慢性阻塞性肺疾病急性加重期血液生物标志物的研究进展
Research Progress on Blood Biomarkers in Acute Exacerbation of Chronic Obstructive Pulmonary Disease
DOI: 10.12677/jcpm.2026.51011, PDF, HTML, XML,   
作者: 孙晶雨:济宁医学院临床医学院(附属医院),山东 济宁;韩丽萍*:济宁市第一人民医院呼吸与危重症医学科,山东 济宁
关键词: 慢性阻塞性肺疾病血液标记物病情严重程度预后Chronic Obstructive Pulmonary Disease Blood Biomarkers Disease Severity Prognosis
摘要: 慢性阻塞性肺疾病(Chronic Obstructive Pulmonary Disease, COPD)简称慢阻肺,是一种进行性疾病,其主要特征是持续的气流受限、气道炎症以及全身效应或合并症。据统计,全世界约有5.45亿人患有COPD,是全球发病率和死亡率的第三大原因。慢性阻塞性肺疾病急性加重(Acute Exacerbation of Chronic Obstructive Pulmonary Disease, AECOPD)不仅并带来沉重的医疗保健费用负担,还会加速患者肺功能的丧失,显著增加其住院和死亡的风险。慢性阻塞性肺疾病发病机制复杂,近年来,有研究发现不同发病机制中血液生物学标志物在评估COPD严重程度及预后方面的存在潜在作用,因其客观、易获取的特性,在评估病情严重程度和预测预后方面展现出重要价值,本文将从血液生物学标志物对AECOPD严重程度的评估及预后影响进行综述。
Abstract: Chronic Obstructive Pulmonary Disease (COPD), often referred to as chronic obstructive lung disease, is a progressive condition characterized primarily by persistent airflow limitation, airway inflammation, and systemic effects or comorbidities. According to statistics, approximately 545 million people worldwide suffer from COPD, making it the third leading cause of morbidity and mortality globally. Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD) not only imposes a heavy burden on healthcare costs but also accelerates the loss of patients’ lung function, significantly increasing their risk of hospitalization and death. The pathogenesis of COPD is complex. In recent years, studies have revealed the potential role of blood biomarkers in evaluating the severity and prognosis of COPD across different pathogenic mechanisms. Due to their objective and easily accessible nature, these biomarkers demonstrate significant value in assessing disease severity and predicting outcomes. This review will summarize the impact of blood biomarkers on the evaluation of AECOPD severity and prognosis.
文章引用:孙晶雨, 韩丽萍. 慢性阻塞性肺疾病急性加重期血液生物标志物的研究进展[J]. 临床个性化医学, 2026, 5(1): 67-73. https://doi.org/10.12677/jcpm.2026.51011

1. 引言

慢性阻塞性肺疾病的发病机制主要与炎症因子、营养免疫、氧化应激等方面有关,随着病情的进展,COPD的一个主要病理特征是气道炎症和重塑,由于气管壁增厚增加导致的气道狭窄、粘液阻塞和肺实质破坏伴肺弹性丧失[1] [2],表现为持续、进行性气流受限,从而使气道和肺部发生不可逆的结构变化,最终导致呼吸衰竭。了解不同发病机制中血液标记物的特点,有助于评估慢阻肺患者病情严重程度和预测预后,指导临床决策。

