4.2450 (3.60, 5.16) 4.3900 (3.77, 5.18) -1.613 0.107 BNP (ng/L) 218.24 (68.96, 1384.14) 526.80 (189.64, 1248.32) -6.946 < 0.001 CTnl (ng/L) 52.86 (7.93, 4068.94) 325.60 (42.18, 1560.90) -7.946 < 0.001 3.4. Multivariate Binary Logistic Regression Analysis After adjusting for confounding factors such as BNP and CTnl (both of which are significant factors of coronary lesions), multivariate binary logistic regression analysis revealed that only the SUA/Scr ratio was independently positively correlated with the severity of coronary lesion, suggesting it may serve as a potential independent risk factor for severe coronary lesions \(\text{OR}\text{=101.844,95\%}\text{}\text{CI}\text{:29.076\:356.726,}\text{}\text{P}\text{<0.05}\) . In contrast, when SUA or Scr was individually incorporated into the model, their potential associations might have been confounded by BNP, CTnl, and mutual interference; after adjustment, no statistically significant differences were observed ( \(\text{SUA}\text{:}\text{}\text{OR}\text{=3.010,95\%}\text{CI}\text{:0.614\:14.762,}\text{}\text{P}\text{=0.174;}\text{}\text{Scr}\text{:}\text{}\text{OR}\text{=0.697,95\%}\text{CI}\text{:0.099\:4.906,}\text{}\text{P}\text{=0.717}\) ). This suggested that compared with single indicators (SUA or Scr), the SUA/Scr ratio more reliably reflects the severity of coronary lesions and may serve as an important reference indicator for assessing the risk of progression to severe coronary lesions (Table 5 ). Table 5 Multivariate Binary Logistic Regression Analysis of SUA, Scr, and SUA/Scr with Severe Coronary Lesions After Correcting for BNP and CTnl Indicator B Value Standard Error Wald Statistic Degrees of Freedom Significance OR Value 95% Confidence Interval 95% Confidence Interval Lower Bound Upper Bound SUA 1.102 0.811 1.845 1 0.174 3.01 0.614 14.762 Scr -0.361 0.996 1.131 1 0.717 0.697 0.099 4.906 SUA/Scr 4.623 0.64 52.259 1 < 0.001 101.844 29.076 356.726 3.5. ROC Curve Analysis of Different Factors for Diagnosing Severe Coronary Lesions We employed ROC curve analysis 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 ~ 0.736, P < 0.05). Furthermore, we analyzed the optimal cutoff values and their corresponding prediction performance. The results showed that the optimal cutoff value of SUA/Scr was 5.35, with a sensitivity of 80.60% and specificity of 75.20%, yielding a predictive efficacy 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%, resulting in a predictive efficacy 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%, yielding an efficacy rated as ‘fair’. These results suggested that compared to either SUA or Scr, SUA/Scr exhibited superior predictive value for severe coronary lesions, suggesting its potential as a biomarker for assessing coronary artery disease severity in clinical practice. Table 6 ROC Curve Analysis of SUA, Scr, and SUA/Scr for Predicting Severe Coronary Lesions Variable AUC P Value 95% CI Optimal Cutoff Value Specificity Sensitivity SUA/Scr 0.84 < 0.05 0.805 ~ 0.875 5.35 75.20% 80.60% SUA 0.787 < 0.05 0.749 ~ 0.825 357.00 µmol/L 68.20% 72.80% Scr 0.69 < 0.05 0.644 ~ 0.736 64.00 µmol/L 50.50% 51.20% Figure 1: ROC Curves of SUA, Scr, and SUA/Scr for Predicting Severe Coronary Lesions Discussion CHD, one of the cardiovascular diseases with the highest mortality rate globally, is a clinical syndrome caused by atherosclerosis-induced narrowing of the coronary arteries, leading to myocardial ischemia, hypoxia, or necrosis [ 7 ] . Most patients experience clinical symptoms such as chest tightness, chest pain, and shortness of breath, impairing their quality of life. The severity of the lesion directly determines treatment strategy selection and long-term prognosis. Therefore, early prediction and effective prevention hold substantial clinical significance in improving patient and effective prevention hold substantial clinical significance in improving patient outcomes. Currently, coronary angiography is regarded as the gold standard for evaluating coronary artery lesions; however, this procedure is invasive, costly and requires high technical expertise, limiting its applicability for routine early screening or dynamic monitoring. Consequently, identifying convenient, non-invasive, and accurate biological markers is of considerable practical significance for optimizing risk stratification and clinical management of CHD. Atherosclerosis is closely associated with metabolic disorders [ 8 ] . SUA, a product of purine metabolism, has been demonstrated to promote vascular endothelial injury, lipid deposition, and plaque formation through mechanisms such as inducing oxidative stress and activating the NLRP3 inflammasome, suggesting a strong correlation between SUA levels and the development of coronary artery disease [ 9 ] . However, SUA levels are susceptible to renal function—impaired renal function may lead to pseudohyperuricemia, indicating that using SUA alone for assessing coronary lesions may lack accuracy. Scr is a classic indicator of glomerular filtration function. The SUA/Scr ratio can correct for the interference of renal function changes on uric acid excretion, thereby 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 [ 10 ] . This study analyzed the clinical data of 528 CHD patients. It first revealed a gradient association between SUA/Scr and coronary lesion severity: as the Gensini score increased from mild to moderate and then to severe, SUA/Scr levels showed a significant upward trend, with statistically significant differences observed in pairwise comparisons among the three groups. 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 result indicates that SUA/Scr is superior to SUA in distinguishing the severity of coronary arter lesions, particularly in more effectively reflecting differences during early disease progression (from mild to moderate), providing important evidence for early risk screening and identification of CHD. Furthermore, Scr showed no significant differences among groups with different lesion severities, reinforcing that a single renal function marker alone is insufficient for accurately reflecting the severity of coronary artery lesions [ 11 ] . In contrast, SUA/Scr, integrates metabolic and renal function information, enabling more accurate detection of biological signals of coronary lesion progression. Based on the above finding, we further validated the independent predictive value of SUA/Scr using Multivariate binary logistic regression analysis. 