Elevated serum NLR and PLR are associated with a higher risk of atherosclerotic renal stenosis

Elevated serum NLR and PLR are associated with a higher risk of atherosclerotic renal stenosis | 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 Article Elevated serum NLR and PLR are associated with a higher risk of atherosclerotic renal stenosis Ge Xu, Yuping Wu, Yaohan Tang, Xiafei Huang, Jinsui Wu, Kerong Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3829803/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract There is still a lack of effective non-invasive diagnosis of atherosclerotic renal stenosis. The aim of this study was to investigate the association of platelet to lymphocyte ratio (PLR) and neutrophil to lymphocyte ratio (NLR) with atherosclerotic renal artery stenosis (ARAS). Data of a total of 1062 patients (362 ARAS, 664 non-ARAS) were collected. Logistic regression analysis and receiver operating characteristic curve analysis was used to analyze the collected patient data. NLR and PLR levels were significantly increased in ARAS group compared with non-ARAS group ( p < 0.05). Correlation analysis showed that both NLR and PLR were positively correlated with ARAS (r = 0.199, r = 0.251, p < 0.05), and only NLR was positively correlated with the degree of stenosis of ARAS (r = 0.152, p < 0.05). Multivariate logistic regression showed that NLR (OR = 1.203, 95%CI = 1.023 ~ 1.046, P = 0.025) and PLR (OR = 1.011, 95%CI = 1.003 ~ 1.019, P = 0.004) were independent risk factors for ARAS. The ROC curve indicated that the diagnostic value of NLR and PLR were (AUC = 0.653, P < 0.001; AUC = 0.62, P < 0.001). In conclusion, elevated levels of NLR and PLR are associated with an increased risk of developing ARAS. NLR and PLR have the potential to be a means of diagnosing ARSA. Health sciences/Cardiology Health sciences/Diseases Health sciences/Nephrology Health sciences/Risk factors Atherosclerotic Renal Artery Stenosis Platelet-to-Lymphocyte Ratio Neutrophil-to-Lymphocyte Ratio Figures Figure 1 Figure 2 Introduction Renal artery stenosis (RAS) is a progressive disease in which a 50% or greater narrowing of one or both renal arteries and their major branches is generally considered clinically significant 1 . Atherosclerosis is the main cause of RAS 2 . Clinical manifestations of atherosclerotic renal artery stenosis (ARAS) are nonspecific, making accurate diagnosis challenging, and often leading to missed or delayed detection 3 . Failure to identify ARAS promptly can result in progressive deterioration of renal function, end-stage renal disease, and refractory hypertension. Early screening, intervention, and treatment are crucial in preventing the development of ARAS into end-stage renal disease 4 . Mounting evidence from basic and clinical studies suggests that atherosclerosis is a chronic inflammatory disease involving processes such as endothelial damage, lipid deposition, inflammatory cell aggregation, and vascular remodeling 5 . Inflammatory factors, including platelets, neutrophils, and lymphocytes, play significant roles in the development of atherosclerosis 6 . Recent research has focused on exploring the interplay between inflammatory factors, with particular interest in the platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) 7 . These ratios have been extensively used to study the onset and prognosis of various diseases due to their cost-effectiveness, convenience, and reliability. Numerous studies conducted worldwide have demonstrated a close association between PLR, NLR, and process such as cardiovascular diseases, cerebrovascular diseases, and systemic inflammation 8–10 . However, the correlation between PLR, NLR, and ARAS is currently not clear. The primary objective of this study is to explore the correlation between PLR, NLR, and ARAS, analyze the associated risk factors, and provide valuable insights for early clinical detection of ARAS. Results General information of the ARAS group compared to the non-ARAS group The ARAS patients exhibited significantly higher age and systolic blood pressure compared to the non-ARAS group (all p values 0.05), as presented in Supplementary table 1. Comparison of General Information between ARAS Moderate Stenosis and Severe Stenosis Groups According to the degree of stenosis, the ARAS group was further divided into moderate stenosis group (50%-70% stenosis, n=104) and severe stenosis group (≥70% stenosis, n=258). The analysis revealed a significantly higher proportion of patients with diabetes in the ARAS severe stenosis group compared to the moderate stenosis group ( p 0.05). Further details can be found in Supplementary table 2. Comparison of Test Results between ARAS and non-ARAS Groups Comparison of the test results between the ARAS and non-ARAS groups revealed significant differences in several parameters. The ARAS group showed higher levels of white blood cells (WBC), platelets (PLT), neutrophils (NE), triglycerides (TG), serum creatinine (Scr), cystatin C, glycated hemoglobin (HbA1c), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR) compared to the non-ARAS group. Conversely, lymphocyte count (LYM) and high-density lipoprotein cholesterol (HDL-C) levels were lower in the ARAS group ( p < 0.05). However, there were no statistically significant differences observed in red blood cell distribution width (RDW), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and lipoprotein(a) between the ARAS and non-ARAS groups ( p > 0.05). Further details can be found in Supplementary table 3. Comparison of Test Results between Moderate and Severe Stenosis Groups in ARAS In ARAS patients, the severe stenosis group showed significantly higher levels of WBC, NE, HbA1c, and NLR compared to the moderate stenosis group ( p 0.05). Refer to Supplementary table 4 for details. Correlation analysis of NLR, PLR and ARSA To assess the relationship between PLR, NLR, and ARAS, as well as the degree of stenosis, a correlation analysis was performed. Since NLR and PLR did not follow a normal distribution according to the normality test, Spearman rank correlation was utilized. The results revealed a significant positive correlation between NLR and ARAS, with a correlation coefficient of 0.251 ( p < 0.05). Similarly, exhibited a significant positive correlation with ARAS, with a correlation coefficient of 0.199 ( p < 0.05). There was a significant positive correlation between NLR and the degree of stenosis, with a correlation coefficient of 0.152 ( p 0.05). For detailed results, please refer to Tables 1 and 2. Tables 1. Correlation analysis of NLR, PLR and ARAS ARAS R p NLR 0.251 ＜0.001 PLR 0.199 ＜0.001 Abbreviation: NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio. Tables 2. Correlation analysis of PLR, NLR and Degree of ARAS stenosis Degree of ARAS stenosis R p PLR 0.030 0.571 NLR 0.152 0.004 Abbreviation: NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio. Univariate logistic regression analysis To investigate the potential associations between general data, test results, and examination findings of the two groups, univariate logistic regression analysis was performed