2. 炎症因子机制

2.1. 嗜酸性粒细胞

嗜酸性粒细胞(Eosinophil, EOS)、C-反应蛋白(C-reactive protein, CRP)、降钙素原(Procalcitonin, PCT)都属于血液标志物中的炎症指标,其中,嗜酸性粒细胞计数被认为是AECOPD的重要生物标志物,嗜酸性粒细胞是关键的免疫反应介质和炎症细胞,具有多种功能[3],作为血液生物标志物,它具有为慢性阻塞性肺疾病患者治疗决策提供信息的潜力。Tashkin [4]等人发现在一些COPD患者中,嗜酸性粒细胞一方面会导致炎症促进气道阻塞,另一方面发现其在预防COPD急性加重期具有作为指导治疗的生物标志物的潜力。Kwok [5]等人通过一项前瞻性研究发现慢阻肺急性加重期患者血嗜酸性粒细胞与稳定期水平差异越大,患者预后越差。Bafadhel [6]等人根据外周嗜酸性粒细胞和其他炎症生物标志物确定了一种嗜酸性粒细胞为主的表型。嗜酸性粒细胞性AECOPD的鉴定通常基于血液检查,血液嗜酸性粒细胞可以作为痰嗜酸性粒细胞计数替代指标[7]。嗜酸性粒细胞水平可以预测皮质类固醇治疗AECOPD患者的治疗效果[8],与非嗜酸性粒细胞性AECOPD相比,目前有研究发现使用全身性皮质类固醇的治疗方法可能更有益于嗜酸性粒细胞性AECOPD患者,血嗜酸性粒细胞水平较高的AECOPD患者C反应蛋白和白细胞计数如果较低,接受全身性皮质类固醇治疗预后会更好[9]。因此,血嗜酸性粒细胞和感染生物标志物的组合可能不仅有助于增强AECOPD的表型分型,更有助于AECOPD的个体化治疗。

2.2. C-反应蛋白

C-反应蛋白(CRP)是一种由肝脏合成的非特异性的系统性炎症标志物。当机体遭遇急性组织损伤、炎症反应或病原体(尤其是细菌)感染时,血清CRP浓度可在数小时内迅速升高,其变化幅度与炎症刺激的强度密切相关[10]。目前已有研究表明,与健康人群及稳定期COPD患者相比,AECOPD患者血清中的CRP显著升高,其水平与COPD的严重程度相关,可以用来评估COPD的潜在急性加重,是诊断AECOPD中最具选择性的生物标志物[11]。CRP水平升高与AECOPD患者的不良临床结局密切相关。其机制可能在于,高水平的CRP不仅反映了全身炎症反应的加剧,还可能直接参与气道病理生理过程,例如促进气道黏液分泌增加,加重气道阻塞,进而导致肺功能下降,加速AECOPD病情的进展[12]。以上研究表明CRP在一定程度上不仅可以反映AECOPD患者的严重程度,动态监测CRP水平可以预测患者的预后。

2.3. 降钙素原

降钙素原(PCT)水平可以反映COPD的严重程度和预测患者的预后,对AECOPD有诊断价值[13]。PCT主要由甲状腺神经内分泌细胞合成,健康人群血清中PCT的正常水平低于0.1 μg/L,感染和炎症在AECOPD的进展过程中起主要作用,当慢阻肺患者合并感染时,PCT水平会显著升高[14],PCT是在细菌诱导的细胞因子作用下释放的,其水平与感染严重程度密切相关,被认为是细菌感染的特异性指标[15],在区分细菌和非细菌AECOPD方面具有诊断价值。Gautam [16]等人还发现在呼吸道病毒感染期间PCT水平升高与疾病严重程度成正比,在此期间,PCT水平可以不受干扰素信号的抑制,因此,PCT水平在病毒性呼吸道感染期间更能反映疾病严重程度。此外,PCT水平还可以指导AECOPD患者使用抗生素的用量及疗程,有研究发现[17]入院时PCT水平低的AECOPD患者,应用抗生素 > 24小时并没有明显的临床益处,此研究成果可以避免抗生素的滥用。

