中华急诊医学杂志  2021, Vol. 30 Issue (4): 467-472   DOI: 10.3760/cma.j.issn.1671-0282.2021.04.017
单核细胞淋巴细胞比值与急性百草枯中毒患者预后的相关性
刘日升 , 曹春水     
南昌大学第一附属医院急诊科,330006
摘要: 目的 本研究旨在探讨血清中单核细胞淋巴细胞比值(monocytes to lymphocyte ratio, MLR)与急性百草枯(paraquat,PQ)中毒患者全因死亡之间的关系。方法 本研究回顾性选取2013年12月至2018年10月收治于南昌大学第一附属医院的急性PQ中毒患者,随访至2019年7月1日。主要终点事件为全因死亡。根据血MLR值将患者平均分为四组,同时根据受试者工作特性(receiver-operating characteristic,ROC)曲线分析确定的最佳MLR截止值0.61分为两组,采用Kaplan-Meier曲线进行生存分析,Cox比例风险回归模型分析相关危险因素,ROC曲线评估MLR对急性PQ中毒患者死亡风险的预测效能。结果 共纳入117例患者,其中男49例,女68例,年龄(36.91±16.00)岁,全因死亡为70(59.8%)例。K-M曲线显示Quartile 4组患者的远期预后较Quartile 1、Quartile 2和Quartile 3差(Log-rank=33.376,P < 0.01),MLR≥0.61较MLR < 0.61组患者的全因病死率明显更高(Log-rank=26.451,P < 0.01)。Cox回归模型分析结果提示MLR是急性PQ中毒患者死亡的独立危险因素(Quartile 4 vs Quartile 1: HR=2.773,95%CI: 1.250~6.154,P=0.012)。ROC曲线结果表明MLR预测全因病死率的最佳截断值为0.61,曲线下面积(area under the curve,AUC)为0.684 (95%CI: 0.591~0.767,P=0.0002),敏感性为47.14%,特异性为91.49%。结论 MLR越高急性PQ中毒患者的死亡风险越高,MLR可作为该人群全因死亡的一个有效预测指标。
关键词: 单核细胞淋巴细胞比值(MLR)    百草枯    中毒    预后    
The relationship between monocyte-to-lymphocyte ratio and prognosis in patients with acute paraquat poisoning
Liu Risheng , Cao Chunshui     
Department of Emergency Medicine, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China
Abstract: Objective To investigate the relationship between monocyte-to-lymphocyte ratio (MLR) in serum and the all-cause mortality in patients with acute paraquat (PQ) poisoning. Methods Patients with acute PQ poisoning in the First Affiliated Hospital of Nanchang University from December 2013 to October 2018 were retrospectively selected and followed up until July 1, 2019. The primary endpoint was all-cause mortality. Patients were classified into quartiles based on serum MLR and also dichotomized based on the optimal cutoff at a MLR of 0.61, determined from the receiver operating characteristic (ROC) curve analysis. The Kaplan-Meier curve was used for survival analysis. Multivariate Cox regression analysis was performed to identify risk factors, and ROC curve was applied to analyze the predictive efficacy of MLR in all-cause mortality of acute PQ patients. Results Of the 117 patients included in the study, 49 (41.88%) patients were male and 68 (58.12%) were female with a mean age of 36.91±16.00 years. The total mortality was 59.8% (70/117). On the Kaplan-Meier analysis, patients in quartile 4 had worse prognosis than patients in quartiles 1, 2 and 3 (Log-rank=33.376, P < 0.01), and patients with MLR≥0.61 had a significantly higher all-cause mortality than those with MLR < 0.61 (Log-rank=26.451, P < 0.01). Cox regression model analysis showed that MLR was an independent predictor of all-cause mortality on the quartile analysis (quartile 4 vs. quartile 1: hazard ratio 2.773, 95% confidence interval (CI): 1.250 to 6.154, P=0.012). ROC curve showed that the optimal cut-off value of MLR was calculated to be at 0.61, the area under the curve (AUC) was 0.684 (95% CI: 0.591-0.767, P=0.0002), with a sensitivity of 47.14% and a specificity of 91.49%. Conclusions High MLR was associated with mortality risk in patients with acute PQ poisoning, and MLR may be an effective predictor of all-cause mortality in this population.
Key words: Monocyte-to-lymphocyte ratio    Paraquat    Poisoning    Prognosis    

