Advances in Clinical Medicine
Vol. 13  No. 08 ( 2023 ), Article ID: 70933 , 7 pages
10.12677/ACM.2023.1381860

中性粒细胞/淋巴细胞比值与痛风患者肾功能 损伤的相关性分析

张福云,赵娜,汤艳春*

青岛大学附属烟台毓璜顶医院风湿免疫科,山东 烟台

收稿日期:2023年7月21日;录用日期:2023年8月14日;发布日期:2023年8月21日

摘要

目的:分析中性粒细胞/淋巴细胞的比值(NLR)与痛风患者肾功能损伤的相关性。方法:收集2022年1月至2022年12月在青岛大学附属烟台毓璜顶医院风湿科诊治的484例痛风患者的临床资料。根据e-GFR将患者分为肾功能损伤组(105例)和肾功能正常组(379例),分析两组患者的一般临床资料、血常规、生化及炎症指标的差异,并采用多因素Logistic回归分析痛风患者肾功能损伤的危险因素。结果:肾功能损伤组患者的女性占比、年龄、病程、合并慢性疾病(高血压病、糖尿病)比例、NLR、红细胞分布宽度、肌酐、胱抑素C、C反应蛋白明显高于肾功能正常组,而红细胞、血红蛋白、淋巴细胞、高密度脂蛋白胆固醇明显低于肾功能正常组,差异具有统计学意义(P < 0.05)。多因素Logistic回归显示年龄、NLR及肌酐是痛风患者发生肾功能损伤的独立危险因素(P < 0.05)。结论:痛风患者肾功能损伤受多个因素影响,NLR值升高是肾功能损伤的独立危险因素。

关键词

痛风,肾功能损伤,中性粒细胞/淋巴细胞比值,危险因素

Correlation between Neutrophil to Lymphocyte Ratio and Renal Function Damage in Gout Patients

Fuyun Zhang, Na Zhao, Yanchun Tang*

Department of Rheumatology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai Shandong

Received: Jul. 21st, 2023; accepted: Aug. 14th, 2023; published: Aug. 21st, 2023

ABSTRACT

Objective: To investigate the correlation between neutrophil to lymphocyte ratio and renal function damage in gout patients. Methods: A total of 484 gout patients treated in the Department of Rheumatology, Yantai Yuhuangding Hospital affiliated to Qingdao University from January 2022 to December 2022 were collected and divided into renal function damage group (105 cases) and normal renal function grout (379 cases) according to e-GFR. The differences in general clinical data, blood routine, biochemical and inflammatory indicators between the two groups were analyzed, and multivariate logistic regression was used to analyze the risk factors of renal function damage in gout patients. Results: The proportion of females, age, course of disease, proportion of chronic diseases (hypertension, diabetes), NLR, red blood cell distribution width, creatinine, cystatin C and C-reactive protein in renal function damage group were significantly higher than those in normal renal function group, while the red blood cell, hemoglobin, lymphocyte and high-density lipoprotein cholesterol were significantly lower than those in normal renal function group, the difference was statistically significant (P < 0.05). Multivariate analysis showed that age, NLR and creatinine were the independent risk factors for renal function damage in gout patients (P < 0.05). Conclusion: Renal function damage in gout patients is influenced by multiple factors, and the increase of NLR is an independent risk factor for renal function damage.

Keywords:Gout, Renal Function Damage, Neutrophil to Lymphocyte Ratio, Risk Factors

Copyright © 2023 by author(s) and Hans Publishers Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