3. 炎症–免疫–营养复合指标

3.1. 中性粒细胞与淋巴细胞比值

近年来,外周血中性粒细胞与淋巴细胞比值(Neutrophil to Lymphocyte Ratio, NLR)、中性粒细胞与白蛋白比值(Neutrophil-Percentage-to-Albumin Ratio, NPAR)作为综合反映机体炎症状态与营养水平的复合指标,在临床预后评估中受到广泛关注。相关研究发现,与稳定的COPD患者相比,AECOPD患者的NLR值显着增加[18]。Chou [19]等人通过一项纵向研究,对受试者的数据进行分析,并通过受试者工作特征(ROC)曲线评估了这些生物标志物对5年全因死亡率的预测效能,ROC曲线分析表明,NPAR预测5年全因死亡率的调整后曲线下面积(AUC)为0.808 (95% CI: 0.722~0.845),略优于NLR的AUC值0.799 (95% CI: 0.763~0.835),这一结果提示,NPAR和NLR均是社区COPD患者死亡风险的有效预测指标,且NPAR在预测5年全因死亡率方面表现出略优的判别能力,其综合价值可能高于其他血液炎症生物标志物。Shi [20]等人通过一项研究发现NPAR水平越高,危重症慢性阻塞性肺疾病患者的死亡风险也相应升高,二者之间存在显著的正相关关系。

3.2. 中性粒细胞与白蛋白比值

此外,一项回顾性研究表明,中性粒细胞与淋巴细胞比值在预测慢性阻塞性肺疾病急性加重期患者的院内及长期死亡率、治疗失败、器官衰竭以及首次因AECOPD再入院风险方面,具有显著临床意义,其最佳临界值确定为4.43,且被证实为目前最优的单一炎症生物标志物[21]。然而,目前关于NLR与患者临床进展之间动态关联的连续评估仍较为缺乏。尤其在患者出院后,针对皮质类固醇、抗生素及支气管扩张剂等关键药物的使用情况,相关数据记录往往不完整或不一致,这限制了NLR预测效用的进一步验证与应用。因此,为更准确评估NLR在AECOPD预后判断中的价值,未来有必要开展设计严谨的前瞻性临床研究,结合长期系统随访,并采用恰当的统计分析方法,以全面验证其预测能力及临床适用性。

3.3. 丙氨酸转氨酶

一项前瞻性研究表明,ALT水平与慢性阻塞性肺病风险呈负相关,ALT水平可能是慢性阻塞性肺病进展的潜在因素,在慢性阻塞性肺病的发展和恶化中起着重要作用[22] [23],在临床实践中,循环ALT水平通常代表特定的肝功能障碍和损伤标志物。最近有新的研究发现,目前除了气道阻塞外,肌肉和体重减轻会增加COPD患者的死亡风险[24] [25],低ALT水平与肌肉减少症、虚弱和整体健康有关[26],表明ALT水平可能反映了慢性阻塞性肺病进展的整体健康状况,可以作为潜在探索标记物,未来仍需要进一步的研究。

4. 氧化应激机制

4.1. γ-谷氨酰转移酶

γ-谷氨酰转移酶(γ-glutamyltransferase, GGT)属于循环肝功能标志物。慢性阻塞性肺疾病的发病机制涉及多方面的复杂过程,其中氧化应激机制被认为是其最重要的核心环节之一。近几年里,一直被认为是氧化应激的新标志物,血清GGT水平可用于检测肺功能下降和预测COPD患者的恶化风险[27]。Desheng [28]等人通过一项研究发现,稳定型COPD患者血清GGT升高,其水平与肺功能呈负相关,此外,他们还发现,21.2 IU/L的GGT水平显示了COPD的可靠诊断预测,并且26.5 IU/L的GGT水平可用于预测COPD患者的恶化。此研究结果证实,血清GGT水平在COPD的进展过程中,具有作为客观生物标志物的潜力,通过监测GGT活性的动态变化,临床上有望实现对COPD病情严重程度的评估,并对其急性加重风险进行早期预警。Du [29]等人发现循环GGT水平与COPD风险之间存在正相关关系。另有一项病例对照研究表明,血清GGT水平作为氧化应激标志物,慢性阻塞性肺病恶化的个体的血清GGT水平会显著升高[30],可以通过更多研究分析来验证GGT可以作为COPD患者急性加重期的血液生物标志物来评估患者预后。