using the presence of ARAS as the dependent variable. The analysis identified age, systolic blood pressure, WBC, PLT, NE, LYM, HDL-C, Scr, cystatin C, PLR and NLR as risk factors for ARAS ( p < 0.05). Please refer to Supplementary table5 for detailed results. Multivariate logistic regression analysis To account for the possibility of multicollinearity among the blood cell parameters (WBC, NE, PLT, and LYM), their variance inflation factor (VIF) values were assessed. It was found that the VIF values for WBC and NE exceeded 10 , indicating the presence of multicollinearity. Therefore, WBC and NE were excluded from further analysis. The remaining indicators were examined for covariance, and their VIF values were below 10, indicating the absence of multicollinearity. Subsequently, the other significant indicators identified in the univariate logistic regression analysis were included in the multivariate logistic regression analysis. The results demonstrated that age, HDL-C, PLR, and NLRwere independent risk factors for the occurrence of ARAS. Please refer to Table 3 for detailed findings. Table 3. Multivariate logistic regression analysis Variables β SE Waldχ 2 p OR 95%CI Age 0.042 0.007 32.054 ＜0.001 1.043 1.028~1.059 HDL-C -0.563 0.218 6.709 0.01 0.569 0.372~0.872 Scr 0.011 0.003 11.625 0.001 1.011 1.005~1.018 NLR 0.185 0.083 4.99 0.025 1.203 1.023~1.046 PLR 0.011 0.004 8.088 0.004 1.011 1.003~1.019 Abbreviation: HDL-C, high-density lipoprotein cholesterol; Scr, serum creatinine; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio. Characterization of ROC curves for PLR and NLR in predicting ARAS The predictive ability of PLR and NLR for ARAS was assessed using ROC curve analysis. The AUC for PLR in predicting ARAS was 0.620 (95% CI: 0.584 to 0.657), with an optimal diagnostic cut-off value of 145.88. The sensitivity and specificity were determined to be 45.3% and 74.1%, respectively (Figure 1A). Similarly, the ROC curve for NLR in predicting ARAS yielded an AUC of 0.653 (95% CI: 0.617 to 0.787). The optimal diagnostic cut-off value for NLR was identified as 2.52, with a sensitivity of 49.2% and a specificity of 75.9% (Figure 1B). Characterization of ROC Curves for PLR and NLR in Predicting ARAS Stenosi s ROC curve analysis was conducted to assess the predictive capacity of PLR and NLR for the degree of ARAS stenosis. The AUC for PLR in predicting the degree of ARAS stenosis was 0.519 ( p =0.570), indicating that PLR does not possess significant predictive value for the degree of ARAS stenosis (Figure 2A). In contrast, the ROC curve for NLR in predicting ARAS stenosis yielded an AUC of 0.597 (95% CI: 0.531 to 0.663). The optimal diagnostic cut-off value for NLR was determined to be 2.32, with a sensitivity of 62.8% and a specificity of 59.6% (Figure 2B). Discussion Cardiovascular diseases has become a significant health concern in China due to improved living standards and an aging population. ARAS, accounting for 1%-3% of hypertensive patients, is a reversible cause of age-related hypertension, as well as chronic cardiac and renal insufficiency. However, the insidious onset and lack of specific clinical manifestations make early detection challenging. Renal arteriography, the main diagnostic tool, is invasive and limited in its use as a screening tool. Therefore, identifying risk factors for ARAS is crucial for early detection and avoiding unnecessary renal arteriography. Our study revealed that age, systolic blood pressure, triglycerides, glycated hemoglobin in the patients of ARAS group were significantly higher than those in the non-ARAS group. HDL-C levels were significantly lower in the ARAS group compared to the non-ARAS group. Age, diabetes, and hypertension are common risk factors for ARAS and contribute to the progression of renal artery stenosis and various cardiovascular diseases. Advanced age, female gender, and a history of hypertension are significant risk factors for ARAS 11 . Hypertension is the most prevalent high-risk factor for cardiovascular disease, emphasizing the importance of effective blood pressure control. Diabetes also debated as an independent risk factor for ARAS. In our study, the proportion of diabetic patients and HbA1c levels were also significantly higher in the severe stenosis group compared to the moderate stenosis group. Dyslipidemia is a significant risk factor for ARAS 12 . Elevated TG is a central feature of the atherogenic dyslipidemia complex 13 . which encompasses depressed HDL-C and elevated small dense LDL particles, both of which are themselves plausibly causally related to atherosclerosis 14 . HDL-C, known for its protective role against atherosclerosis, promotes reverse cholesterol transport and has anti-inflammatory, anti-oxidant, and endothelial repair properties 15,16 . In our study, LDL-C levels did not show a significant difference between the ARAS and non-ARAS groups, possibly due to prior statin therapy in hypertensive patients. Our results showed that the white blood cells, platelets, neutrophils in the ARAS group were significantly higher than those in the non-ARAS group; The lymphocytes in ARAS patients were significantly lower than those of non-ARAS group. Previous studies have demonstrated that elevated levels of neutrophils and platelets together, along with reduced levels of lymphocytes, are associated with vascular diseases 17,18 . Platelets not only contribute to thrombosis but also release inflammatory factors and mediators, thereby promoting inflammatory reactions 19 . Increased platelet count can activate platelets, leading to the release of pro-inflammatory mediators from endothelial cells and leukocytes. This process facilitates monocyte adhesion, migration, and the aggregation of leukocytes in damaged vascular endothelium, thereby initiating and promoting the development of atherosclerotic lesions 20 . In contrast, neutrophils exhibit a non-specific inflammatory response in endothelial atherosclerotic plaques. The inflammatory response increases neutrophil production and releases various active components involved in activation, migration, tissue infiltration, and interaction with vascular endothelial cells. These processes accelerate the progression of atherosclerotic thrombosis 21 .Lymphocytes produce cytokines that inhibit cell proliferation and promote cell death. Lymphocyte apoptosis has been observed in atherosclerotic lesions involved in atherosclerotic plaque growth, lipid core development, plaque rupture, and thrombosis. NLR and PLR are involved in different immunological pathways and activate the nonspecific inflammatory response by increasing the neutrophil or platelet count 22,23 PLR and NLR are markers that combine information on hemostasis and inflammation, with high sensitivity for demonstrating the inflammatory process 24,25 . Several studies suggest that NLR and PLR can be markers of inflammatory activity in various diseases 26,27 . Our study first found PLR and NLR in the patients of ARAS group were significantly higher than those in the non-ARAS group. There is a significant positive correlation between PLR, NLR and ARAS, NLR is also