http://creativecommons.org/licenses/by/4.0/

1. 引言

痛风是由尿酸钠晶体沉积在关节或非关节结构中所致的一组异质性疾病。随着生活条件的提高,痛风的患病率呈逐年上升和年轻化趋势 [1] [2] 。肾脏是痛风最常累及的器官之一,英国一项荟萃分析发现24%痛风患者合并3期及以上的肾功能损伤 [3] 。在临床工作中,若不能及时发现痛风性肾损伤的高危患者并积极采取干预措施,患者一旦进展为终末期肾病,严重影响患者生活质量,并给家庭和社会造成严重的经济负担 [4] [5] 。因此,探索痛风性肾功能损伤的危险因素,对预防与延缓其发生、发展、改善患者生活质量有重要意义。目前已有研究证明炎症反应在痛风及其肾功能损伤中发挥至关重要的作用。中性粒细胞/淋巴细胞(neutrophil to lymphocyte ratio, NLR)作为新型、廉价的炎症标志物 [6] ,已被证实与急性肾损伤 [7] 、糖尿病肾病 [8] 、狼疮性肾炎 [9] 等疾病密切相关。目前对NLR与痛风性肾损害的相关性研究较少,本研究回顾性分析痛风患者的临床资料,探讨NLR与痛风性肾功能损伤的相关性,寻找肾功能损伤的可能危险因素,为临床上早期识别高危患者提供价值参考。

2. 资料与方法

2.1. 研究对象

回顾性分析2022年1月至2022年12月期间在青岛大学附属烟台毓璜顶医院诊疗的484例痛风患者的临床资料。纳入标准:1) 均符合2015年美国风湿病学会和欧洲抗风湿病联盟联合诊断的痛风分类标准 [10] ;2) 基线资料、血液学资料完整;3) 患者及家属同意参加本项研究,并签署知情同意书。排除标准:1) 处于急性感染期;2) 合并恶性肿瘤、血液系统疾病;3) 类风湿性关节炎、骨关节炎等其他自身免疫性疾病;4) 近期使用过影响白细胞生成的药物;5) 其他肾脏疾病患者,包括原发性肾小球疾病、急性肾损害等。本研究经青岛大学附属医院烟台毓璜顶医院伦理委员会批准。(批件号:烟毓医伦理审2023-300)

2.2. 研究方法

2.2.1. 一般资料

收集患者的年龄、性别、病程、高血压病史、糖尿病病史、秋水仙碱、非布司他及非甾体抗炎药用药史等一般临床资料。

2.2.2. 实验室资料

收集患者禁食一夜后的清晨血样,采用日本Sysmex XN-9000全自动血液分析仪及其配套试剂检测血常规及炎症指标,包括:血细胞(WBC)、血红蛋白(HGB)、红细胞分布宽度(RDW-SD)、白细胞(WBC)、中性粒细胞(NEU)、淋巴细胞(LYM)、单核细胞(MNC)、血小板(PLT)、血沉(ESR)、C反应蛋白(CRP)并计算中性粒细胞/淋巴细胞(NLR)。采用Stream全自动生化分析仪及其配套试剂检测生化,收集指标包括:血清尿酸(SUA)、肌酐(CRE)、胱抑素C(CysC)、高密度脂蛋白胆固醇(HDL-C),并计算单核细胞/高密度脂蛋白胆固醇(MHR)。采用CKD-EPI [11] 方程计算eGFR,根据e-GFR将痛风患者分为肾功能损伤组[eGFR < 90 ml/(min·1.73 m2)]和肾功能正常组[eGFR ≥ 90 ml/(min·1.73 m2)]。

2.3. 统计方法

应用SPSS 25.0软件对数据进行统计分析,若定量资料服从正态分布,采用 x ¯ ± s 表示,两独立样本t检验进行组间比较;若定量资料服从非正态分布,采用[M (Q1, Q3)]表示,秩和检验进行组间比较;定性资料采用[n (%)]表示,组间比较采用c2检验。采用多因素logistic回归分析,筛选痛风性肾功能损伤的危险因素。P < 0.05为差异有统计学意义。

3. 结果

3.1. 两组患者一般临床资料的比较

本研究共纳入484例痛风患者,其中肾功能损伤组105例(21.69%),肾功能正常组379例(78.31%)。肾功能损伤组患者的女性占比、年龄、病程、合并慢性疾病(高血压病、糖尿病)比例明显高于肾功能正常组,差异具有统计学意义(P < 0.05)。两组患者在秋水仙碱、非布司他及非甾体抗炎药用药史方面的差异无统计学意义(P > 0.05),见表1

Table 1. Comparison of general clinical data between gout patients with and without renal function damage