4.2. 尿酸/肌酐比值

尿酸(Uric Acid, UA)是体内嘌呤代谢的最终产物,是人体内一种重要的内源性水溶性抗氧化剂,在人体内发挥着多重生理功能,主要包括保护细胞结构完整性、抵抗氧化损伤以及清除过量氧自由基等重要作用。目前已知UA与全身炎症标志物[31]、刺激内皮素-1引起的支气管收缩[32] [33]以及氧饱和度降低[34]有关。多项研究结果显示,血液中尿酸浓度的高低与肺动脉压力异常升高、睡眠呼吸暂停综合征的发生以及机体缺氧程度之间存在显著关联[35],缺氧时,尿酸水平会明显增加。在COPD发生发展过程中,当机体长期接触有害颗粒、烟草烟雾等刺激时,会导致肺部氧化应激水平升高并出现持续性慢性炎症状态,进而导致肺组织结构损伤和呼吸功能衰退。随着肺功能不断恶化,人体氧气摄入能力显著降低,导致组织供氧不足,这种缺氧现象在疾病急性加重阶段表现得尤为显著,可能是继发于组织缺氧的嘌呤分解代谢增加的结果,尤其在病情的急性加重期更为明显[36]。一项研究表明气流受限更严重的患者和频繁恶化的患者尿酸水平较高,高尿酸水平可以作为30天死亡率的独立预测因子,气流受限越严重的患者血清尿酸水平越高[37],尿酸/肌酐比值(UA/Cr)可用于评估住院COPD患者的肺功能[38]。基于上述发现,后续研究进行了更深入的探讨,研究发现,采用尿酸与肌酐的比值(UA/Cr)这一复合指标,能够有效减少肾脏代谢功能对尿酸评估带来的干扰。相较于单独检测尿酸水平,UA/Cr比值被认为可以更准确地反映机体实际缺氧状况[39],以上研究表明UA/Cr是COPD患者发生急性加重的危险因素,可以用于评估COPD患者的病情严重程度和进展。

5. 总结

慢性阻塞性肺疾病急性加重期的管理是疾病管理中的关键挑战,近年来血液生物标志物的研究取得了显著进展,多种炎症标志物如CRP、PCT、EOS不仅有助于区分急性加重的病因,还能指导治疗方案选择,并与疾病严重程度和不良结局密切相关。NLR、NPAR等复合指标综合反映了炎症与营养状态,是预测死亡风险和再入院的有效工具,ALT水平可能反映了慢性阻塞性肺病进展的整体健康状况。此外,GGT作为氧化应激的标志物,其水平升高与肺功能下降和恶化风险相关,UA/Cr则能反映组织缺氧程度,是评估病情严重程度和死亡风险的独立预测因子,未来研究应致力于多种标志物的联合应用,并开展前瞻性研究以验证其在动态监测和个体化治疗中的价值,从而优化AECOPD的临床管理策略,改善患者预后。