positively correlated with the degree of stenosis in ARAS. These results suggested an association with the chronic inflammatory process in ARAS. However, their accuracy and sensitivity for predicting ARAS were limited, as indicated by the AUC values. Multivariate logistic regression analysis confirmed PLR and NLR as independent risk factors for ARAS. Limitations of this study: Firstly, this study was retrospective and had limitations due to human and time constraints, which may have introduced bias and affected the final results. Secondly, the study did not follow the patients over a long period, making it difficult to assess the dynamic changes in PLR and NLR and their relationship with ARAS. Consequently, the study did not fully evaluate the impact of ARAS on PLR and NLR. Finally, the study only examined the correlation between some routine blood parameters and ARAS, without including other parameters or common inflammation indicators. Therefore, it was not possible to determine the influence of other routine blood parameters on the study or whether they could be combined with other inflammation indicators to predict the occurrence of ARAS. Further extensive research is needed to explore and confirm these findings. In summary, the elevated levels of NLR and PLR are found to be associated with an increased risk of developing ARAS In this retrospective study. The higher the NLP, the more severe the stenosis of ARAS.NLR and PLR have the potential to be a means of diagnosing ARSA. Materials and methods Study Population: A retrospective analysis was conducted on a cohort of 1026 patients diagnosed with hypertension who underwent renal arteriography at the Department of Cardiovascular Medicine, First Affiliated Hospital of Guangxi Medical University, between January 2020 and December 2022. Relevant patient information, including smoking history, diabetes history, and demographic characteristics such as age, sex, height, and weight, was recorded. All patients underwent routine blood tests, renal function assessments, lipid profiles, glycosylated hemoglobin measurements, and renal arteriography. Patients were categorized into the ARAS (renal artery stenosis) group (n=362) or the non-ARAS group (n=664) based on the presence or absence of renal artery stenosis. It should be noted that this research was conducted in accordance with the purpose of the Declaration of Helsinki and its amendments, and approved by the Ethics Committee of The First Affiliated Hospital of Guangxi Medical University (Number: 2024-E045-01). The patients/participants provided a signed informed consent form. Inclusion criteria (1) Patients who met the diagnostic criteria for hypertension according to the 2018 Chinese guidelines for the prevention and treatment of hypertension. (2) Patients who provided informed consent and understood the purpose of renal arteriography. (3) Patients with complete accurate data and information. Exclusion criteria (1) Patients with incomplete clinical data. (2) Patients with severe hepatic or renal insufficiency or malnutrition. (3) Patients with acute or chronic infections, malignancies, hematological disorders, tumors, tuberculosis, or other diseases. (4) Patients with a recent history of acute myocardial infarction or decompensated heart failure. (5) Patients diagnosed with other causes of renal stenosis, such as fibromuscular dysplasia or Takayasu arteritis. (6) Patients diagnosed with other types of secondary hypertension. (7) Patients with a previous history of renal artery stent implantation. Diagnostic Criteria (1) ARAS: Diagnosis required the presence of at least one risk factor for atherosclerosis (age over 40 years, long-term smoking, diabetes, hyperlipidemia) and kidney artery angiography showing a ≥50% decrease in the diameter of the main trunk and/or branches of the renal artery. Lesions typically involved the proximal segment and ostium of the renal artery, displaying eccentric stenosis, irregular plaques, and calcification. (2) Diagnosis followed the criteria outlined in the 2018 Chinese Guidelines for the Prevention and Treatment of Hypertension 28 , including systolic blood pressure ≥ 140mmHg and/or diastolic blood pressure ≥ 90mmHg measured on different days or currently taking antihypertensive medication. (3) Diabetes: Diagnosis followed the diagnostic criteria for diabetes proposed in the Chinese Guidelines for the Prevention and Treatment of Type 2 Diabetes in 2020 29 , including typical diabetes symptoms with elevated blood glucose levels or glycated hemoglobin ≥ 6.5%. (4) Smoking History: Defined as continuous smoking of at least one cigarette per day for more than one year or quitting smoking within the past six months. Data Collection (1) General Data: Patient information including gender, age, height, weight, smoking history, diabetes history, and initial standard blood pressure measurement were obtained through comprehensive history-taking and precise measurements. Body Mass Index (BMI) was calculated using recorded height and weight. (2) Laboratory Test Results: Comprehensive documentation of laboratory test results included white blood cell count (WBC), platelet count (PLT), absolute neutrophil count (NE), absolute lymphocyte count (LYM), and red blood cell distribution width (RDW). Serum creatinine (Scr), cystatin C, lipid profile (total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and lipoprotein a), and glycated hemoglobin (HbA1c) levels were measured. Platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) were calculated as PLR = PLT/LYM and NLR = NE/LYM. (3) Renal Arteriography: percutaneous selective renal arteriography was performed by at least two qualified clinicians to evaluate the extent of luminal stenosis through visual diameter measurement. Patients were adequately informed about the purpose, potential risks, and precautionary measures associated with renal arteriography, and informed consent was obtained. (4) Group Classification: Based on renal arteriography findings, patients with renal artery stenosis ≥50% were classified into the ARAS group, while patients with stenosis <50% were classified into the non-ARAS group. Within the ARAS group, further classification was made based on stenosis severity into a moderate stenosis group (50% to 70% stenosis) and a severe stenosis group (≥70% stenosis) using the classification criteria recommended by the Society for Cardiovascular Angiography and Interventions in 2014 30 . Statistical Analysis : Statistical analysis was performed using SPSS 27.0 software. Group differences were analyzed using independent samples t-test, Mann-Whitney U test, or chi-square test as appropriate. Spearman's rank correlation analysis was used to assess the correlation between PLR, NLR, and ARAS. Logistic regression models were employed to analyze the risk factors for ARAS. The predictive value of PLR and NLR for renal artery stenosis was assessed using ROC curves. Statistical significance was set at p value < 0.05. Declarations Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Author Contribution GX designed the experiments. GX, YHT, YPW, KRL, XFH analyzed the data. YPW and JSW collected the patients. YPW, GX and YHT wrote the manuscript. All au-thors reviewed the manuscript. Data availability The datasets used or analysed during the current study are available from the corresponding author on reasonable . References White, C. J. & Olin, J. W. Diagnosis and management of atherosclerotic renal artery stenosis: improving patient selection and outcomes. Nat Clin Pract Cardiovasc Med 6, 176-190, doi:10.1038/ncpcardio1448 (2009). The, W. 