中文English
ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

乳酸水平对HBV相关慢加急性肝衰竭患者短期预后的预测价值

杨烁 刘坤 杨兰 徐玲 鲁晓擘 孙晓风 玛力帕提·艾尔肯江

引用本文:
Citation:

乳酸水平对HBV相关慢加急性肝衰竭患者短期预后的预测价值

DOI: 10.3969/j.issn.1001-5256.2022.07.007
基金项目: 

国家自然科学基金 (82060115)

伦理学声明:本研究于2021年10月27日经由新疆医科大学第一附属医院伦理委员会审批,批号:K202110-06。
利益冲突声明:本研究不存在研究者、伦理委员会成员、受试者监护人以及与公开研究成果有关的利益冲突。
作者贡献声明:孙晓风、鲁晓擘负责课题设计;杨烁、刘坤、杨兰、徐玲负责资料分析与撰写论文;杨烁、刘坤、杨兰、徐玲、孙晓风、玛力帕提·艾尔肯江参与收集数据与修改论文;孙晓风、鲁晓擘负责拟定写作思路,指导撰写文章并最后定稿。
详细信息
    通信作者:

    孙晓风,xjwlsxf@163.com

Value of lactate level in predicting the short-term prognosis of patients with acute-on-chronic hepatitis B liver failure

Research funding: 

National Natural Science Foundation of China (82060115)

More Information
    Corresponding author: SUN Xiaofeng, xjwlsxf@163.com(ORCID: 0000-0002-2596-3669)
  • 摘要:   目的  本研究旨在评估乳酸对HBV相关慢加急性肝衰竭(HBV-ALCF)患者90 d预后的预测价值。  方法  回顾性纳入2017年1月—2021年6月新疆医科大学第一附属医院感染病·肝病中心收治的117例HBV-ACLF患者,根据90 d随访结果分为生存组(n=43)和死亡组(n=74);收集患者于本院诊断HBV-ACLF后24 h内的血常规、肝肾功能、凝血功能、动脉血气、肝性脑病等并发症,计算ALBI、MELD、MELD-Na、MESO、iMELD、CLIF-C ACLF评分。计量资料符合正态分布的组间比较采用t检验,非正态分布的组间比较采用Mann-Whitney U检验,计数资料组间比较采用χ2检验。采用二元logistic分析乳酸是否为HBV-ACLF患者90 d预后的独立危险因素,Pearson相关分析检验乳酸与感染情况及临床并发症的相关性。绘制受试者工作特征曲线(ROC曲线)分析乳酸相加于各评分后能否提高现有模型的预测价值,两两比较采用Z检验。  结果  死亡组WBC、INR、乳酸均大于生存组,Na小于生存组,差异均有统计学意义(Z值分别为-2.813、-2.855、-3.186、-2.044,P值均<0.05);年龄、MELD、MELD-Na、MESO、iMELD、CLIF-C ACLF评分均显著高于生存组,差异均有统计学意义(t值分别为2.536、4.615、4.247、4.941、5.832、7.562,P值均<0.05)。logistic分析表明年龄(OR=1.075,95%CI: 1.026~1.127,P=0.002)、INR(OR=2.198,95%CI: 1.149~4.203,P=0.017)、乳酸(OR=1.431,95%CI: 1.002~2.044,P=0.049)是HBV-ACLF患者90 d预后的独立危险因素,将乳酸纳入现有模型后ROC曲线下面积均有所增加。  结论  乳酸是HBV-ACLF患者90 d预后的独立危险因素,将其纳入现有模型可能提高预测价值。

     

  • 图  1  六种评分增加乳酸前后ROC曲线的比较

    Figure  1.  Comparison of ROC curves before and after increasing lactate for six scores

    表  1  CLIF-C OF评分

    Table  1.   CLIF-C OF scores

    器官/系统 1分 2分 3分
    肝脏(TBil, mg/dL) <6 6~12 >12
    肾脏(Cr, mg/dL) <2 2~3.4 ≥3.5或肾脏替代治疗
    凝血功能(INR) <2 2~2.4 ≥2.5
    神经(感性脑病分级) 0 Ⅰ~Ⅱ Ⅲ~Ⅳ
    循环(平均动脉压,mmHg) ≥70 <70 应用血管活性药物
    (去甲肾上腺素、多巴胺、肾上腺素)
    呼吸
      PaO2/FiO2 >300 201~300 ≤200
      SPO2/FiO2 >357 215~357 ≤214
    注:Cr,肌酐;PaO2/FiO2,氧分压/氧浓度;SpO2/FiO2,血氧饱和度/氧浓度。
    下载: 导出CSV