百草枯(paraquat,PQ)是一种高效接触型除草剂,由于其进入泥土后迅速失活且无残留,具有环保高效的优点,因此被全世界广泛用于农业生产。PQ对人畜具有强毒性,人类经口摄入20%PQ水溶液达15~20 mL即可致死[1],急性PQ中毒往往可损伤患者肺、肾及肝等多个器官,病死率高达60%~80%[2];肺组织为PQ中毒损伤的靶器官,早期严重的肺水肿以及后期出现的不可逆肺纤维化是PQ中毒的主要病理变化[3-6]。目前PQ中毒的治疗方法主要有洗胃催吐、利尿导泻、血液净化、抗氧化、肺移植等[7-8],然而,这些方法的有效性尚不明确,因此PQ中毒患者病死率极高。PQ中毒的致病机制主要与氧化应激和炎症损伤有关[9-11],其中炎症反应为当前研究热点,值得关注的是,近年来已有不少研究发现白细胞、中性粒细胞、中性粒细胞与淋巴细胞比值(neutrophil to lymphocyte ratio,NLR)等炎症指标与PQ中毒患者预后相关[12-15],这进一步提示PQ中毒与炎症反应有密切联系。

单核细胞与淋巴细胞比值(monocytes to lymphocyte ratio,MLR)作为一个新型的炎症指标[16],可直接从血常规中计算获得,具有成本低廉、检测方便、快速等优点,已被用于多种与炎症损伤相关疾病的评估,如肿瘤、缺血性脑卒中、冠心病等[17-19],然而目前尚无研究探讨MLR与急性PQ中毒患者全因死亡的关系。因此,本文旨在研究MLR与急性PQ中毒患者预后之间的关系,以及评估MLR对急性PQ中毒患者死亡风险的预测价值。

1 资料与方法

本次研究对象匿名,不涉及对患者的任何干预措施,患者入院均已签署知情同意书。

1.1 一般资料

回顾性选取2013年12月年至2018年10月收治于南昌大学第一附属医院的急性PQ中毒患者117例,研究对象均有明确口服中毒史、临床症状及符合PQ中毒诊断标准。随访至截止时间。主要终点事件为全因死亡。纳入标准:①中毒至入院时间≤24 h;②年龄≥14岁。排除标准:①服毒时间不详;②混合其他农药或药物中毒;③怀孕期服毒;④近期合并其他感染;⑤慢性阻塞性肺疾病(慢性支气管炎、肺气肿等);⑥血液病;⑦长期服用免疫抑制剂(糖皮质激素);⑧肿瘤;⑨合并心、脑、肾、肝等重要脏器基础疾病;⑩资料缺失或失访。具体流程见图 1

图 1 流程图 Fig 1 Flow chart of the included patients
1.2 治疗原则

所有患者均按PQ中毒原则接受治疗:①清除毒物(洗胃导泻、补液利尿、血液净化等);②抗氧化剂治疗;③免疫抑制剂治疗;④抗肺纤维化及器官支持。

1.3 资料收集

收集患者资料(包括年龄、性别、体温、心率、收缩压、呼吸频率、烟酒史、高血压、糖尿病、服毒量和急性生理和慢性健康评估Ⅱ(acute physiology and chronic health evaluation-Ⅱ,APACHE Ⅱ)评分,以及入院首次抽血化验指标:白细胞、血小板、单核细胞、淋巴细胞、血红蛋白、血白蛋白、丙氨酸转氨酶、血总胆红素、血肌酐、肌酸激酶、肺泡氧分压、血气pH及血钾值),为避免误差,以上资料由两名临床医生共同采集并进行核对,所有资料均从南昌大学第一附属医院电子病历系统获得。MLR为单核细胞与淋巴细胞计数的比值。生存时间通过病历记录及电话随访确定。

1.4 统计学方法

采用SPSS 21.0软件进行统计学分析。近似正态分布计量资料采用均数标准差(Mean±SD)描述,非正态分布的计量资料采用中位数和四分位间距描述;计数资料采用总数和百分比描述;计量资料的组间比较如符合正态分布采用ANOVA单因素分析,如不符合正态分布采用Kruskal-Wallis检验,计数资料的组间比较采用卡方检验;采用Kaplan-Meier曲线分析患者累积生存率;Cox多因素回归模型分析急性PQ中毒患者的独立危险因素,结果以风险比(hazard ratio,HR)±95%置信区间(confidence interval,CI)表示;采用受试者工作特性(receiver-operating characteristic,ROC)曲线评估MLR对PQ中毒患者全因死亡的预测价值。以P < 0.05为差异有统计学意义。