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Wei Sheng Yan Jiu 52, 541-548, doi:10.19813/j.cnki.weishengyanjiu.2023.04.004 (2023). Klein, A. J. et al. SCAI appropriate use criteria for peripheral arterial interventions: An update. Catheter Cardiovasc Interv 90, E90-e110, doi:10.1002/ccd.27141 (2017). Additional Declarations No competing interests reported. Supplementary Files Supplementarytables.pdf Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-3829803","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":269716535,"identity":"6aa96726-4864-4260-b111-e7d60a1e5419","order_by":0,"name":"Ge Xu","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ge","middleName":"","lastName":"Xu","suffix":""},{"id":269716536,"identity":"e0966b32-d4de-4d71-99ec-105523a329e3","order_by":1,"name":"Yuping Wu","email":"","orcid":"","institution":"the First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuping","middleName":"","lastName":"Wu","suffix":""},{"id":269716537,"identity":"6f5dd2c1-ce88-431b-b59a-ee00e217e74c","order_by":2,"name":"Yaohan Tang","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yaohan","middleName":"","lastName":"Tang","suffix":""},{"id":269716538,"identity":"510d2d03-d7d7-444d-afb2-c6cbac707ac1","order_by":3,"name":"Xiafei Huang","email":"","orcid":"","institution":"the First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiafei","middleName":"","lastName":"Huang","suffix":""},{"id":269716539,"identity":"973b9850-2343-4bfc-9a51-12faf1c844bc","order_by":4,"name":"Jinsui Wu","email":"","orcid":"","institution":"the First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jinsui","middleName":"","lastName":"Wu","suffix":""},{"id":269716540,"identity":"e2c0d25d-4aa0-4eca-95d4-c4bec036680b","order_by":5,"name":"Kerong Li","email":"","orcid":"","institution":"the First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kerong","middleName":"","lastName":"Li","suffix":""},{"id":269716541,"identity":"5628eb12-f878-49ef-aef8-a5983276c966","order_by":6,"name":"Ge Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIie3RPQrCMBjG8YRAuqR2TSnoFSIFcSh4EJe3CJ10cnEoGCi0Sw/Qa/QGrwSceoDuXkDoKn6M3Ro3wfz33/DwEOJy/WC0YGgep4RxT1sSVpUpii7zZgItiVd3MfqlCeYSLInfgELJWcTDW9uTPNlOkrABQCV4zKPsuCbX7KCnyLIBRJBix6P9SlJtpsmmTzWikucy7CwJrQ25aFCMS2FLqpIYgsC4+GwBmy20CIaBPl9sUZm2v+fJNBmnrK8ZkW+Fy+Vy/Udvaqs+u7loMI0AAAAASUVORK5CYII=","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":true,"prefix":"","firstName":"Ge","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-01-02 15:14:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3829803/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3829803/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50386873,"identity":"87fd98fe-084d-4b5b-920c-bba64f4a24be","added_by":"auto","created_at":"2024-01-30 17:53:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105377,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curves for PLR and NLR prediction of ARAS.\u003c/strong\u003e ROC curves for PLR (A) and NLR (B) prediction of ARAS.\u003c/p\u003e","description":"","filename":"floatimage1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3829803/v1/e8570f94b3b8fe1bae78ebda.jpg"},{"id":50386874,"identity":"bf6dd40b-c621-4672-b69b-79d620fb1375","added_by":"auto","created_at":"2024-01-30 17:53:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":113248,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2. ROC curves for PLR and NLR prediction of ARAS stenosis.\u003c/strong\u003e ROC curves for PLR (A) and NLR (B) prediction of ARAS stenosis.\u003c/p\u003e","description":"","filename":"floatimage2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3829803/v1/a1d59a0c714a582cca7d0548.jpg"},{"id":62258220,"identity":"8237563f-6c6d-4c40-ae3a-5f5639506ccd","added_by":"auto","created_at":"2024-08-12 07:55:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":739261,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3829803/v1/6ff8d1d4-a12e-4fa8-81b7-22ca9513db2b.pdf"},{"id":50386875,"identity":"fcd17428-8749-4b9c-bd91-e224a73a437b","added_by":"auto","created_at":"2024-01-30 17:53:03","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":224491,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytables.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3829803/v1/763ba947fa7beb26c6a62820.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Elevated serum NLR and PLR are associated with a higher risk of atherosclerotic renal stenosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRenal artery stenosis (RAS) is a progressive disease in which a 50% or greater narrowing of one or both renal arteries and their major branches is generally considered clinically significant\u003csup\u003e1\u003c/sup\u003e. Atherosclerosis is the main cause of RAS\u003csup\u003e2\u003c/sup\u003e. Clinical manifestations of atherosclerotic renal artery stenosis (ARAS) are nonspecific, making accurate diagnosis challenging, and often leading to missed or delayed detection\u003csup\u003e3\u003c/sup\u003e. Failure to identify ARAS promptly can result in progressive deterioration of renal function, end-stage renal disease, and refractory hypertension. Early screening, intervention, and treatment are crucial in preventing the development of ARAS into end-stage renal disease\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMounting evidence from basic and clinical studies suggests that atherosclerosis is a chronic inflammatory disease involving processes such as endothelial damage, lipid deposition, inflammatory cell aggregation, and vascular remodeling\u003csup\u003e5\u003c/sup\u003e. Inflammatory factors, including platelets, neutrophils, and lymphocytes, play significant roles in the development of atherosclerosis\u003csup\u003e6\u003c/sup\u003e. Recent research has focused on exploring the interplay between inflammatory factors, with particular interest in the platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR)\u003csup\u003e7\u003c/sup\u003e. These ratios have been extensively used to study the onset and prognosis of various diseases due to their cost-effectiveness, convenience, and reliability. Numerous studies conducted worldwide have demonstrated a close association between PLR, NLR, and process such as cardiovascular diseases, cerebrovascular diseases, and systemic inflammation\u003csup\u003e8\u0026ndash;10\u003c/sup\u003e. However, the correlation between PLR, NLR, and ARAS is currently not clear. The primary objective of this study is to explore the correlation between PLR, NLR, and ARAS, analyze the associated risk factors, and provide valuable insights for early clinical detection of ARAS.