    表  2  入组时基线资料的比较分析

    Table  2.   Comparative analysis of baseline information at enrollment

    指标 生存组(n=43) 死亡组(n=74) 统计值 P
    年龄(岁) 44.05±10.32 49.70±12.33 t=2.536 0.013
    男/女(例) 31/12 55/19 χ2=0.070 0.792
    WBC(×109/L) 6.25(5.10~8.20) 7.83(5.90~11.57) Z=-2.813 0.005
    红细胞分布宽度(%) 16.20(14.60~17.80) 17.45(15.28~18.60) Z=-1.804 0.071
    Na(mmol/L) 135.00(132.42~136.87) 132.96(128.42~136.0) Z=-2.044 0.041
    血小板压积(%) 0.56(0.31~0.90) 0.59(0.40~1.02) Z=-0.933 0.351
    PLT(×109/L) 122(90~142) 91(60~133.5) Z=-1.883 0.060
    Alb(g/L) 29.29(24.81~32.57) 28.22(25.54~31.42) Z=-0.334 0.739
    INR 2.52(1.96~3.03) 2.85(2.43~3.59) Z=-2.855 0.004
    Cr(mg/dL) 0.72(0.62~0.88) 0.84(0.62~1.16) Z=-1.916 0.055
    TBil(mg/dL) 17.08(13.46~20.58) 19.67(14.12~26.51) Z=-1.713 0.087
    AST(U/L) 222.72(111.14~563.52) 215.95(105.59~529.12) Z=-0.636 0.525
    ALT(U/L) 362.10(161.57~682.10) 197.87(64.42~648.65) Z=-1.269 0.204
    乳酸(mmol/L) 2.30(1.80~2.70) 2.60(2.00~3.82) Z=-3.186 0.001
    ALBI评分 -1.30(-1.59~-0.94) -1.16(-1.48~-0.92) Z=-1.198 0.231
    MELD评分 24.29±4.27 28.99±6.74 t=4.615 <0.001
    MELD-Na评分 25.66±8.33 34.28±13.63 t=4.247 <0.001
    MESO评分 1.81±0.34 2.21±0.53 t=4.941 <0.001
    iMELD评分 43.61±5.69 51.73±9.37 t=5.832 <0.001
    CLIF-C ACLF评分 45.48±6.71 56.70±9.22 t=7.562 <0.001
    糖尿病[例(%)] 3(6.98) 14(18.92) χ2=3.123 0.077
    肝硬化[例(%)] 25(58.14) 52(70.27) χ2=1.779 0.182
    人工肝支持[例(%)] 26(60.47) 42(56.76) χ2=0.154 0.695
    下载: 导出CSV

    表  3  两组并发症发生情况比较

    Table  3.   Comparison of the occurrence of complications between the two groups

    指标 例数 生存组(n=43) 死亡组(n=74) χ2 P
    上消化道出血[例(%)] 15 1(2.33) 14(18.92) 6.700 0.010
    肺部感染或感染性休克[例(%)] 41 8(18.60) 33(44.59) 8.070 0.004
    肝肾综合征[例(%)] 13 0 13(17.57) 6.813 0.009
    腹水[例(%)] 98 34(79.07) 64(86.49) 1.100 0.294
    肝性脑病[例(%)] 51 6(13.95) 45(60.81) 24.284 <0.001
    下载: 导出CSV

    表  4  HBV-ACLF患者预后影响因素的多因素logistic分析

    Table  4.   Multi-factor logistic analysis of the prognostic factors of HBV-ACLF

    指标 B SE Wald P OR 95%CI
    年龄 0.073 0.024 9.174 0.002 1.075 1.026~1.127
    INR 0.787 0.331 5.667 0.017 2.198 1.149~4.203
    乳酸 0.359 0.182 3.888 0.049 1.431 1.002~2.044
    下载: 导出CSV

    表  5  各模型预测90 d病死率的的准确性

    Table  5.   Accuracy of each model in predicting 90-d mortality rate

    评分模型 AUC 95%CI P cut-off值 灵敏度 特异度
    ALBI 0.567 0.458~0.675 0.231 -1.233 9 0.595 0.558
    乳酸 0.677 0.579~0.775 0.001 3.150 0 0.405 0.930
    MELD 0.698 0.604~0.791 <0.001 29.574 6 0.432 0.953
    MELD-Na 0.698 0.603~0.793 <0.001 31.935 7 0.527 0.837
    MESO 0.709 0.617~0.802 <0.001 2.286 9 0.446 0.977
    iMELD 0.766 0.682~0.851 <0.001 50.144 4 0.527 0.907
    CLIF-C ACLF 0.832 0.761~0.904 <0.001 51.472 6 0.689 0.860
    下载: 导出CSV