2 结果 2.1 患者一般情况

本研究共纳入117例患者,其中男49例,女68例,年龄(36.91±16.00)岁。随访至截至日期,病死率为59.8%(70/117)。表 1列出了基于MLR值平均分为四组(Quartile 1: MLR≤0.22,Quartile 2: MLR 0.22~0.37,Quartile 3: MLR 0.37~0.71,Quartile 4: MLR > 0.71)的患者人口学特征与临床数据的基线资料。由结果示,与Quartile 1相比,Quartile 4患者的白细胞、单核细胞、血MLR值、血气pH、血肌酐值较高,而淋巴细胞数则较低;各组患者年龄、性别及入院时一般情况均差异无统计学意义(P > 0.05)。

表 1 急性百草枯中毒患者入院临床资料 Table 1 The clinical data of patients with acute paraquat poisoning
指标 Total (n=117) Quartile 1 (n=29) Quartile 2 (n=30) Quartile 3 (n=29) Quartile 4 (n=29) P
年龄(岁) 36.91±16.00 36.48±14.39 39.33±14.24 30.48±14.97 41.24±18.73 0.322
性别(男/女) 49/68 12/17 11/19 13/16 13/16 0.077
体温(℃) 36.50±0.38 36.47±0.32 36.54±0.40 36.52±0.34 36.47±0.45 0.080
心率(次/min) 83.10±15.56 80.97±13.07 81.07±12.23 88.93±14.85 81.52±20.24 0.610
收缩压(mmHg) 124.10±18.61 124.66±18.12 121.27±14.61 120.90±16.55 129.66±23.68 0.845
呼吸频率(次/min) 19.96±5.38 19.59±4.02 19.07±3.89 20.90±7.71 20.31±5.17 0.350
吸烟(是/否) 15/102 5/24 6/24 2/27 2/27 0.282
高血压(是/否) 11/106 4/25 2/28 3/26 2/27 0.769
糖尿病(是/否) 1/116 1/28 0/30 0/29 0/29 0.421
服用PQ剂量(mL) 35(15, 97.5) 40(10, 60) 20(10, 50) 25(15, 60) 70(30, 100) 0.009
血气分析pH 7.41(7.39, 7.44) 7.41(7.39, 7.44) 7.44(7.41, 7.46) 7.41(7.39, 7.44) 7.39(7.32, 7.42) 0.001
APACHE-Ⅱ评分 4(2, 9.75) 5(2.75, 11.25) 3(2, 5) 3(1, 9) 9(4, 16) 0.007
血白细胞(×109/L) 13.84(9.45, 19.36) 10.01(8.28, 18.72) 10.02(7.21, 12.13) 14.84(10.47, 19.33) 19.67(15.86, 31.41) < 0.001
血红蛋白(g/L) 139.85±18.37 135.10±15.84 136.70±19.68 142.38±19.11 145.31±17.58 0.114
单核细胞(×109/L) 0.42 (0.23, 0.65) 0.15 (0.05, 0.23) 0.36 (0.24, 0.42) 0.48 (0.37, 0.63) 0.84 (0.61, 1.43) < 0.001
淋巴细胞(×109/L) 0.97 (0.71, 1.35) 1.07 (0.84, 2.30) 1.20 (0.77, 1.44) 0.93 (0.69, 1.17) 0.79 (0.60, 1.20) 0.012
血清MLR 0.37 (0.22, 0.71) 0.17 (0.04, 0.19) 0.28 (0.25, 0.33) 0.54 (0.46, 0.62) 1.02 (0.91, 1.32) < 0.001
谷丙转氨酶(U/L) 19 (16, 33.5) 17 (12, 52) 16.5 (12, 25) 19 (11, 31) 26 (19, 56) 0.078
血总胆红素(mmol/L) 13.3 (9.7, 18.75) 14.6 (9.85, 22.8) 12.75 (9.98, 16.12) 13.5 (9.55, 20.0) 13.8 (10.85, 19.4) 0.239
血白蛋白(g/L) 42.9 (39.55, 45.95) 42.5 (40.3, 44.5) 42.4 (39.25, 44.9) 43.6 (38.6, 48.2) 44.9 (41.45, 46.9) 0.226
血肌酐(mmol/L) 102.8 (61.1, 217.7) 97.7 (54.55, 250.3) 62.7 (54.18, 90.23) 118 (77.1, 223.05) 174.7 (94.85, 269.5) 0.001
肌酸激酶(U/L) 143 (90.5, 274.5) 158 (104.5, 300.5) 100 (74.75, 145.75) 146 (89, 284.5) 244 (122, 518.5) 0.001
血钾(mmol/L) 3.80±0.61 3.87±0.66 3.76±0.35 3.86±0.66 3.71±0.70 0.725
注:(1 mmHg=0.133 kPa,1 cmH2O=0.098 kPa)
2.2 ROC曲线分析