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eGeneral information of the ARAS group compared to the non-ARAS group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ARAS patients exhibited significantly higher age and systolic blood pressure compared to the non-ARAS group (all \u003cem\u003ep\u003c/em\u003e values\u0026lt; 0.05). However, there were no significant differences observed in terms of gender, smoking history, diabetes history, and diastolic blood pressure between the two groups (all \u003cem\u003ep\u003c/em\u003e values\u0026gt; 0.05), as presented in Supplementary table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of General Information between ARAS Moderate Stenosis and Severe Stenosis Groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the degree of stenosis, the ARAS group was further divided into moderate stenosis group (50%-70% stenosis, n=104) and severe stenosis group (\u0026ge;70% stenosis, n=258). The analysis revealed a significantly higher proportion of patients with diabetes in the ARAS severe stenosis group compared to the moderate stenosis group (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05). However, there were no statistical differences in terms of age, gender, smoking history, systolic blood pressure, and diastolic blood pressure between the two groups (\u003cem\u003ep\u003c/em\u003e\u0026gt; 0.05). Further details can be found in Supplementary table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of Test Results between ARAS and non-ARAS Groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComparison of the test results between the ARAS and non-ARAS groups revealed significant differences in several parameters. The ARAS group showed higher levels of white blood cells (WBC), platelets (PLT), neutrophils (NE), triglycerides (TG), serum creatinine (Scr), cystatin C, glycated hemoglobin (HbA1c), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR) compared to the non-ARAS group. Conversely, lymphocyte count (LYM) and high-density lipoprotein cholesterol (HDL-C) levels were lower in the ARAS group (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05). However, there were no statistically significant differences observed in red blood cell distribution width (RDW), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and lipoprotein(a) between the ARAS and non-ARAS groups (\u003cem\u003ep\u003c/em\u003e\u0026gt; 0.05). Further details can be found in Supplementary table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of Test Results between Moderate and Severe Stenosis Groups in ARAS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn ARAS patients, the severe stenosis group showed significantly higher levels of WBC, NE, HbA1c, and NLR compared to the moderate stenosis group (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). No significant differences were observed in RDW, LYM, PLT, TC, TG, HDL-C, LDL-C, lipoprotein(a), Scr, cystatin C, and PLR between the severe and moderate stenosis groups (\u003cem\u003ep\u003c/em\u003e\u0026gt; 0.05). Refer to Supplementary table 4 for details.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation analysis of NLR, PLR and ARSA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the relationship between PLR, NLR, and ARAS, as well as the degree of stenosis, a correlation analysis was performed. Since NLR and PLR did not follow a normal distribution according to the normality test, Spearman rank correlation was utilized. The results revealed a significant positive correlation between NLR and ARAS, with a correlation coefficient of 0.251 (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05). Similarly, exhibited a significant positive correlation with ARAS, with a correlation coefficient of 0.199 (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05). There was a significant positive correlation between NLR and the degree of stenosis, with a correlation coefficient of 0.152 (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05). However, no significant correlation was observed between PLR and the degree of stenosis (\u003cem\u003ep\u003c/em\u003e\u0026gt; 0.05). For detailed results, please refer to Tables 1 and 2.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\"\u003e\n \u003cp\u003eTables 1.\u0026nbsp;Correlation analysis of NLR, PLR and ARAS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.273056057866185%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.72694394213381%\" colspan=\"2\"\u003e\n \u003cp\u003eARAS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.2129963898917%\" valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.39350180505415%\" valign=\"top\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.39350180505415%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.2129963898917%\" valign=\"top\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.39350180505415%\" valign=\"top\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.39350180505415%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\"\u003e\n \u003cp\u003eTables 2. Correlation analysis of PLR, NLR and\u0026nbsp;Degree of\u0026nbsp;ARAS stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.273056057866185%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.72694394213381%\" colspan=\"2\"\u003e\n \u003cp\u003eDegree of ARAS stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.2129963898917%\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.39350180505415%\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.39350180505415%\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.2129963898917%\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.39350180505415%\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.39350180505415%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate logistic regression analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the potential associations between general data, test results, and examination findings of the two groups, univariate logistic regression analysis was performed using the presence of ARAS as the dependent variable. The analysis identified age, systolic blood pressure, WBC, PLT, NE, LYM, HDL-C, Scr, cystatin C, PLR and NLR as risk factors for ARAS (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05). Please refer to Supplementary table5 for detailed results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate logistic regression analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo account for the possibility of multicollinearity among the blood cell parameters (WBC, NE, PLT, and LYM), their variance inflation factor (VIF) values were assessed. It was found that the VIF values for WBC and NE exceeded 10 , indicating the presence of multicollinearity. Therefore, WBC and NE were excluded from further analysis. The remaining indicators were examined for covariance, and their VIF values were below 10, indicating the absence of multicollinearity.\u003c/p\u003e\n\u003cp\u003eSubsequently, the other significant indicators identified in the univariate logistic regression analysis were included in the multivariate logistic regression analysis. The results demonstrated that age, HDL-C, PLR, and NLRwere independent risk factors for the occurrence of ARAS. Please refer to Table 3 for detailed findings.