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 SUA or Scr alone had no statistically significant predictive effect. This result indicates that SUA/Scr is less interfered with by other confounding factors than a single index, and its association with coronary lesions is more stable. Therefore, SUA/Scr serves as a reliable indicator for assessing the risk of progression to severe coronary lesions. ROC curve analysis further quantified the predictive efficacy of SUA/Scr: the AUC of SUA/Scr was significantly higher than that of SUA and Scr alone; With a cutoff value of 5.35, SUA/Scr achieved a sensitivity of 80.60% and specificity of 75.20%, demonstrating ‘excellent’ predictive performance. These findings are consistent with those reported by Jiang et al. [ 4 ] regarding the association between SUA/Scr and in-hospital outcomes in elderly patients with acute myocardial infarction, both confirming the advantage of SUA/Scr in cardiovascular disease risk assessment. Its high sensitivity and specificity suggest its potential to be adopted as a routine clinical laboratory. Obviously, this study has certain limitations: first, it was a single-center retrospective design with a limited geographical scope of sample sourcing, which may lead to selection bias. Future studies should adopt a multi-center, prospective design to further validate the reliability of the findings. Second, the study did not include potential confounding factors (e.g., ABCG2 gene) or lifestyle factors (e.g., alcohol consumption, high-purine diet) associated with uric acid metabolism that may interfere with the association analysis between SUA/Scr and coronary lesions. In summary, this study proposes 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. Its predictive performance significantly surpasses that of either SUA or Scr used alone. The measurement of SUA/Scr is convenient and cost-effective, and holds promise as a novel biomarker for clinical assessment of coronary lesion severity, providing important reference for early warning, risk stratification, and individualized prevention and treatment strategies in CHD. Future research should conduct large-scale, long-term prospective studies to further establish the role of SUA/Scr in prognosis assessment of CHD and to explore its feasibility in guiding clinical interventions. Declarations Ethics approval : This study was approved by the Ethics Committee of Mianyang Third People's Hospital (approval number: 2026-06; approval date: February 24, 2026). All procedures were conducted in accordance with the Ethical Review Measures for Life Sciences and Medical Research Involving Humans, the Guidelines for the Construction of Ethics Review Committees for Clinical Research Involving Humans, and the Declaration of Helsinki. Consent to participate: The requirement for informed consent was waived due to the retrospective nature of this study, as approved by the Ethics Committee of Mianyang Third People's Hospital. Consent for publication : Not applicable. Competing interests: The authors declare that they have no competing interests. Acknowledgements Not applicable. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution 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. Data Availability The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. References Negi S, Anand A. Atherosclerotic coronary heart disease-epidemiology, classification and management. Cardiovasc Hematol Disord Drug Targets. 2010;10:356–68. 10.2174/187152910793743832 . Attiq A, Afzal S, Ahmad W, et al. 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Comparison of estimated GFR equations based on serum cystatin C alone and in combination with serum creatinine in patients with coronary artery disease. Anatol J Cardiol. 2015;15:351–8. 10.5152/akd.2014.5535 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 May, 2026 Reviews received at journal 04 May, 2026 Reviews received at journal 27 Apr, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers invited by journal 19 Mar, 2026 Editor invited by journal 10 Mar, 2026 Editor assigned by journal 10 Mar, 2026 Submission checks completed at journal 10 Mar, 2026 First submitted to journal 05 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9040816","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":609010959,"identity":"9ee506b9-f737-49ca-8fee-b46845c97028","order_by":0,"name":"Tingfen Wang","email":"","orcid":"","institution":"Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tingfen","middleName":"","lastName":"Wang","suffix":""},{"id":609010960,"identity":"14214f24-ea09-4e6b-8bf2-2051843354b2","order_by":1,"name":"Tingyu Wang","email":"","orcid":"","institution":"Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tingyu","middleName":"","lastName":"Wang","suffix":""},{"id":609010961,"identity":"3bd31025-baca-42f7-9a96-0daf10e26446","order_by":2,"name":"Runfeng Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYJCCDyDCAM4CAR78OhhnwLRAWGykaGHmIUaL+Yzcgw0fd9Tam7OfPfza5s/hxPnzGxgfvG1jkDfHoUXmRl5i48wzx5kte/LSrHPbDiduOMbAbDi3jcFwZwN2LRISOeaPeduOsRkcyDEzzm24nbiBjYFNmreNIcHgAE4ths1/247xGJx/Y2Zs8ed24vw2BvbfBLUwttVIGNzIMX7MwHY7seEYAxszXi08bwwbe9sOGBjceGPG2Nv233jDscRmyTnnJAw34NLCnmPY8LOtzt7gfI7xhx9/0mTnNx8++OFNmY08Llug4DCIYJOAcBgbQGbhVQ8EdSCC+QMhZaNgFIyCUTAyAQBe7l5+Xe8JAgAAAABJRU5ErkJggg==","orcid":"","institution":"Southwest Medical University","correspondingAuthor":true,"prefix":"","firstName":"Runfeng","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-03-05 13:54:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9040816/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9040816/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105318763,"identity":"61a8052e-5e55-4327-af66-157bcab861cd","added_by":"auto","created_at":"2026-03-24 16:55:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24427,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curves of SUA, Scr, and SUA/Scr for Predicting Severe Coronary Lesions\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9040816/v1/07d14f3ff03403c96957f2d7.png"},{"id":105318973,"identity":"62b4c95e-91ac-4ec7-8591-9280b6b0d4c4","added_by":"auto","created_at":"2026-03-24 16:56:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1062206,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9040816/v1/f35e634e-1d9c-46cc-99a8-8df04c8e1efc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Serum uric acid/creatinine ratio provides insights into the severity of coronary artery lesions and emerges as a potential predictor","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronary heart disease (CHD) is one of the leading causes of death worldwide, with its core pathological feature being coronary artery stenosis caused by atherosclerosis. The extent of coronary lesions directly determines treatment strategies and prognostic outcomes \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Early and accurate assessment of disease severity holds significant clinical importance for optimizing treatment strategies and reducing the risk of adverse cardiovascular events. Currently, coronary angiography is the gold standard for evaluating the severity of coronary lesion, but it has limitations such as invasiveness and high cost. Thus, there is an urgent need to identify convenient, non-invasive biomarkers to assist in evaluation.