    表  6  相加乳酸后六种新模型的预测价值

    Table  6.   Predictive values of the six new models after summing lactate

    评分模型 AUC 95%CI P 灵敏度 特异度
    ALBI+乳酸 0.690 0.593~0.787 0.001 0.541 0.767
    MELD+乳酸 0.709 0.617~0.801 <0.001 0.446 0.977
    MELD-Na+乳酸 0.717 0.625~0.809 <0.001 0.622 0.767
    MESO+乳酸 0.719 0.625~0.813 <0.001 0.446 0.907
    iMELD+乳酸 0.775 0.692~0.858 <0.001 0.514 0.907
    CLIF-C ACLF+乳酸 0.839 0.769~0.909 <0.001 0.622 0.953
    下载: 导出CSV
  • [1] BERNAL W, JALAN R, QUAGLIA A, et al. Acute-on-chronic liver failure[J]. Lancet, 2015, 386(10003): 1576-1587. DOI: 10.1016/S0140-6736(15)00309-8.
    [2] LIAW YF. Antiviral therapy of chronic hepatitis B: opportunities and challenges in Asia[J]. J Hepatol, 2009, 51(2): 403-410. DOI: 10.1016/j.jhep.2009.04.003.
    [3] SHEN Y, WANG X, ZHANG S, et al. A comprehensive validation of HBV-related acute-on-chronic liver failure models to assist decision-making in targeted therapeutics[J]. Sci Rep, 2016, 6: 33389. DOI: 10.1038/srep33389.
    [4] CHEN W, YOU J, CHEN J, et al. Combining the serum lactic acid level and the lactate clearance rate into the CLIF-SOFA score for evaluating the short-term prognosis of HBV-related ACLF patients[J]. Expert Rev Gastroenterol Hepatol, 2020, 14(6): 483-489. DOI: 10.1080/17474124.2020.1763172.
    [5] CHEN W, YOU J, CHEN J, et al. Modified model for end-stage liver disease improves short-term prognosis of hepatitis B virus-related acute-on-chronic liver failure[J]. World J Gastroenterol, 2017, 23(40): 7303-7309. DOI: 10.3748/wjg.v23.i40.7303.
    [6] van HALL G. Lactate kinetics in human tissues at rest and during exercise[J]. Acta Physiol(Oxf), 2010, 199(4): 499-508. DOI: 10.1111/j.1748-1716.2010.02122.x.
    [7] NIE Y, ZHANG Y, LIU LX, et al. Serum lactate level predicts short-term and long-term mortality of HBV-ACLF patients: a prospective study[J]. Ther Clin Risk Manag, 2020, 16: 849-860. DOI: 10.2147/TCRM.S272463.
    [8] Liver Failure and Artificial Liver Group, Chinese Society of Infectious Diseases, Chinese Medical Association; Severe Liver Disease and Artificial Liver Group, Chinese Society of Hepatology, Chinese Medical Association. Guideline for diagnosis and treatment of liver failure(2018)[J]. J Clin Hepatol, 2019, 35(1): 38-44. DOI: 10.3969/j.issn.1001-5256.2019.01.007.

    中华医学会感染病学分会肝衰竭与人工肝学组, 中华医学会肝病学分会重型肝病与人工肝学组. 肝衰竭诊治指南(2018年版)[J]. 临床肝胆病杂志, 2019, 35(1): 38-44. DOI: 10.3969/j.issn.1001-5256.2019.01.007.
    [9] JOHNSON PJ, BERHANE S, KAGEBAYASHI C, et al. Assessment of liver function in patients with hepatocellular carcinoma: a new evidence-based approach-the ALBI grade[J]. J Clin Oncol, 2015, 33(6): 550-558. DOI: 10.1200/JCO.2014.57.9151.
    [10] KAMATH PS, WIESNER RH, MALINCHOC M, et al. A model to predict survival in patients with end-stage liver disease[J]. Hepatology, 2001, 33(2): 464-470. DOI: 10.1053/jhep.2001.22172.
    [11] BIGGINS SW, KIM WR, TERRAULT NA, et al. Evidence-based incorporation of serum sodium concentration into MELD[J]. Gastroenterology, 2006, 130(6): 1652-1660. DOI: 10.1053/j.gastro.2006.02.010.
    [12] HUO TI, WANG YW, YANG YY, et al. Model for end-stage liver disease score to serum sodium ratio index as a prognostic predictor and its correlation with portal pressure in patients with liver cirrhosis[J]. Liver Int, 2007, 27(4): 498-506. DOI: 10.1111/j.1478-3231.2007.01445.x.
    [13] LUCA A, ANGERMAYR B, BERTOLINI G, et al. An integrated MELD model including serum sodium and age improves the prediction of early mortality in patients with cirrhosis[J]. Liver Transpl, 2007, 13(8): 1174-1180. DOI: 10.1002/lt.21197.
    [14] HERNAEZ R, SOLÀ E, MOREAU R, et al. Acute-on-chronic liver failure: an update[J]. Gut, 2017, 66(3): 541-553. DOI: 10.1136/gutjnl-2016-312670.
    [15] REN Y, LIU L, LI Y, et al. Development and validation of a scoring system to predict progression to acute-on-chronic liver failure in patients with acute exacerbation of chronic hepatitis B[J]. Hepatol Res, 2018, 48(9): 692-700. DOI: 10.1111/hepr.13062.
    [16] ZHANG WJ, ZHANG LJ, WU JZ. Value of MELD、AARC、COSSH ccoring systems in evaluating the 90 -day prognosis of hepatitis B virus-related acute-on-chronic liver failure[J]. J Clin Hepatol, 2020, 36(4): 813-817. DOI: 10.3969/j.issn.1001-5256.2020.04.021.