NOTES

*通讯作者。

参考文献

[1] Yehia, D., Leung, C. and Sin, D.D. (2024) Clinical Utilization of Airway Inflammatory Biomarkers in the Prediction and Monitoring of Clinical Outcomes in Patients with Chronic Obstructive Pulmonary Disease. Expert Review of Molecular Diagnostics, 24, 409-421. [Google Scholar] [CrossRef] [PubMed]
[2] Kim, V., Rogers, T.J. and Criner, G.J. (2008) New Concepts in the Pathobiology of Chronic Obstructive Pulmonary Disease. Proceedings of the American Thoracic Society, 5, 478-485. [Google Scholar] [CrossRef] [PubMed]
[3] Jacobsen, E.A., Helmers, R.A., Lee, J.J. and Lee, N.A. (2012) The Expanding Role(s) of Eosinophils in Health and Disease. Blood, 120, 3882-3890. [Google Scholar] [CrossRef] [PubMed]
[4] Tashkin, D.P. and Wechsler, M.E. (2018) Role of Eosinophils in Airway Inflammation of Chronic Obstructive Pulmonary Disease. International Journal of Chronic Obstructive Pulmonary Disease, 13, 335-349. [Google Scholar] [CrossRef] [PubMed]
[5] Kwok, W.C., Tam, T.C.C., Chau, C.H., Lam, F.M. and Ho, J.C.M. (2025) Differences in Blood Eosinophil Level during Stable Disease and during Exacerbation of COPD and Exacerbation Risks. Lung, 203, Article No. 37. [Google Scholar] [CrossRef] [PubMed]
[6] Bafadhel, M., McKenna, S., Terry, S., Mistry, V., Reid, C., Haldar, P., et al. (2011) Acute Exacerbations of Chronic Obstructive Pulmonary Disease: Identification of Biologic Clusters and Their Biomarkers. American Journal of Respiratory and Critical Care Medicine, 184, 662-671. [Google Scholar] [CrossRef] [PubMed]
[7] Bafadhel, M., Pavord, I.D. and Russell, R.E.K. (2017) Eosinophils in COPD: Just Another Biomarker? The Lancet Respiratory Medicine, 5, 747-759. [Google Scholar] [CrossRef] [PubMed]
[8] Feng, L., Li, J., Qian, Z., Li, C., Gao, D., Wang, Y., et al. (2024) Comprehensive Nomograms Using Routine Biomarkers Beyond Eosinophil Levels: Enhancing Predictability of Corticosteroid Treatment Outcomes in AECOPD. Journal of Inflammation Research, 17, 1511-1526. [Google Scholar] [CrossRef] [PubMed]
[9] Li, J., Liang, L., Feng, L., Cao, S., Cai, Y.S., Li, X., et al. (2023) The Prognostic Value of Blood Eosinophil Level in AECOPD Is Influenced by Corticosteroid Treatment during Hospitalization. Journal of Inflammation Research, 16, 3233-3243. [Google Scholar] [CrossRef] [PubMed]
[10] Hoult, G., Gillespie, D., Wilkinson, T.M.A., Thomas, M. and Francis, N.A. (2022) Biomarkers to Guide the Use of Antibiotics for Acute Exacerbations of COPD (AECOPD): A Systematic Review and Meta-Analysis. BMC Pulmonary Medicine, 22, Article No. 194. [Google Scholar] [CrossRef] [PubMed]
[11] Hurst, J.R., Donaldson, G.C., Perera, W.R., Wilkinson, T.M.A., Bilello, J.A., Hagan, G.W., et al. (2006) Use of Plasma Biomarkers at Exacerbation of Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine, 174, 867-874. [Google Scholar] [CrossRef] [PubMed]
[12] Munuswamy, R., De Brandt, J., Burtin, C., Derave, W., Aumann, J., Spruit, M.A., et al. (2021) Monomeric CRP Is Elevated in Patients with COPD Compared to Non-COPD Control Persons. Journal of Inflammation Research, 14, 4503-4507. [Google Scholar] [CrossRef] [PubMed]
[13] Gong, C., Yang, Y., Chen, M. and Xie, Z. (2020) Effect of Procalcitonin on the Prognosis of Patients with COPD. Biomedical Reports, 12, 313-318. [Google Scholar] [CrossRef] [PubMed]
[14] Carbonell, R., Moreno, G., Martín-Loeches, I., Bodí, M. and Rodríguez, A. (2023) The Role of Biomarkers in Influenza and COVID-19 Community-Acquired Pneumonia in Adults. Antibiotics, 12, Article 161. [Google Scholar] [CrossRef] [PubMed]