ROC曲线结果如图 2所示,确定MLR预测全因病死率的最佳截断值为0.61,曲线下面积(area under the curve,AUC)为0.684 (95%CI: 0.591~0.767,P=0.0002),敏感性为47.14%,特异性为91.49%。

MLR为单核细胞与淋巴细胞比值 图 2 MLR预测急性百枯中毒患者全因死率ROC曲线 Fig 2 The ROC curve of MLR predicting all-cause mortality in patients with acnte paraqnat poisoning
2.3 K-M曲线生存分析及Cox风险回归模型

Kaplan-Meier生存分析(图 3)显示Quartile 4的累积生存率较Quartile 1、Quartile 2和Quartile 3低(log-rank=33.376,P < 0.01)。根据MLR最佳截断值0.61将研究人群分为两组做相同分析(图 4),与MLR < 0.61的患者相比,MLR≥0.61患者的终点事件发生率明显更高(log-rank=26.451,P < 0.01)。纳入与PQ中毒患者全因死亡相关的风险因素后进行多因素Cox回归分析(表 2),结果表明,当校正年龄、性别、糖尿病、高血压、吸烟、呼吸频率、血红蛋白、血白蛋白及血肌酐值后,Quartile 4比Quartile 1的死亡风险更高(HR=2.773,95%CI: 1.250~6.154, P=0.012)。

图 3 4组百草枯中毒患者Kaplan-Meier生存曲线 Fig 3 The Kaplan-Meier curve of patients with paraquat poisoning in Quartiles 1, 2, 3 and 4

图 4 2组百草枯中毒患者Kaplan-Meier生存曲线 Fig 4 The Kaplan-Meier curve of patients with paraquat poisoning with MLR ≤0.61 and > 0.61

表 2 MLR预测急性百草枯中毒患者全因死亡的多因素Cox分析模型 Table 2 Multivariate Cox analysis model of MLR for predicting all-cause mortality in patients with acute paraquat poisoning
MLR Quartile 1 (≤0.22) Quartile 2 (0.22~0.37) Quartile 3 (0.37~0.71) Quartile 4 (>0.71)
未校正模型
 HR (95%CI) 参考 0.664 (0.311~1.419) 1.055 (0.522~2.135) 3.095(1.625~5.892)
 P - 0.291 0.881 0.001
校正模型
 模型A
  HR (95%CI) 参考 0.626(0.292~1.345) 1.174(0.572~2.413) 3.037(1.587~5.811)
  P - 0.230 0.662 0.001
 模型B
  HR (95%CI) 参考 0.683(0.312~1.496) 1.223(0.582~2.571) 3.292(1.665~6.510)
  P - 0.341 0.596 0.001
 模型C
  HR (95%CI) 参考 0.707(0.310~1.162) 0.893(0.409~1.953) 2.773(1.250~6.154)
  P - 0.410 0.778 0.012
模型A:校正年龄、性别;模型B:校正模型A及糖尿病、高血压、吸烟;模型C:校正模型B及呼吸频率、血红蛋白、血白蛋白、血肌酐值
3 讨论

本研究探讨了入院时血MLR水平与急性PQ中毒患者病死率之间的关系,在本研究中,发现高MLR组患者的累计生存率明显低于其他较低MLR组,同时,基于最佳截断MLR值0.61分组的分析也发现了相同的趋势。此外,还发现在调整了相关危险因素后,MLR是急性PQ中毒患者全因病死率的一个重要的、独立的预测因子。