\u003c/p\u003e \u003cp\u003eAtherosclerosis is fundamentally a chronic inflammatory process \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. As the product of purine metabolism, serum uric acid (SUA) promotes the development and progression of atherosclerosis through inflammatory cascades of the NLRP3 inflammasome, and has been confirmed to be positively associated with the occurrence and progression of coronary lesions \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. However, SUA levels are susceptible to renal function\u0026mdash;impaired renal function often leads to elevated SUA levels. Serum creatinine (Scr) is a classic indicator for assessing renal function, and the metabolic ratio of SUA/Scr derived from it can correct for the impact of renal function on uric acid excretion, thereby more objectively reflecting the production level of net uric acid \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Nevertheless, research on the correlation between SUA/Scr ratio and the severity of coronary lesions remains limited. Therefore, this study aims to explore the correlation between SUA/Scr ratio and the severity of coronary lesion, analyze its predictive value, and provide new reference evidence for early risk stratification and clinical assessment of CHD.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\n\u003ch3\u003e1. Study Population\u003c/h3\u003e\n\u003cp\u003eThis retrospective study included 528 patients with CHD who underwent coronary angiography for the first time at 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.\u003c/p\u003e \u003cp\u003eInclusion criteria: ① Age\u0026thinsp;\u0026ge;\u0026thinsp;18 years; ② Hospitalized due to myocardial ischemia symptoms such as chest pain or tightness and underwent initial coronary angiography; ③ Meeting the diagnostic criteria for CHD: at least one segment of major coronary artery or branch of the coronary showing stenosis\u0026thinsp;\u0026ge;\u0026thinsp;50% confirmed by coronary angiography \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e; ④ Completed required biochemical tests before angiography; ⑤ Complete clinical data.\u003c/p\u003e \u003cp\u003eExclusion criteria: ① Coexisting other cardiovascular diseases, such as valvular heart disease or congenital heart disease; ② History of severe infectious diseases or renal transplantation; ③ History of myocardial infarction, cardiac surgery within 3 months, or previous coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI); ④ Use of medications affecting uric acid, blood lipids, or renal function within 7 days before admission; ⑤ Other conditions that may influence inflammatory status or hemodynamic condition.\u003c/p\u003e\n\u003ch3\u003e2. Data Collection\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.1 General Data\u003c/h2\u003e \u003cp\u003eIncluding gender, age, smoking history (defined as smoking\u0026thinsp;\u0026gt;\u0026thinsp;1 cigarette per day for more than 1 year), history of hypertension, and history of hyperlipidemia.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Laboratory Data\u003c/h2\u003e \u003cp\u003eBiochemical 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 (\u0026micro;mol/L) divided by Scr (\u0026micro;mol/L).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Coronary Angiography Results\u003c/h2\u003e \u003cp\u003eEvaluated by at least two experienced interventional cardiologists. The severity of coronary artery lesions was evaluated using the Gensini score, calculated as: Gensini score\u0026thinsp;=\u0026thinsp;basic score for stenosis degree \u0026times; weight coefficient for stenosis location; the total score is the sum of scores for all lesions. Higher scores indicate more severe lesions \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Detailed scoring criteria are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGensini Scoring Criteria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStenosis Degree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasic Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStenosis Location\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWeight Coefficient\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeft main coronary artery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25% to \u0026le;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProximal left anterior descending artery or proximal circumflex artery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;50% to \u0026le;\u0026thinsp;75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMid left anterior descending artery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;75% to \u0026le;\u0026thinsp;90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDistal left anterior descending artery or distal circumflex artery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;90% to \u0026le;\u0026thinsp;99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRight coronary artery, first diagonal branch, obtuse marginal branch, posterior descending artery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOcclusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecond diagonal branch, posterior lateral branch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e3. Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eData analysis was performed using SPSS 27.0 statistical software, with a significance level set at α\u0026thinsp;=\u0026thinsp;0.05 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;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 χ\u0026sup2; test. Continuous data \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\text{e.g.,}\\text{}\\text{age,}\\text{}\\text{SUA,}\\text{}\\text{Scr,}\\text{}\\text{SUA/Scr}\\)\u003c/span\u003e\u003c/span\u003e) were first assessed for normality using the Shapiro-Wilk test. Since all data failed to follow a normal distribution, they were presented as \"median (interquartile range)\". Intergroup comparisons were performed using non-parametric tests: the Kruskal-Wallis H test was used for overall comparisons, and the Mann-Whitney U test with Bonferroni correction was used for pairwise comparisons.