表1. 肾功能损伤组与肾功能正常组患者一般临床资料的比较

注:a表示χ2值,b表示Z值,余检验统计量为t值。

3.2. 两组患者血常规指标的比较

肾功能损伤组患者RDW-SD、NLR明显高于肾功能正常组,而RBC、HGB、LYM明显低于肾功能正常组,差异具有统计学意义(P < 0.05)。两组患者在PLT、WBC、NEU、EOS、BAS差异无统计学意义(P > 0.05),见表2

Table 2. Comparison of blood routine indicators between gout patients with and without renal function damage

表2. 肾功能损伤组与肾功能正常组患者血常规指标的比较

注:a表示χ2值,b表示Z值,余检验统计量为t值;RBC = 红细胞,HGB = 血红蛋白,RDW-SD = 红细胞分布宽度SD,PLT = 血小板,WBC = 白细胞,NEU = 中性粒细胞,LYM = 淋巴细胞,MNC = 单核细胞,NLR = 中性粒细胞/淋巴细胞,EOS = 嗜酸性粒细胞,BAS = 嗜碱性粒细胞。

3.3. 两组患者生化及炎症指标的比较

肾功能损伤组患者CER、CysC、CRP明显高于肾功能正常组,而HDL-C明显低于肾功能正常组,差异具有统计学意义(P < 0.05)。两组患者在SUA、GLU、TIBL、MHR差异无统计学意义(P > 0.05),见表3

Table 3. Comparison of biochemical and inflammatory indicators between gout patients with and without renal function damage

表3. 肾功能损伤组与肾功能正常组患者生化及炎症指标的比较

注:a表示χ2值,b表示Z值,余检验统计量为t值;SUA = 血清尿酸,CER = 肌酐,CysC = 胱抑素C,GLU = 葡萄糖,HDL-C = 高密度脂蛋白胆固醇,TBIL = 总胆红素MHR = 单核细胞/高密度脂蛋白胆固醇,CRP = C反应蛋白。

3.4. 痛风性肾损伤的多因素Logistic回归分析

以痛风患者是否发生肾功能损伤为因变量(赋值:肾功能损伤 = 1,肾功能正常 = 0),将组间比较有统计学意义的指标:性别(赋值:男性 = 1,女性 = 0),高血压(赋值:有 = 1,无 = 0)、糖尿病(赋值:有 = 1,无 = 0)、余年龄、病程、RBC、HGB、RDW-SD、LYM、NLR、CER、CysC、HDL-C、CRP (赋值均为实测值)作为自变量纳入多因素Logistic回归分析,结果显示年龄、CER及NLR是痛风患者发生肾功能损伤的独立危险因素,见表4

Table 4. Multivariate Logistic regression analysis of renal function damage in gout patients

表4. 痛风性肾功能损伤多因素Logistics回归分析

4. 讨论

痛风是一种与嘌呤代谢紊乱和/或尿酸排泄障碍所致的高尿酸血症直接相关的炎症性疾病。血中尿酸浓度呈过饱和状态,尿酸盐晶体在肾内长期沉积可导致痛风性肾损伤。尿酸可通过促进炎症反应、破坏内皮细胞、激活肾素–血管紧张素系统(RAS)和抑制一氧化氮合酶等机制损伤肾小管间质和肾血管 [12] [13] [14] ,破坏肾脏功能,而肾脏功能受损会导致尿酸排泄障碍,加速上述过程。如不及时干预,两者相互促进,痛风患者不可避免走向终末期肾病。因此,及时发现肾功能损伤,积极采取干预措施,对阻止疾病进展有重要价值。