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003eTable 3. Multivariate logistic regression analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eWald\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e32.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.028~1.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eHDL-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e6.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e0.372~0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eScr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e11.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.005~1.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.023~1.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e8.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e1.003~1.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: HDL-C, high-density lipoprotein cholesterol; Scr, serum creatinine; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacterization of ROC curves for PLR and NLR in predicting ARAS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe predictive ability of PLR and NLR for ARAS was assessed using ROC curve analysis. The AUC for PLR in predicting ARAS was 0.620 (95% CI: 0.584 to 0.657), with an optimal diagnostic cut-off value of 145.88. The sensitivity and specificity were determined to be 45.3% and 74.1%, respectively (Figure 1A). Similarly, the ROC curve for NLR in predicting ARAS yielded an AUC of 0.653 (95% CI: 0.617 to 0.787). The optimal diagnostic cut-off value for NLR was identified as 2.52, with a sensitivity of 49.2% and a specificity of 75.9% (Figure 1B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacterization of ROC Curves for PLR and NLR in Predicting ARAS Stenosi\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eROC curve analysis was conducted to assess the predictive capacity of PLR and NLR for the degree of ARAS stenosis. The AUC for PLR in predicting the degree of ARAS stenosis was 0.519 (\u003cem\u003ep\u003c/em\u003e=0.570), indicating that PLR does not possess significant predictive value for the degree of ARAS stenosis (Figure 2A). In contrast, the ROC curve for NLR in predicting ARAS stenosis yielded an AUC of 0.597 (95% CI: 0.531 to 0.663). The optimal diagnostic cut-off value for NLR was determined to be 2.32, with a sensitivity of 62.8% and a specificity of 59.6% (Figure 2B).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCardiovascular diseases has become a significant health concern in China due to improved living standards and an aging population. ARAS, accounting for 1%-3% of hypertensive patients, is a reversible cause of age-related hypertension, as well as chronic cardiac and renal insufficiency. However, the insidious onset and lack of specific clinical manifestations make early detection challenging. Renal arteriography, the main diagnostic tool, is invasive and limited in its use as a screening tool. Therefore, identifying risk factors for ARAS is crucial for early detection and avoiding unnecessary renal arteriography.\u003c/p\u003e\n\u003cp\u003eOur study revealed that age, systolic blood pressure, triglycerides, glycated hemoglobin in the patients of ARAS group were significantly higher than those in the non-ARAS group. HDL-C levels were significantly lower in the ARAS group compared to the non-ARAS group.\u003c/p\u003e\n\u003cp\u003eAge, diabetes, and hypertension are common risk factors for ARAS and contribute to the progression of renal artery stenosis and various cardiovascular diseases. Advanced age, female gender, and a history of hypertension are significant risk factors for ARAS\u003csup\u003e11\u003c/sup\u003e. Hypertension is the most prevalent high-risk factor for cardiovascular disease, emphasizing the importance of effective blood pressure control. Diabetes also debated as an independent risk factor for ARAS. In our study, the proportion of diabetic patients and HbA1c levels were also significantly higher in the severe stenosis group compared to the moderate stenosis group.\u003c/p\u003e\n\u003cp\u003eDyslipidemia\u0026nbsp;is a significant risk factor for ARAS\u003csup\u003e12\u003c/sup\u003e.\u0026nbsp;Elevated TG is a central feature of the atherogenic dyslipidemia complex\u003csup\u003e13\u003c/sup\u003e. which encompasses depressed HDL-C and elevated small dense LDL particles, both of which are themselves plausibly causally related to atherosclerosis\u003csup\u003e14\u003c/sup\u003e. HDL-C, known for its protective role against atherosclerosis, promotes reverse cholesterol transport and has anti-inflammatory, anti-oxidant, and endothelial repair properties\u003csup\u003e15,16\u003c/sup\u003e. In our study, LDL-C levels did not show a significant difference between the ARAS and non-ARAS groups, possibly due to prior statin therapy in hypertensive patients.\u003c/p\u003e\n\u003cp\u003eOur results showed that the white blood cells, platelets, neutrophils in the ARAS group were significantly higher than those in the non-ARAS group; The lymphocytes in ARAS patients were significantly lower than those of non-ARAS group. Previous studies have demonstrated that elevated levels of neutrophils and platelets together, along with reduced levels of lymphocytes, are associated with vascular diseases\u003csup\u003e17,18\u003c/sup\u003e. Platelets not only contribute to thrombosis but also release inflammatory factors and mediators, thereby promoting inflammatory reactions\u003csup\u003e19\u003c/sup\u003e. Increased platelet count can activate platelets, leading to the release of pro-inflammatory mediators from endothelial cells and leukocytes. This process facilitates monocyte adhesion, migration, and the aggregation of leukocytes in damaged vascular endothelium, thereby initiating and promoting the development of atherosclerotic lesions\u003csup\u003e20\u003c/sup\u003e. In contrast, neutrophils exhibit a non-specific inflammatory response in endothelial atherosclerotic plaques. The inflammatory response increases neutrophil production and releases various active components involved in activation, migration, tissue infiltration, and interaction with vascular endothelial cells. These processes accelerate the progression of atherosclerotic thrombosis\u003csup\u003e21\u003c/sup\u003e.Lymphocytes produce cytokines that inhibit cell proliferation and promote cell death. Lymphocyte apoptosis has been observed in atherosclerotic lesions involved in atherosclerotic plaque growth, lipid core development, plaque rupture, and thrombosis.\u003c/p\u003e\n\u003cp\u003eNLR and PLR are involved in different immunological pathways and activate the nonspecific inflammatory response by increasing the neutrophil or platelet count\u003csup\u003e22,23\u003c/sup\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003ePLR and NLR are markers that combine information on hemostasis and inflammation, with high sensitivity for demonstrating the inflammatory process\u003csup\u003e24,25\u003c/sup\u003e.