农药中毒是我国的一个重要公共健康问题,其中,急性PQ中毒由于进展快、预后差、无特效治疗措施,近年来引起了人们广泛关注[20],据报道,2002-2011年间我国PQ中毒发生率持续上升[21],尽管2012年起国内外已禁止生产和销售PQ,PQ中毒事件增长速度有所减缓,但我国为农业大国,PQ存贮量巨大,近年PQ中毒发病率仍呈现上升趋势。因此寻找一个可靠的可用于预测PQ中毒患者死亡风险的指标至关重要。

血浆PQ浓度是被认为是预测PQ中毒病死率准确、可靠的指标[22-24],然而,该指标检测费用昂贵且许多医院尚不具备相关检测设备,因此,该指标的临床适用性不高。与血浆PQ浓度相比,MLR是一个计算简便、廉价的指标。近年来,MLR已被认为是内皮功能障碍和炎症的代用指标,具有一定的预后和预测价值[16];MLR作为一种新型的炎症预测因子,许多研究证明MLR与多种疾病的死亡预后相关[25-28],Yuan等[29]研究表明MLR越高,非小细胞肺癌患者的死亡风险越高,而Choi, 等[30]在研究中也发现MLR值可独立预测胆囊癌化疗患者的生存率。

单核细胞是白细胞的一种亚型,具有分化成巨噬细胞及树突状细胞的潜力,当前许多研究认为,单核细胞计数升高与各种疾病的不良预后有密切关系[31-33]。作为机体免疫的重要成员,单核细胞在PQ中毒机制中的作用逐渐引起人们关注,有研究表明,PQ可诱导骨髓间充质干细胞快速表达单核细胞趋化蛋白-1,使血液中单核细胞迅速增多[34-35];活化的单核细胞聚集在肺内,促进趋化因子和促炎因子(如TNF-α和IL-8)的产生,激活炎症反应,其次,来源于单核细胞的肺泡巨噬细胞可启动免疫反应并产生活性氧,导致细胞NADPH耗竭和细胞膜脂质过氧化,同时,肺泡巨噬细胞产生的转化生长因子,可促进成纤维细胞中促纤维化基因的表达,导致组织纤维化。淋巴细胞是机体主要的免疫细胞,参与炎症反应的调控,淋巴细胞减少常见于心肌缺血、生理应激、皮质醇和儿茶酚胺水平升高,以及严重炎症反应导致淋巴细胞凋亡的患者。PQ中毒引起淋巴细胞绝对值下降的具体机制尚未明确,可能与PQ引起氧化应激使体内氧自由基(ROS)及皮质醇激素产生增多,进而诱导淋巴细胞凋亡有关。

目前已有研究表明,高单核细胞和低淋巴细胞均可作为预测PQ中毒预后的独立风险指标,然而,相比于单核细胞或淋巴细胞绝对值,MLR可能是更好的预测指标,理由如下:首先,MLR相对于单个单核细胞或淋巴细胞计数更稳定,更不容易被不同的生理病理条件改变;其次,使用比值方式可消除系统误差,减少误差干扰,提高统计效能;最后,MLR结合了单核细胞与淋巴细胞两个指标的意义,增强指标的说服力与可靠性;因此采用MLR作为预测急性PQ中毒预后的指标会更加理想。