NEU是血液循环中最常见的白细胞,是非特异性免疫反应的主要参与者,在痛风炎症反应中发挥着不可或缺的作用。尿酸钠晶体可通过破坏吞噬细胞的溶酶体 [15] 、改变细胞膜钾离子通透性 [16] 、激活Syk/磷脂酰肌醇-3激酶(PI3K)信号通路 [17] 等方式激活核苷酸结合寡聚化结构域样受体蛋白3 (NLRP3)炎症小体 [18] 。NLRP3促进巨噬细胞IL-1β和IL-18的分泌,这些细胞因子通过上调内皮细胞P-选择素和E-选择素的表达,促进NEU向关节炎症处招募和浸润 [19] [20] 。NEU与尿酸钠晶体相互作用,形成中性粒细胞外网状陷阱(neutrophil extracellular traps, NETs)。NETs中的组蛋白与髓过氧化物酶对肾上皮细胞和内皮细胞有潜在毒性,会导致肾小球损伤,激活自身免疫过程,诱发血管损伤并促进肾纤维化 [21] [22] 。此外,NEU水平增加,释放大量的炎症因子可诱导LYM的凋亡 [23] [24] 。NLR在一定程度上反映了先天性免疫和适应性免疫的平衡 [25] ,具有较高的稳定性,不受脱水、剧烈运动、病理等因素影响。在本研究中,痛风性肾功能损伤组的NLR明显高于肾功能正常组,多因素logistic回归显示NLR [OR = 2.675, 95% CI (1.114, 6.428), P = 0.028]为痛风性肾功能损伤的独立危险因素。NLR作为廉价、简单易得的临床指标,可能为早期诊断痛风性肾损伤提供新的方向,二者间存在的潜在联系也可能为治疗提供新的思路和靶点。

痛风性肾功能损伤组与肾功能正常组相比,发病年龄较大,为58.00 (44.00, 67.50)岁,有统计学意义(P < 0.05),提示肾功能损伤的发生与年龄有关。随着年龄的增长,肾脏的结构与功能发生变化 [26] [27] 。有报道称,一般从40岁开始,肾功能大约每10年会下降10%左右 [28] 。且部分老年痛风患者合并影响血流动力学稳定的慢性基础疾病,如高血压、糖尿病等,故肾损伤发生率较高。在此研究中,痛风性肾功能损伤组的女性占比更高(7.62% vs 0.79%),目前暂无肾功能损伤与性别的相关性,未来需进一步完善大样本、多中心、前瞻性研究明确两者关系。CysC是目前已知的评价早期肾功能损害的敏感指标 [29] ,其水平升高可在一定程度上反映肾小球功能受损。在此研究中,为痛风性肾功能损伤的独立危险因素。已有研究证明CRP不仅仅是炎症指标,还可能通过NF-κB和TGF-β/Smad3信号通路引起肾脏炎症和纤维化,在肾功能损伤的发展中起到致病作用 [30] [31] ,痛风性肾功能损伤组CRP明显高于非肾损伤组,进一步为此观点增添了统计学依据。

5. 总结

综上,NLR与痛风性肾功能损伤密切相关。在临床工作中,针对NLR明显升高的患者,应及时干预,阻止患者肾功能损伤进展,避免终末期肾病的出现。

文章引用

张福云,赵 娜,汤艳春. 中性粒细胞/淋巴细胞比值与痛风患者肾功能损伤的相关性分析
Correlation between Neutrophil to Lymphocyte Ratio and Renal Function Damage in Gout Patients[J]. 临床医学进展, 2023, 13(08): 13309-13315. https://doi.org/10.12677/ACM.2023.1381860

参考文献

  1. 1. Singh, J.A. and Gaffo, A. (2020) Gout Epidemiology and Comorbidities. Seminars in Arthritis and Rheumatism, 50, S11-S16. https://doi.org/10.1016/j.semarthrit.2020.04.008

  2. 2. 中华医学会, 中华医学会杂志社, 中华医学会全科医学分会, 等. 痛风及高尿酸血症基层诊疗指南(2019年) [J]. 中华全科医师杂志, 2020, 19(4): 293-303.