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Comparison of Clinical Data Among the Three Groups\u003c/h2\u003e \u003cp\u003eOverall intergroup comparisons showed that with progressive severity of disease form mild to severe, SUA, SUA/Scr, BNP, and CTnl levels gradually increased, exhibiting statistically significant differences (all \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). However, no significant differences were observed in gender composition, prevalence of hypertension/hyperlipidemia/smoking, age, Scr, LDL-C, HDL-C, TG, or TC among the three groups (all \u003cem\u003eP\u003c/em\u003e ≥ 0.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab2\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Clinical Indicators Among Patients with Different Coronary Lesion Severities\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eClinical Indicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eMild Lesion Group\u003c/p\u003e \u003cp\u003e(n = 156)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eModerate Lesion Group\u003c/p\u003e \u003cp\u003e(n = 155)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSevere Lesion Group\u003c/p\u003e \u003cp\u003e(n = 217)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eTest Statistic\u003c/p\u003e \u003cp\u003e(χ²/H)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMale [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e95 (60.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e93 (60.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e148 (68.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHistory of hypertension [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e101 (64.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e94 (60.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e133 (61.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHistory of hyperlipidemia [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e62 (39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e58 (37.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e85 (39.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSmoking history [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e63 (40.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e54 (34.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e100 (46.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e69.00 (58.00, 75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e69.00 (59.00, 77.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e70.00 (57.00, 76.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA (µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e332.00 (267.25, 398.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e346.50 (287.00, 417.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e392.50 (315.25, 448.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eScr (µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e64.50 (55.00, 80.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e64.00 (56.50, 75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e68.00 (57.00, 78.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA/Scr (µmol/L per µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.74 (4.24, 5.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e5.26 (4.68, 6.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e6.12 (5.01, 7.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e173.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2.5650 (1.97, 3.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2.7200 (2.06, 3.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2.8100 (2.08, 3.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.1100 (0.91, 1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.0700 (0.89, 1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.0200 (0.85, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.4950 (1.03, 2.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.4000 (0.97, 2.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.3800 (0.94, 2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTC (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.2450 (3.60, 5.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.2800 (3.56, 5.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.3900 (3.77, 5.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBNP (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e218.24 (68.96, 1384.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e247.38 (99.24, 864.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e526.80 (189.64, 1248.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e54.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCTnl (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e52.86 (7.93, 4068.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e209.28 (16.38, 1081.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e325.60 (42.18, 1560.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e81.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Pairwise Comparisons of Indicators Among Groups\u003c/h2\u003e \u003cp\u003eTo further clarify the characteristics of indicator differences among groups, pairwise comparisons (mild vs. moderate, mild vs. severe, moderate vs. severe) were performed using the Bonferroni-corrected Mann-Whitney U test (corrected α = 0.05/12 ≈ 0.0042). The results showed that SUA/Scr, BNP, and CTnl exhibited statistically significant differences in all pairwise comparisons (all corrected \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0042). SUA levels differed significantly between the mild vs. severe and moderate vs. severe groups (both corrected \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0042), but no significant difference was observed between the mild vs. moderate groups \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{P}\\text{=0.483}\\)\u003c/span\u003e\u003c/span\u003e, suggesting that the marked elevation of SUA primarily occurs during the progression from moderate to severe lesions (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab3\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical Results of Pairwise Comparisons of Indicators Among Different Coronary Lesion Severity Groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eComparison Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eMann-Whitney U Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eWilcoxon W Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eZ Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eCorrected Asymptotic Significance\u003c/p\u003e \u003cp\u003e(Two-Tailed)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMild vs. Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA (µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e11534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e23780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-7.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.483\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA/Scr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e9044.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e21290.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-3.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBNP (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e10053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e22299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-2.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCTnl (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e8691.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e20937.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-4.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMild vs. Severe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA (µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e8360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e20606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-8.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA/Scr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e5369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e17615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-11.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBNP (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e9561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e21807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-7.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCTnl (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e7750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e19996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-8.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eModerate vs. Severe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA (µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e8146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e20236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-8.481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA/Scr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e6112.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e18202.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-10.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBNP (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e12202.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e24292.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-4.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCTnl (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e12313.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e24403.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-4.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Further Grouped Comparisons\u003c/h2\u003e \u003cp\u003eBased on the comparison results, we found that there was no statistically significant difference between the mild and moderate groups of SUA, while the core indicators such as SUA/Scr, BNP, and CTnl exhibited gradient changes across all groups. Additionally, SUA showed a marked increase specifically during the transition from moderate to severe lesions, suggesting a high degree of homogeneity in biomarker profiles between mild and moderate disease stages. Therefore, we combined the mild and moderate lesion groups into a single mild-to-moderate lesion group for further comparative analysis with the severe lesion group.\u003c/p\u003e \u003cp\u003eThere 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 \u0026gt; 0.05). However, SUA, SUA/Scr, BNP, and CTnl showed statistically significant differences (all P \u0026lt; 0.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab4\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Clinical Data Between Mild-to-Moderate and Severe Coronary Lesion Groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eClinical Indicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eMild-to-Moderate Lesion Group\u003c/p\u003e \u003cp\u003e(n = 311)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSevere Lesion Group\u003c/p\u003e \u003cp\u003e(n = 217)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eTest Statistic\u003c/p\u003e \u003cp\u003e(χ²/Z)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMale [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e188 (60.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e148 (68.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHistory of hypertension [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e195 (62.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e133 (61.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHistory of hyperlipidemia [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e120 (38.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e85 (39.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSmoking history [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e117 (37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e100 (46.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e3.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e69.00 (58.00, 76.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e70.00 (57.00, 76.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA (µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e332.00 (267.25, 398.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e392.50 (315.25, 448.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-9.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eScr (µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e64.50 (55.00, 80.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e68.00 (57.00, 78.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-1.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA/Scr (µmol/L per µmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.74 (4.24, 5.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e6.12 (5.01, 7.