[15] Bateman, R.M., Sharpe, M.D., Jagger, J.E., et al. (2016) Crit Care. 36th International Symposium on Intensive Care and Emergency Medicine: Brussels, Belgium, 15-18 March 2016, 94.
[16] Gautam, S., Cohen, A.J., Stahl, Y., Valda Toro, P., Young, G.M., Datta, R., et al. (2020) Severe Respiratory Viral Infection Induces Procalcitonin in the Absence of Bacterial Pneumonia. Thorax, 75, 974-981. [Google Scholar] [CrossRef] [PubMed]
[17] Bremmer, D.N., Moffa, M.A., Ma, K., Bean, H.R., Snatchko, J., Trienski, T.L., et al. (2019) Acute Exacerbations of Chronic Obstructive Pulmonary Disease with a Low Procalcitonin Concentration: Impact of Antibiotic Therapy. Clinical Infectious Diseases, 68, 725-730. [Google Scholar] [CrossRef] [PubMed]
[18] Ramya, P.A., Mohapatra, M.M., Saka, V.K., et al. (2023) Haematological and Inflammatory Biomarkers among Stable COPD and Acute Exacerbations of COPD Patients. Sultan Qaboos University Medical Journal, 23, 239-244. [Google Scholar] [CrossRef] [PubMed]
[19] Lan, C.C., Su, W.L., Yang, M.C., et al. (2023) Predictive Role of Neutrophil‐Percentage‐to‐Albumin, Neutrophil‐to‐Lymphocyte and Eosinophil‐to‐Lymphocyte Ratios for Mortality in Patients with COPD: Evidence from NHANES 2011-2018. Respirology, 28, 1136-1146. [Google Scholar] [CrossRef] [PubMed]
[20] Shi, Y., Shi, Y., Liu, Y., Wang, C., Qi, M. and Li, C. (2025) Association between Neutrophil Percentage to Serum Albumin Ratio and In-Hospital Mortality of Patients with Chronic Obstructive Pulmonary Disease in Intensive Care Unit: A Retrospective Cohort Study. International Journal of Chronic Obstructive Pulmonary Disease, 20, 1227-1237. [Google Scholar] [CrossRef] [PubMed]
[21] Shao, S., Zhang, Z., Feng, L., Liang, L. and Tong, Z. (2023) Association of Blood Inflammatory Biomarkers with Clinical Outcomes in Patients with AECOPD: An 8-Year Retrospective Study in Beijing. International Journal of Chronic Obstructive Pulmonary Disease, 18, 1783-1802. [Google Scholar] [CrossRef] [PubMed]
[22] Choi, Y.J., Kwon, D.S., Kim, T., Cho, J.H., Kim, H.J., Byun, M.K., et al. (2021) Low Alanine Aminotransferase as a Risk Factor for Chronic Obstructive Pulmonary Disease in Males. Scientific Reports, 11, Article No. 14829. [Google Scholar] [CrossRef] [PubMed]
[23] Lasman, N., Shalom, M., Turpashvili, N., Goldhaber, G., Lifshitz, Y., Leibowitz, E., et al. (2020) Baseline Low ALT Activity Is Associated with Increased Long-Term Mortality after COPD Exacerbations. BMC Pulmonary Medicine, 20, Article No. 133. [Google Scholar] [CrossRef] [PubMed]
[24] Wada, H., Ikeda, A., Maruyama, K., Yamagishi, K., Barnes, P.J., Tanigawa, T., et al. (2021) Low BMI and Weight Loss Aggravate COPD Mortality in Men, Findings from a Large Prospective Cohort: The JACC Study. Scientific Reports, 11, Article No. 1531. [Google Scholar] [CrossRef] [PubMed]
[25] Kim, E.K., Singh, D., Park, J.H., Park, Y.B., Kim, S., Park, B., et al. (2020) Impact of Body Mass Index Change on the Prognosis of Chronic Obstructive Pulmonary Disease. Respiration, 99, 943-953. [Google Scholar] [CrossRef] [PubMed]
[26] Irina, G., Refaela, C., Adi, B., Avia, D., Liron, H., Chen, A., et al. (2018) Low Blood ALT Activity and High FRAIL Questionnaire Scores Correlate with Increased Mortality and with Each Other. A Prospective Study in the Internal Medicine Department. Journal of Clinical Medicine, 7, Article 386. [Google Scholar] [CrossRef] [PubMed]