  3. 3. Roughley, M.J., Belcher, J., Mallen, C.D., et al. (2015) Gout and Risk of Chronic Kidney Disease and Nephrolithiasis: Meta-Analysis of Observational Studies. Arthritis Research & Therapy, 17, 90. https://doi.org/10.1186/s13075-015-0610-9

  4. 4. Li, Y., Ning, Y., Shen, B., et al. (2023) Temporal Trends in Prev-alence and Mortality for Chronic Kidney Disease in China from 1990 to 2019: An Analysis of the Global Burden of Disease Study 2019. Clinical Kidney Journal, 16, 312-321. https://doi.org/10.1093/ckj/sfac218

  5. 5. Ke, C., Liang, J., Liu, M., et al. (2022) Burden of Chronic Kidney Disease and Its Risk-Attributable Burden in 137 Low- and Mid-dle-Income Countries, 1990-2019: Results from the Global Burden of Disease Study 2019. BMC Nephrology, 23, Article No. 17. https://doi.org/10.1186/s12882-021-02597-3

  6. 6. Zahorec, R. (2021) Neutrophil-to-Lymphocyte Ratio, Past, Present and Future Perspectives. Bratislavske Lekarske Listy, 122, 474-488. https://doi.org/10.4149/BLL_2021_078

  7. 7. Chen, J.J., Kuo, G., Fan, P.C., et al. (2022) Neutro-phil-to-Lymphocyte Ratio Is a Marker for Acute Kidney Injury Progression and Mortality in Critically Ill Populations: A Population-Based, Multi-Institutional Study. Journal of Nephrology, 35, 911-920. https://doi.org/10.1007/s40620-021-01162-3

  8. 8. Li, L., Shen, Q. and Rao, S. (2022) Association of Neutro-phil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio with Diabetic Kidney Disease in Chinese Patients with Type 2 Diabetes: A Cross-Sectional Study. Therapeutics and Clinical Risk Management, 18, 1157-1166. https://doi.org/10.2147/TCRM.S393135

  9. 9. Soliman, W.M., Sherif, N.M., Ghanima, I.M., et al. (2020) Neutro-phil to Lymphocyte and Platelet to Lymphocyte Ratios in Systemic Lupus Erythematosus: Relation with Disease Activity and Lupus Nephritis. Reumatología Clínica (England Ed), 16, 255-261. https://doi.org/10.1016/j.reuma.2018.07.008

  10. 10. Neogi, T., Jansen, T.L., Dalbeth, N., Fransen, J., et al. (2015) 2015 Gout Classification Criteria: An American College of Rheumatology/European League against Rheumatism Collab-orative Initiative. Annals of the Rheumatic Diseases, 74, 1789-1798. https://doi.org/10.1136/annrheumdis-2015-208237

  11. 11. Levey, A.S., Stevens, L.A., Schmid, C.H., et al. (2009) A New Equation to Estimate Glomerular Filtration Rate. Annals of Internal Medicine, 150, 604-612. https://doi.org/10.7326/0003-4819-150-9-200905050-00006

  12. 12. Waheed, Y., Yang, F. and Sun, D. (2021) Role of Asymptomatic Hyperuricemia in the Progression of Chronic Kidney Disease and Cardiovascular Disease. The Korean Journal of Internal Medicine, 36, 1281-1293. https://doi.org/10.3904/kjim.2020.340

  13. 13. Mei, Y., Dong, B., Geng, Z., et al. (2022) Excess Uric Acid Induces Gouty Nephropathy through Crystal Formation: A Review of Recent Insights. Frontiers in Endocrinology (Lausanne), 13, Article ID: 911968. https://doi.org/10.3389/fendo.2022.911968

  14. 14. Srivastava, A., Kaze, A.D., Mcmullan, C.J., et al. (2018) Uric Acid and the Risks of Kidney Failure and Death in Individuals with CKD. American Journal of Kidney Diseases, 71, 362-370. https://doi.org/10.1053/j.ajkd.2017.08.017

  15. 15. Orlowski, G.M., Colbert, J.D., Sharma, S., et al. (2015) Multiple Cathepsins Promote Pro-IL-1beta Synthesis and NLRP3-Mediated IL-1beta Activation. The Journal of Immu-nology, 195, 1685-1697. https://doi.org/10.4049/jimmunol.1500509

  16. 16. Hari, A., Zhang, Y., Tu, Z., et al. (2014) Activation of NLRP3 In-flammasome by Crystalline Structures via Cell Surface Contact. Scientific Reports, 4, Article No. 7281. https://doi.org/10.1038/srep07281

  17. 17. 隋晓露, 许云鹏, 张燕子, 等. PI3K/AKT/NF-κB信号通路在大鼠尿酸性肾病中的作用机制[J]. 实用临床医药杂志, 2022, 26(18): 78-82.