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-12.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2.5650 (1.97, 3.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2.8100 (2.08, 3.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-1.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.1100 (0.91, 1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.0200 (0.85, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-1.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.4950 (1.03, 2.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.3800 (0.94, 2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.609\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTC (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.2450 (3.60, 5.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.3900 (3.77, 5.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-1.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBNP (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e218.24 (68.96, 1384.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e526.80 (189.64, 1248.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-6.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCTnl (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e52.86 (7.93, 4068.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e325.60 (42.18, 1560.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-7.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Multivariate Binary Logistic Regression Analysis\u003c/h2\u003e \u003cp\u003eAfter adjusting for confounding factors such as BNP and CTnl (both of which are significant factors of coronary lesions), multivariate binary logistic regression analysis revealed that only the SUA/Scr ratio was independently positively correlated with the severity of coronary lesion, suggesting it may serve as a potential independent risk factor for severe coronary lesions \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{OR}\\text{=101.844,95\\%}\\text{}\\text{CI}\\text{:29.076\\:356.726,}\\text{}\\text{P}\\text{\u0026lt;0.05}\\)\u003c/span\u003e\u003c/span\u003e. In contrast, when SUA or Scr was individually incorporated into the model, their potential associations might have been confounded by BNP, CTnl, and mutual interference; after adjustment, no statistically significant differences were observed (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{SUA}\\text{:}\\text{}\\text{OR}\\text{=3.010,95\\%}\\text{CI}\\text{:0.614\\:14.762,}\\text{}\\text{P}\\text{=0.174;}\\text{}\\text{Scr}\\text{:}\\text{}\\text{OR}\\text{=0.697,95\\%}\\text{CI}\\text{:0.099\\:4.906,}\\text{}\\text{P}\\text{=0.717}\\)\u003c/span\u003e\u003c/span\u003e). This suggested that compared with single indicators (SUA or Scr), the SUA/Scr ratio more reliably reflects the severity of coronary lesions and may serve as an important reference indicator for assessing the risk of progression to severe coronary lesions (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab5\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate Binary Logistic Regression Analysis of SUA, Scr, and SUA/Scr with Severe Coronary Lesions After Correcting for BNP and CTnl\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" rowspan=\"2\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eB Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eWald Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eDegrees of Freedom\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eOR Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003e95% Confidence Interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003e95% Confidence Interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eLower Bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eUpper Bound\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e14.762\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eScr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e-0.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA/Scr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e52.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e101.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e29.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e356.726\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5. ROC Curve Analysis of Different Factors for Diagnosing Severe Coronary Lesions\u003c/h2\u003e \u003cp\u003eWe employed ROC curve analysis to evaluate the predictive efficacy of SUA, Scr, and SUA/Scr for severe coronary lesions. The results showed (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, Fig.\u0026nbsp;1) that the AUC of SUA/Scr was 0.840 (95% CI: 0.805 ~ 0.875, P \u0026lt; 0.05), which was significantly higher than that of SUA (AUC = 0.787, 95% CI: 0.749 ~ 0.825, P \u0026lt; 0.05) and Scr (AUC = 0.690, 95% CI: 0.644 ~ 0.736, P \u0026lt; 0.05).\u003c/p\u003e \u003cp\u003eFurthermore, we analyzed the optimal cutoff values and their corresponding prediction performance. The results showed that the optimal cutoff value of SUA/Scr was 5.35, with a sensitivity of 80.60% and specificity of 75.20%, yielding a predictive efficacy 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%, resulting in a predictive efficacy 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%, yielding an efficacy rated as ‘fair’.\u003c/p\u003e \u003cp\u003eThese results suggested that compared to either SUA or Scr, SUA/Scr exhibited superior predictive value for severe coronary lesions, suggesting its potential as a biomarker for assessing coronary artery disease severity in clinical practice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab6\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC Curve Analysis of SUA, Scr, and SUA/Scr for Predicting Severe Coronary Lesions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eOptimal Cutoff Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA/Scr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.805 ~ 0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e75.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e80.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.749 ~ 0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e357.00 µmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e68.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e72.80%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eScr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e\u0026lt; 0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0.644 ~ 0.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e64.00 µmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e50.