[27] Kim, H.W., Lee, S.H.F., Lee, D.H., et al. (2018) Relationship of Serum Gamma-Glutamyltransferase Levels with Pulmonary Function and Chronic Obstructive Pulmonary Disease. International Journal of Chronic Obstructive Pulmonary Disease, 13, 335-349.
[28] Sun, D., Liu, H., Ouyang, Y., Liu, X. and Xu, Y. (2020) Serum Levels of Gamma-Glutamyltransferase during Stable and Acute Exacerbations of Chronic Obstructive Pulmonary Disease. Medical Science Monitor, 26, 1-7. [Google Scholar] [CrossRef] [PubMed]
[29] Du, W., Guan, H., Wan, X., Zhu, Z., Yu, H., Luo, P., et al. (2023) Circulating Liver Function Markers and the Risk of COPD in the UK Biobank. Frontiers in Endocrinology, 14, Article 1121900. [Google Scholar] [CrossRef] [PubMed]
[30] Ermis, H., Celik, M.R., Gulbas, G., Tavli, D. and Aytemur, Z.A. (2013) Relationship between Serum γ‑Glutamyltransferase Levels and Acute Exacerbation of Chronic Obstructive Pulmonary Disease. Polish Archives of Internal Medicine, 123, 85-90. [Google Scholar] [CrossRef] [PubMed]
[31] Ruggiero, C., Cherubini, A., Ble, A., Bos, A.J.G., Maggio, M., Dixit, V.D., et al. (2006) Uric Acid and Inflammatory Markers. European Heart Journal, 27, 1174-1181. [Google Scholar] [CrossRef] [PubMed]
[32] Romi, M.M., Arfian, N., Tranggono, U., Setyaningsih, W.A.W. and Sari, D.C.R. (2017) Uric Acid Causes Kidney Injury through Inducing Fibroblast Expansion, Endothelin-1 Expression, and Inflammation. BMC Nephrology, 18, Article No. 328. [Google Scholar] [CrossRef] [PubMed]
[33] Spiropoulos, K., Trakada, G., Nikolaou, E., Prodromakis, E., Efremidis, G., Pouli, A., et al. (2003) Endothelin-1 Levels in the Pathophysiology of Chronic Obstructive Pulmonary Disease and Bronchial Asthma. Respiratory Medicine, 97, 983-989. [Google Scholar] [CrossRef] [PubMed]
[34] Elsayed, N.M., Nakashima, J.M. and Postlethwait, E.M. (1993) Measurement of Uric Acid as a Marker of Oxygen Tension in the Lung. Archives of Biochemistry and Biophysics, 302, 228-232. [Google Scholar] [CrossRef] [PubMed]
[35] Kir, E., Güven Atici, A., Güllü, Y.T., Köksal, N. and Tunçez, İ.H. (2021) The Relationship between Serum Uric Acid Level and Uric Acid/Creatinine Ratio with Chronic Obstructive Pulmonary Disease Severity (Stable or Acute Exacerbation) and the Development of Cor Pulmonale. International Journal of Clinical Practice, 75, Article 14303. [Google Scholar] [CrossRef] [PubMed]
[36] Fukuhara, A., Saito, J., Sato, S., Saito, K., Fukuhara, N., Tanino, Y., et al. (2017) The Association between Risk of Airflow Limitation and Serum Uric Acid Measured at Medical Health Check-Ups. International Journal of Chronic Obstructive Pulmonary Disease, 12, 1213-1219. [Google Scholar] [CrossRef] [PubMed]
[37] Bartziokas, K., Papaioannou, A.I., Loukides, S., Papadopoulos, A., Haniotou, A., Papiris, S., et al. (2013) Serum Uric Acid as a Predictor of Mortality and Future Exacerbations of COPD. European Respiratory Journal, 43, 43-53. [Google Scholar] [CrossRef] [PubMed]
[38] Gao, H., Wang, J., Zou, X., Zhang, K., Zhou, J. and Chen, M. (2022) High Blood Urea Nitrogen to Creatinine Ratio Is Associated with Increased Risk of Sarcopenia in Patients with Chronic Obstructive Pulmonary Disease. Experimental Gerontology, 169, Article 111960. [Google Scholar] [CrossRef] [PubMed]
[39] Barmehziar, S., Fadaii, A., Samadian, F., Shakiba, A. and Koolaji, S. (2023) Investigating the Role of Uric Acid and Uric Acid-to-Creatinine Ratio as a Predictive Factor of Chronic Obstructive Pulmonary Disease Exacerbation in 2019. The Clinical Respiratory Journal, 17, 1025-1037. [Google Scholar] [CrossRef] [PubMed]