  18. 18. Zhao, J., Wei, K., Jiang, P., et al. (2022) In-flammatory Response to Regulated Cell Death in Gout and Its Functional Implications. Frontiers in Immunology, 13, Ar-ticle ID: 888306. https://doi.org/10.3389/fimmu.2022.888306

  19. 19. Sil, P., Wicklum, H., Surell, C., et al. (2017) Macrophage-Derived IL-1beta Enhances Monosodium Urate Crystal-Triggered NET Formation. Inflammation Research, 66, 227-237. https://doi.org/10.1007/s00011-016-1008-0

  20. 20. Mitroulis, I., Kambas, K. and Ritis, K. (2013) Neu-trophils, IL-1beta, and Gout: Is There a Link? Seminars in Immunopathology, 35, 501-512. https://doi.org/10.1007/s00281-013-0361-0

  21. 21. Salazar-Gonzalez, H., Zepeda-Hernandez, A., Melo, Z., et al. (2019) Neutrophil Extracellular Traps in the Establishment and Progression of Renal Diseases. Medicina (Kaunas), 55, 431. https://doi.org/10.3390/medicina55080431

  22. 22. Zheng, F., Ma, L., Li, X., et al. (2022) Neutrophil Extracellu-lar Traps Induce Glomerular Endothelial Cell Dysfunction and Pyroptosis in Diabetic Kidney Disease. Diabetes, 71, 2739-2750. https://doi.org/10.2337/db22-0153

  23. 23. Agarwal, R. and Light, R.P. (2011) Patterns and Prognostic Value of Total and Differential Leukocyte Count in Chronic Kidney Disease. Clinical Journal of the American Society of Nephrology, 6, 1393-1399. https://doi.org/10.2215/CJN.10521110

  24. 24. Diakos, C.I., Charles, K.A., Mcmillan, D.C., et al. (2014) Can-cer-Related Inflammation and Treatment Effectiveness. The Lancet Oncology, 15, e493-e503. https://doi.org/10.1016/S1470-2045(14)70263-3

  25. 25. Buonacera, A., Stancanelli, B., Colaci, M., et al. (2022) Neu-trophil to Lymphocyte Ratio: An Emerging Marker of the Relationships between the Immune System and Diseases. In-ternational Journal of Molecular Sciences, 23, Article No. 3636. https://doi.org/10.3390/ijms23073636

  26. 26. 敖强国, 侯颉玢, 张雅宾, 等. 老年肾脏和急性肾损伤[J]. 中华保健医学杂志, 2020, 22(6): 659-662.

  27. 27. 陈泳清. 重症患者急性肾损伤发病特征及相关危险因素分析[D]: [硕士学位论文]. 南宁: 广西中医药大学, 2021.

  28. 28. Chung, S.M., Lee, D.J., Hand, A., et al. (2015) Kidney Function Changes with Aging in Adults: Compari-son between Cross-Sectional and Longitudinal Data Analyses in Renal Function Assessment. Biopharmaceutics and Drug Disposition, 36, 613-621. https://doi.org/10.1002/bdd.1988

  29. 29. Ferguson, T.W., Komenda, P. and Tangri, N. (2015) Cystatin C as a Biomarker for Estimating Glomerular Filtration Rate. Current Opinion in Nephrology and Hyper-tension, 24, 295-300. https://doi.org/10.1097/MNH.0000000000000115

  30. 30. Li, J., Chen, J., Lan, H.Y., et al. (2023) Role of C-Reactive Protein in Kidney Diseases. Kidney Disease (Basel), 9, 73-81. https://doi.org/10.1159/000528693

  31. 31. Johnson, N.H., Keane, R.W. and De Rivero Vaccari, J.P. (2022) Renal and Inflammatory Proteins as Biomarkers of Diabetic Kid-ney Disease and Lupus Nephritis. Oxidative Medicine and Cellular Longevity, 2022, Article ID: 5631099. https://doi.org/10.1155/2022/5631099

  32. NOTES

    *通讯作者。

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