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e51.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eFigure 1: ROC Curves of SUA, Scr, and SUA/Scr for Predicting Severe Coronary Lesions\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCHD, one of the cardiovascular diseases with the highest mortality rate globally, is a clinical syndrome caused by atherosclerosis-induced narrowing of the coronary arteries, leading to myocardial ischemia, hypoxia, or necrosis\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Most patients experience clinical symptoms such as chest tightness, chest pain, and shortness of breath, impairing their quality of life. The severity of the lesion directly determines treatment strategy selection and long-term prognosis. Therefore, early prediction and effective prevention hold substantial clinical significance in improving patient and effective prevention hold substantial clinical significance in improving patient outcomes. Currently, coronary angiography is regarded as the gold standard for evaluating coronary artery lesions; however, this procedure is invasive, costly and requires high technical expertise, limiting its applicability for routine early screening or dynamic monitoring. Consequently, identifying convenient, non-invasive, and accurate biological markers is of considerable practical significance for optimizing risk stratification and clinical management of CHD.\u003c/p\u003e\u003cp\u003eAtherosclerosis is closely associated with metabolic disorders \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. SUA, a product of purine metabolism, has been demonstrated to promote vascular endothelial injury, lipid deposition, and plaque formation through mechanisms such as inducing oxidative stress and activating the NLRP3 inflammasome, suggesting a strong correlation between SUA levels and the development of coronary artery disease \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. However, SUA levels are susceptible to renal function—impaired renal function may lead to pseudohyperuricemia, indicating that using SUA alone for assessing coronary lesions may lack accuracy. Scr is a classic indicator of glomerular filtration function. The SUA/Scr ratio can correct for the interference of renal function changes on uric acid excretion, thereby 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 \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study analyzed the clinical data of 528 CHD patients. It first revealed a gradient association between SUA/Scr and coronary lesion severity: as the Gensini score increased from mild to moderate and then to severe, SUA/Scr levels showed a significant upward trend, with statistically significant differences observed in pairwise comparisons among the three groups. 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 result indicates that SUA/Scr is superior to SUA in distinguishing the severity of coronary arter lesions, particularly in more effectively reflecting differences during early disease progression (from mild to moderate), providing important evidence for early risk screening and identification of CHD. Furthermore, Scr showed no significant differences among groups with different lesion severities, reinforcing that a single renal function marker alone is insufficient for accurately reflecting the severity of coronary artery lesions\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. In contrast, SUA/Scr, integrates metabolic and renal function information, enabling more accurate detection of biological signals of coronary lesion progression.\u003c/p\u003e\u003cp\u003eBased on the above finding, we further validated the independent predictive value of SUA/Scr using Multivariate binary logistic regression analysis. 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 SUA or Scr alone had no statistically significant predictive effect. This result indicates that SUA/Scr is less interfered with by other confounding factors than a single index, and its association with coronary lesions is more stable. Therefore, SUA/Scr serves as a reliable indicator for assessing the risk of progression to severe coronary lesions.\u003c/p\u003e\u003cp\u003eROC curve analysis further quantified the predictive efficacy of SUA/Scr: the AUC of SUA/Scr was significantly higher than that of SUA and Scr alone; With a cutoff value of 5.35, SUA/Scr achieved a sensitivity of 80.60% and specificity of 75.20%, demonstrating ‘excellent’ predictive performance. These findings are consistent with those reported by Jiang et al. \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e regarding the association between SUA/Scr and in-hospital outcomes in elderly patients with acute myocardial infarction, both confirming the advantage of SUA/Scr in cardiovascular disease risk assessment. Its high sensitivity and specificity suggest its potential to be adopted as a routine clinical laboratory.\u003c/p\u003e\u003cp\u003eObviously, this study has certain limitations: first, it was a single-center retrospective design with a limited geographical scope of sample sourcing, which may lead to selection bias. Future studies should adopt a multi-center, prospective design to further validate the reliability of the findings. Second, the study did not include potential confounding factors (e.g., ABCG2 gene) or lifestyle factors (e.g., alcohol consumption, high-purine diet) associated with uric acid metabolism that may interfere with the association analysis between SUA/Scr and coronary lesions.\u003c/p\u003e\u003cp\u003eIn summary, this study proposes 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. Its predictive performance significantly surpasses that of either SUA or Scr used alone. The measurement of SUA/Scr is convenient and cost-effective, and holds promise as a novel biomarker for clinical assessment of coronary lesion severity, providing important reference for early warning, risk stratification, and individualized prevention and treatment strategies in CHD. Future research should conduct large-scale, long-term prospective studies to further establish the role of SUA/Scr in prognosis assessment of CHD and to explore its feasibility in guiding clinical interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003e \u003cb\u003eEthics approval\u003c/b\u003e :\u003c/h2\u003e \u003cp\u003e This study was approved by the Ethics Committee of Mianyang Third People's Hospital (approval number: 2026-06; approval date: February 24, 2026). All procedures were conducted in accordance with the Ethical Review Measures for Life Sciences and Medical Research Involving Humans, the Guidelines for the Construction of Ethics Review Committees for Clinical Research Involving Humans, and the Declaration of Helsinki.