\u003cem\u003e\u0026nbsp;\u003c/em\u003eSeveral studies suggest that NLR and PLR can be markers of inflammatory activity in various diseases\u003csup\u003e26,27\u003c/sup\u003e.\u003cem\u003e\u0026nbsp;\u003c/em\u003eOur study first found PLR and NLR in the patients of ARAS group were significantly higher than those in the non-ARAS group. There is a significant positive correlation between PLR, NLR and ARAS, NLR is also positively correlated with the degree of stenosis in ARAS. These results suggested an association with the chronic inflammatory process in ARAS. However, their accuracy and sensitivity for predicting ARAS were limited, as indicated by the AUC values. Multivariate logistic regression analysis confirmed PLR and NLR as independent risk factors for ARAS.\u003c/p\u003e\n\u003cp\u003eLimitations of this study: Firstly, this study was retrospective and had limitations due to human and time constraints, which may have introduced bias and affected the final results. Secondly, the study did not follow the patients over a long period, making it difficult to assess the dynamic changes in PLR and NLR and their relationship with ARAS. Consequently, the study did not fully evaluate the impact of ARAS on PLR and NLR. Finally, the study only examined the correlation between some routine blood parameters and ARAS, without including other parameters or common inflammation indicators. Therefore, it was not possible to determine the influence of other routine blood parameters on the study or whether they could be combined with other inflammation indicators to predict the occurrence of ARAS. Further extensive research is needed to explore and confirm these findings.\u003c/p\u003e\n\u003cp\u003eIn summary, the elevated levels of NLR and PLR are found to be associated with an increased risk of developing ARAS In this retrospective study. The higher the NLP, the more severe the stenosis of ARAS.NLR and PLR have the potential to be a means of diagnosing ARSA.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Population:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA retrospective analysis was conducted on a cohort of 1026 patients diagnosed with hypertension who underwent renal arteriography at the Department of Cardiovascular Medicine, First Affiliated Hospital of Guangxi Medical University, between January 2020 and December 2022. Relevant patient information, including smoking history, diabetes history, and demographic characteristics such as age, sex, height, and weight, was recorded. All patients underwent routine blood tests, renal function assessments, lipid profiles, glycosylated hemoglobin measurements, and renal arteriography. Patients were categorized into the ARAS (renal artery stenosis) group (n=362) or the non-ARAS group (n=664) based on the presence or absence of renal artery stenosis. It should be noted that this research was conducted in accordance with the purpose of the Declaration of Helsinki and its amendments, and approved by the Ethics Committee of The First Affiliated Hospital of Guangxi Medical University (Number: 2024-E045-01). The patients/participants provided a signed informed consent form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Inclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(1) Patients who met the diagnostic criteria for hypertension according to the 2018 Chinese guidelines for the prevention and treatment of hypertension. (2) Patients who provided informed consent and understood the purpose of renal arteriography. (3) Patients with complete accurate data and information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Exclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(1) Patients with incomplete clinical data. (2) Patients with severe hepatic or renal insufficiency or malnutrition. (3) Patients with acute or chronic infections, malignancies, hematological disorders, tumors, tuberculosis, or other diseases. (4) Patients with a recent history of acute myocardial infarction or decompensated heart failure. (5) Patients diagnosed with other causes of renal stenosis, such as fibromuscular dysplasia or Takayasu arteritis. (6) Patients diagnosed with other types of secondary hypertension. (7) Patients with a previous history of renal artery stent implantation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Diagnostic Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(1) ARAS: Diagnosis required the presence of at least one risk factor for atherosclerosis (age over 40 years, long-term smoking, diabetes, hyperlipidemia) and kidney artery angiography showing a \u0026ge;50% decrease in the diameter of the main trunk and/or branches of the renal artery. Lesions typically involved the proximal segment and ostium of the renal artery, displaying eccentric stenosis, irregular plaques, and calcification. (2) Diagnosis followed the criteria outlined in the 2018 Chinese Guidelines for the Prevention and Treatment of Hypertension\u003csup\u003e28\u003c/sup\u003e, including systolic blood pressure \u0026ge; 140mmHg and/or diastolic blood pressure \u0026ge; 90mmHg measured on different days or currently taking antihypertensive medication. (3) Diabetes: Diagnosis followed the diagnostic criteria for diabetes proposed in the Chinese Guidelines for the Prevention and Treatment of Type 2 Diabetes in 2020\u003csup\u003e29\u003c/sup\u003e, including typical diabetes symptoms with elevated blood glucose levels or glycated hemoglobin \u0026ge; 6.5%.\u003c/p\u003e\n\u003cp\u003e(4) Smoking History: Defined as continuous smoking of at least one cigarette per day for more than one year or quitting smoking within the past six months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(1) General Data: Patient information including gender, age, height, weight, smoking history, diabetes history, and initial standard blood pressure measurement were obtained through comprehensive history-taking and precise measurements. Body Mass Index (BMI) was calculated using recorded height and weight. (2) Laboratory Test Results: Comprehensive documentation of laboratory test results included white blood cell count (WBC), platelet count (PLT), absolute neutrophil count (NE), absolute lymphocyte count (LYM), and red blood cell distribution width (RDW). Serum creatinine (Scr), cystatin C, lipid profile (total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and lipoprotein a), and glycated hemoglobin (HbA1c) levels were measured. Platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) were calculated as PLR = PLT/LYM and NLR = NE/LYM. (3) Renal Arteriography: percutaneous selective renal arteriography was performed by at least two qualified clinicians to evaluate the extent of luminal stenosis through visual diameter measurement. Patients were adequately informed about the purpose, potential risks, and precautionary measures associated with renal arteriography, and informed consent was obtained. (4) Group Classification: Based on renal arteriography findings, patients with renal artery stenosis \u0026ge;50% were classified into the ARAS group, while patients with stenosis \u0026lt;50% were classified into the