利益冲突  所有作者均声明不存在利益冲突。

参考文献
[1] Wunnapuk K, Mohammed F, Gawarammana I, et al. Prediction of paraquat exposure and toxicity in clinically ill poisoned patients: a model based approach[J]. Br J Clin Pharmacol, 2014, 78(4): 855-866. DOI:10.1111/bcp.12389
[2] Weng CH, Hu CC, Lin JL, et al. Predictors of acute respiratory distress syndrome in patients with paraquat intoxication[J]. PLoS One, 2013, 8(12): e82695. DOI:10.1371/journal.pone.0082695
[3] Schapochnik A, da Silva MR, Leal MP, et al. Vitamin D treatment abrogates the inflammatory response in paraquat-induced lung fibrosis[J]. Toxicol Appl Pharmacol, 2018, 355: 60-67. DOI:10.1016/j.taap.2018.06.020
[4] Harchegani AL, Hemmati AA, Nili-Ahmadabadi A, et al. Cromolyn sodium attenuates paraquat-induced lung injury by modulation of proinflammatory cytokines[J]. Drug Res (Stuttg), 2017, 67(5): 283-288. DOI:10.1055/s-0042-123711
[5] Sun B, Chen YG. Advances in the mechanism of paraquat-induced pulmonary injury[J]. Eur Rev Med Pharmacol Sci, 2016, 20(8): 1597-1602.
[6] 符红娜, 聂时南. 百草枯致肺纤维化的上皮-间质转化的机制研究进展[J]. 中华急诊医学杂志, 2019, 28: 803-805. DOI:10.3760/cma.j.issn.1671-0282.2019.06.033
[7] Sun BS, He YZ. Paraquat poisoning mechanism and its clinical treatment progress[J]. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue, 2017, 29(11): 1043-1046. DOI:10.3760/cma.j.issn.2095-4352.2017.11.018
[8] Wu WP, Lai MN, Lin CH, et al. Addition of immunosuppressive treatment to hemoperfusion is associated with improved survival after paraquat poisoning: a nationwide study[J]. PLoS One, 2014, 9(1): e87568. DOI:10.1371/journal.pone.0087568
[9] Ahmed MAE, El Morsy EM, Ahmed AAE. Protective effects of febuxostat against paraquat-induced lung toxicity in rats: Impact on RAGE/PI3K/Akt pathway and downstream inflammatory cascades[J]. Life Sci, 2019, 221: 56-64. DOI:10.1016/j.lfs.2019.02.007
[10] Yang W, Liu W, Yu W, et al. Angptl2 deficiency attenuates paraquat (PQ)-induced lung injury in mice by altering inflammation, oxidative stress and fibrosis through NF-κB pathway[J]. Biochem Biophys Res Commun, 2018, 503(1): 94-101. DOI:10.1016/j.bbrc.2018.05.186
[11] Liu MW, Su MX, Zhang W, et al. Protective effect of Xuebijing injection on paraquat-induced pulmonary injury via down-regulating the expression of p38 MAPK in rats[J]. BMC Complement Altern Med, 2014, 14: 498. DOI:10.1186/1472-6882-14-498
[12] Chen HL, Hu LF, Li HZ, et al. An effective machine learning approach for prognosis of paraquat poisoning patients using blood routine indexes[J]. Basic Clin Pharmacol Toxicol, 2017, 120(1): 86-96. DOI:10.1111/bcpt.12638
[13] Feng SY, Gao J, Li Y. A retrospective analysis of leucocyte count as a strong predictor of survival for patients with acute paraquat poisoning[J]. PLoS One, 2018, 13(7): e0201200. DOI:10.1371/journal.pone.0201200
[14] Liang H, Gao Y, Liu Y, et al. Predictive value of neutrophil-to-lymphocyte ratio in 30-day mortality of patients with acute paraquat poisoning[J]. Chin J Ind Hyg Occup Dis, 2018, 36(12): 911-914. DOI:10.3760/cma.j.issn.1001-9391.2018.12.007
[15] Zhou DC, Zhang H, Luo ZM, et al. Prognostic value of hematological parameters in patients with paraquat poisoning[J]. Sci Rep, 2016, 6: 36235. DOI:10.1038/srep36235
[16] Balta S, Demırer Z, Aparci M, et al. The lymphocyte-monocyte ratio in clinical practice[J]. J Clin Pathol, 2016, 69(1): 88-89. DOI:10.1136/jclinpath-2015-203233
[17] Stotz M, Szkandera J, Stojakovic T, et al. The lymphocyte to monocyte ratio in peripheral blood represents a novel prognostic marker in patients with pancreatic cancer[J]. Clin Chem Lab Med, 2015, 53(3): 499-506. DOI:10.1515/cclm-2014-0447
[18] Ren H, Liu X, Wang L, et al. Lymphocyte-to-monocyte ratio: a novel predictor of the prognosis of acute ischemic stroke[J]. J Stroke Cerebrovasc Dis, 2017, 26(11): 2595-2602. DOI:10.1016/j.jstrokecerebrovasdis.2017.06.019