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to participate:\u003c/strong\u003e \u003cp\u003e The requirement for informed consent was waived due to the retrospective nature of this study, as approved by the Ethics Committee of Mianyang Third People's Hospital.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication :\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTingfen Wang: Conceptualization, Methodology, Data curation, Formal analysis, Writing - Original DraftTingyu Wang: Investigation, Data curation, ValidationRunfeng Zhang: Conceptualization, Supervision, Writing - Review \u0026amp; EditingAll authors have read and approved the final manuscript and take full responsibility for the integrity and accuracy of the data presented.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNegi S, Anand A. 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Anatol J Cardiol. 2015;15:351\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5152/akd.2014.5535\u003c/span\u003e\u003cspan address=\"10.5152/akd.2014.5535\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Coronary artery lesions, Serum uric acid-to-creatinine ratio, Predictive value","lastPublishedDoi":"10.21203/rs.3.rs-9040816/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9040816/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: With changes in lifestyle, the incidence of chronic metabolic diseases and cardiovascular diseases has increased year by year, posing a major public health threat to human health. Coronary heart disease (CHD) is one of the most common cardiovascular diseases in clinical practice, with its mortality rate consistently ranking among the highest globally. Therefore, timely and accurate assessment of coronary artery lesions play a crucial role in reducing mortality and improving prognosis in CHD patients.\u003c/p\u003e\n\u003cp\u003eObjective: To investigate the correlation between the serum uric acid-to-creatinine ratio (SUA/Scr) and the severity of coronary artery disease, and to evaluates its potential clinical value in predicting disease severity and risk stratification. This study aims to provide experimental evidence and theoretical support for early warning, disease assessment, and the development of individualized prevention and treatment strategies for CHD.\u003c/p\u003e\n\u003cp\u003eMethods: This retrospective study included 528 patients with CHD who underwent initial coronary angiography due to chest pain or chest tightness at the Department of Cardiovascular Medicine, Mianyang Third People's Hospital, from January and December 2023. Gensini scores were calculated based on coronary angiography results, and patients were divided into three groups: mild lesion group (Gensini score \u0026lt; 20, n=156), moderate lesion group (20 ≤ Gensini score \u0026lt; 40, n=155), and severe lesion group (Gensini score ≥ 40, n=217). General clinical data and biochemical indicators were collected, and the SUA/Scr ratio were calculated. Differences in SUA, Scr, and SUA/Scr among the three groups were compared. Multivariate ordinal logistic regression analysis was used to identify independent risk factors for coronary lesions. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive efficacy of SUA, Scr, and SUA/Scr for moderate-to-severe coronary lesions.\u003c/p\u003e\n\u003cp\u003eResults: Intergroup comparisons showed no significant difference in Scr levels among the three groups (\u003cem\u003eP\u003c/em\u003e\u0026gt; 0.05). No significant difference in SUA levels was observed between the mild and moderate lesion groups (\u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05); however, SUA levels in both groups were significantly lower than those in the severe lesion group (both \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). In contrast, the SUA/Scr ratio progressively increased with the severity of coronary lesions, and pairwise comparisons among the three groups (all P \u0026lt; 0.05). Multivariate binary logistic regression analysis revealed that, after adjusting for confounding factors, SUA/Scr ratio remained an independent risk factor for severe coronary lesions, with OR=101.844, P \u0026lt; 0.05. ROC curve analysis showed that the area under the curve (AUC), optimal cutoff value, sensitivity, and specificity of SUA/Scr were 0.840, 5.35, 80.60%, and 75.2%, respectively—values that were all higher than those obtained when SUA or Scr was used individually.\u003c/p\u003e\n\u003cp\u003eConclusion: SUA/Scr ratio is closely associated with the severity of coronary artery lesions in CHD patients and serves as an independent predictor of coronary artery disease, holding significant clinical value in assessing the severity of coronary lesions.\u003c/p\u003e","manuscriptTitle":"Serum uric acid/creatinine ratio provides insights into the severity of coronary artery lesions and emerges as a potential predictor","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 16:54:06","doi":"10.21203/rs.3.rs-9040816/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-11T09:21:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T04:26:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-28T03:44:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"101970834499734019257518083899916181561","date":"2026-04-13T04:29:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118892559029165041731343189280490941838","date":"2026-04-09T16:09:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T15:53:05+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-10T11:14:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-10T09:50:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-10T09:49:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Research Notes","date":"2026-03-05T13:50:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f6a80fd3-ccbd-4ce6-8f0a-03ed6ca99f2c","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-11T09:21:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T04:26:52+00:00","index":34,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-16T16:53:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 16:54:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9040816","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9040816","identity":"rs-9040816","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}