non-ARAS group. Within the ARAS group, further classification was made based on stenosis severity into a moderate stenosis group (50% to 70% stenosis) and a severe stenosis group (\u0026ge;70% stenosis) using the classification criteria recommended by the Society for Cardiovascular Angiography and Interventions in 2014\u003csup\u003e30\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using SPSS 27.0 software. Group differences were analyzed using independent samples t-test, Mann-Whitney U test, or chi-square test as appropriate. Spearman\u0026apos;s rank correlation analysis was used to assess the correlation between PLR, NLR, and ARAS. Logistic regression models were employed to analyze the risk factors for ARAS. The predictive value of PLR and NLR for renal artery stenosis was assessed using ROC curves. Statistical significance was set at \u003cem\u003ep\u0026nbsp;\u003c/em\u003evalue \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eGX designed the experiments. GX, YHT, YPW, KRL, XFH analyzed the data. YPW and JSW collected the patients. YPW, GX and YHT wrote the manuscript. All au-thors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe datasets used or analysed during the current study are available from the corresponding author on reasonable .\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWhite, C. J. \u0026amp; Olin, J. W. Diagnosis and management of atherosclerotic renal artery stenosis: improving patient selection and outcomes. \u003cem\u003eNat Clin Pract Cardiovasc Med\u003c/em\u003e 6, 176-190, doi:10.1038/ncpcardio1448 (2009).\u003c/li\u003e\n\u003cli\u003eThe, W. Report on Cardiovascular Health and Diseases in China 2022: an Updated Summary. \u003cem\u003eBiomed Environ Sci\u003c/em\u003e 36, 669-701, doi:10.3967/bes2023.106 (2023).\u003c/li\u003e\n\u003cli\u003ePappaccogli, M.\u003cem\u003e et al.\u003c/em\u003e Endovascular Versus Medical Management of Atherosclerotic Renovascular Disease: Update and Emerging Concepts. \u003cem\u003eHypertension\u003c/em\u003e 80, 1150-1161, doi:10.1161/hypertensionaha.122.17965 (2023).\u003c/li\u003e\n\u003cli\u003ede Bhailis, \u0026Aacute;.\u003cem\u003e et al.\u003c/em\u003e Managing acute presentations of atheromatous renal artery stenosis. \u003cem\u003eBMC Nephrol\u003c/em\u003e 23, 210, doi:10.1186/s12882-022-02813-8 (2022).\u003c/li\u003e\n\u003cli\u003eTan, Q.\u003cem\u003e et al.\u003c/em\u003e The Mechanism and Role of N(6)-Methyladenosine (m(6)A) Modification in Atherosclerosis and Atherosclerotic Diseases. \u003cem\u003eJ Cardiovasc Dev Dis\u003c/em\u003e 9, doi:10.3390/jcdd9110367 (2022).\u003c/li\u003e\n\u003cli\u003eHou, P.\u003cem\u003e et al.\u003c/em\u003e Macrophage polarization and metabolism in atherosclerosis. \u003cem\u003eCell Death Dis\u003c/em\u003e 14, 691, doi:10.1038/s41419-023-06206-z (2023).\u003c/li\u003e\n\u003cli\u003eTudurachi, B. S., Anghel, L., Tudurachi, A., Sascău, R. A. \u0026amp; Stătescu, C. Assessment of Inflammatory Hematological Ratios (NLR, PLR, MLR, LMR and Monocyte/HDL-Cholesterol Ratio) in Acute Myocardial Infarction and Particularities in Young Patients. \u003cem\u003eInt J Mol Sci\u003c/em\u003e 24, doi:10.3390/ijms241814378 (2023).\u003c/li\u003e\n\u003cli\u003eHuang, L. Y.\u003cem\u003e et al.\u003c/em\u003e Associations of the neutrophil to lymphocyte ratio with intracranial artery stenosis and ischemic stroke. \u003cem\u003eBMC Neurol\u003c/em\u003e 21, 56, doi:10.1186/s12883-021-02073-3 (2021).\u003c/li\u003e\n\u003cli\u003eLi, H., Zhou, Y., Ma, Y., Han, S. \u0026amp; Zhou, L. The prognostic value of the platelet-to-lymphocyte ratio in acute coronary syndrome: a systematic review and meta-analysis. \u003cem\u003eKardiol Pol\u003c/em\u003e 75, 666-673, doi:10.5603/KP.a2017.0068 (2017).\u003c/li\u003e\n\u003cli\u003eSharma, D. \u0026amp; Gandhi, N. 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J.\u003cem\u003e et al.\u003c/em\u003e SCAI appropriate use criteria for peripheral arterial interventions: An update. \u003cem\u003eCatheter Cardiovasc Interv\u003c/em\u003e 90, E90-e110, doi:10.1002/ccd.27141 (2017).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Atherosclerotic Renal Artery Stenosis, Platelet-to-Lymphocyte Ratio, Neutrophil-to-Lymphocyte Ratio","lastPublishedDoi":"10.21203/rs.3.rs-3829803/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3829803/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThere is still a lack of effective non-invasive diagnosis of atherosclerotic renal stenosis. The aim of this study was to investigate the association of platelet to lymphocyte ratio (PLR) and neutrophil to lymphocyte ratio (NLR) with atherosclerotic renal artery stenosis (ARAS). Data of a total of 1062 patients (362 ARAS, 664 non-ARAS) were collected. Logistic regression analysis and receiver operating characteristic curve analysis was used to analyze the collected patient data. NLR and PLR levels were significantly increased in ARAS group compared with non-ARAS group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Correlation analysis showed that both NLR and PLR were positively correlated with ARAS (r\u0026thinsp;=\u0026thinsp;0.199, r\u0026thinsp;=\u0026thinsp;0.251, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and only NLR was positively correlated with the degree of stenosis of ARAS (r\u0026thinsp;=\u0026thinsp;0.152, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Multivariate logistic regression showed that NLR (OR\u0026thinsp;=\u0026thinsp;1.203, 95%CI\u0026thinsp;=\u0026thinsp;1.023\u0026thinsp;~\u0026thinsp;1.046, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025) and PLR (OR\u0026thinsp;=\u0026thinsp;1.011, 95%CI\u0026thinsp;=\u0026thinsp;1.003\u0026thinsp;~\u0026thinsp;1.019, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) were independent risk factors for ARAS. The ROC curve indicated that the diagnostic value of NLR and PLR were (AUC\u0026thinsp;=\u0026thinsp;0.653, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; AUC\u0026thinsp;=\u0026thinsp;0.62, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In conclusion, elevated levels of NLR and PLR are associated with an increased risk of developing ARAS. NLR and PLR have the potential to be a means of diagnosing ARSA.\u003c/p\u003e","manuscriptTitle":"Elevated serum NLR and PLR are associated with a higher risk of atherosclerotic renal stenosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-30 17:52:58","doi":"10.21203/rs.3.rs-3829803/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2cfea65e-969e-4a21-840a-afbc659b3904","owner":[],"postedDate":"January 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28412368,"name":"Health sciences/Cardiology"},{"id":28412369,"name":"Health sciences/Diseases"},{"id":28412370,"name":"Health sciences/Nephrology"},{"id":28412371,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-08-12T07:55:16+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-30 17:52:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3829803","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3829803","identity":"rs-3829803","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}