[19] Murat SN, Yarlioglues M, Celik IE, et al. The relationship between lymphocyte-to-monocyte ratio and bare-metal stent in-stent restenosis in patients with stable coronary artery disease[J]. Clin Appl Thromb Hemost, 2017, 23(3): 235-240. DOI:10.1177/1076029615627340
[20] 卢中秋. 精益求精, 进一步提高我国急诊中毒临床诊治水平[J]. 中华急诊医学杂志, 2019, 28: 275-278. DOI:10.3760/cma.j.issn.1671-0282.2019.03.001
[21] Yin Y, Guo X, Zhang SL, et al. Analysis of paraquat intoxication epidemic (2002-2011) within China[J]. Biomed Environ Sci, 2013, 26(6): 509-512. DOI:10.3967/0895-3988.2013.06.014
[22] Senarathna L, Eddleston M, Wilks MF, et al. Prediction of outcome after paraquat poisoning by measurement of the plasma paraquat concentration[J]. QJM, 2009, 102(4): 251-259. DOI:10.1093/qjmed/hcp006
[23] Hong SY, Lee JS, Sun IO, et al. Prediction of patient survival in cases of acute paraquat poisoning[J]. PLoS One, 2014, 9(11): e111674. DOI:10.1371/journal.pone.0111674
[24] Du Y, Mou Y. Predictive value of 3 methods in severity evaluation and prognosis of acute paraquat poisoning[J]. J Central South Univ Med Sci, 2013, 38(7): 737-742. DOI:10.3969/j.issn.1672-7347.2013.07.014
[25] Wang L, Long W, Li PF, et al. An elevated peripheral blood monocyte-to-lymphocyte ratio predicts poor prognosis in patients with primary pulmonary lymphoepithelioma-like carcinoma[J]. PLoS One, 2015, 10(5): e0126269. DOI:10.1371/journal.pone.0126269
[26] Shi LH, Qin XQ, Wang HJ, et al. Elevated neutrophil-to-lymphocyte ratio and monocyte-to-lymphocyte ratio and decreased platelet-to-lymphocyte ratio are associated with poor prognosis in multiple myeloma[J]. Oncotarget, 2017, 8(12): 18792-18801. DOI:10.18632/oncotarget.13320
[27] Xiang FF, Chen RY, Cao XS, et al. Monocyte/lymphocyte ratio as a better predictor of cardiovascular and all-cause mortality in hemodialysis patients: a prospective cohort study[J]. Hemodial Int, 2018, 22(1): 82-92. DOI:10.1111/hdi.12549
[28] Fan ZY, Li Y, Ji HH, et al. Prognostic utility of the combination of monocyte-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio in patients with NSTEMI after primary percutaneous coronary intervention: a retrospective cohort study[J]. BMJ Open, 2018, 8(10): e023459. DOI:10.1136/bmjopen-2018-023459
[29] Yuan C, Li N, Mao XY, et al. Elevated pretreatment neutrophil/white blood cell ratio and monocyte/lymphocyte ratio predict poor survival in patients with curatively resected non-small cell lung cancer: Results from a large cohort[J]. Thorac Cancer, 2017, 8(4): 350-358. DOI:10.1111/1759-7714.12454
[30] Choi YH, Lee JW, Lee SH, et al. A high monocyte-to-lymphocyte ratio predicts poor prognosis in patients with advanced gallbladder cancer receiving chemotherapy[J]. Cancer Epidemiol Biomarkers Prev, 2019, 28(6): 1045-1051. DOI:10.1158/1055-9965.EPI-18-1066
[31] Balın Ö, Tartar AS, Akbulut A. The predictive role of haematological parameters in the diagnosis of osteoarticular brucellosis[J]. Afr Health Sci, 2018, 18(4): 988-994. DOI:10.4314/ahs.v18i4.19
[32] Feng F, Zheng GZ, Wang Q, et al. Low lymphocyte count and high monocyte count predicts poor prognosis of gastric cancer[J]. BMC Gastroenterol, 2018, 18(1): 148. DOI:10.1186/s12876-018-0877-9
[33] Moon JM, Chun BJ, Cho YS, et al. Diagnostic value of parameters related to white blood cell counts for troponin I elevation in CO poisoning[J]. Cardiovasc Toxicol, 2019, 19(4): 334-343. DOI:10.1007/s12012-018-09501-w
[34] Shi C, Jia T, Mendez-Ferrer S, et al. Bone marrow mesenchymal stem and progenitor cells induce monocyte emigration in response to circulating toll-like receptor ligands[J]. Immunity, 2011, 34(4): 590-601. DOI:10.1016/j.immuni.2011.02.016
[35] Amirshahrokhi K, Khalili AR. Carvedilol attenuates paraquat-induced lung injury by inhibition of proinflammatory cytokines, chemokine MCP-1, NF-κB activation and oxidative stress mediators[J]. Cytokine, 2016, 88: 144-153. DOI:10.1016/j.cyto.2016.09.004