    张文佳, 赵丽娟, 吴基洲. MELD、AARC、COSSH评分系统对乙型肝炎相关慢加急性肝衰竭90天预后的评估价值[J]. 临床肝胆病杂志, 2020, 36(4): 813-817. DOI: 10.3969/j.issn.1001-5256.2020.04.021.
    [17] DU Q, LU SJ, LU DX, et al. Clinical characteristics and prognosis of patients with decompensated liver cirrhosis complicated with chronic and acute liver failure[J]. Chin J Gerontol, 2021, 41(3): 520-523. DOI: 10.3969/j.issn.1005-9202.2021.03.021.

    杜蔷, 陆盛菊, 卢大秀, 等. HBV感染失代偿期肝硬化并发慢加急性肝衰竭患者的临床特点及预后[J]. 中国老年学杂志, 2021, 41(3): 520-523. DOI: 10.3969/j.issn.1005-9202.2021.03.021.
    [18] SHANG DB, XIANG XG. Advances in the pathogenesis and treatment of acute-on-chronic liver failure[J]. J Clin Hepatol, 2021, 37(4): 765-769. DOI: 10.3969/j.issn.1001-5256.2021.04.005.

    尚大宝, 项晓刚. 慢加急性肝衰竭的发病机制和治疗进展[J]. 临床肝胆病杂志, 2021, 37(4): 765-769. DOI: 10.3969/j.issn.1001-5256.2021.04.005.
    [19] KRAUT JA, MADIAS NE. Lactic acidosis[J]. N Engl J Med, 2014, 371(24): 2309-2319. DOI: 10.1056/NEJMra1309483.
    [20] HILL AV. Muscular activity and carbohydrate metabolism[J]. Science, 1924, 60(1562): 505-514. DOI: 10.1126/science.60.1562.505.
    [21] BROOKS GA. The science and translation of lactate shuttle theory[J]. Cell Metab, 2018, 27(4): 757-785. DOI: 10.1016/j.cmet.2018.03.008.
    [22] CARDOSO FS, ABRALDES JG, SY E, et al. Lactate and number of organ failures predict intensive care unit mortality in patients with acute-on-chronic liver failure[J]. Liver Int, 2019, 39(7): 1271-1280. DOI: 10.1111/liv.14083.
    [23] KRUSE JA, ZAIDI SA, CARLSON RW. Significance of blood lactate levels in critically ill patients with liver disease[J]. Am J Med, 1987, 83(1): 77-82. DOI: 10.1016/0002-9343(87)90500-6.
    [24] JEPPESEN JB, MORTENSEN C, BENDTSEN F, et al. Lactate metabolism in chronic liver disease[J]. Scand J Clin Lab Invest, 2013, 73(4): 293-299. DOI: 10.3109/00365513.2013.773591.
    [25] DROLZ A, HORVATITS T, RUTTER K, et al. Lactate improves prediction of short-term mortality in critically ill patients with cirrhosis: a multinational study[J]. Hepatology, 2019, 69(1): 258-269. DOI: 10.1002/hep.30151.
    [26] CHAMULEAU RA. Bioartificial liver support anno 2001[J]. Metab Brain Dis, 2002, 17(4): 485-491. DOI: 10.1023/a:1021990725508.
    [27] TRIANTAFYLLOU E, WOOLLARD KJ, MCPHAIL M, et al. The role of monocytes and macrophages in acute and acute-on-chronic liver failure[J]. Front Immunol, 2018, 9: 2948. DOI: 10.3389/fimmu.2018.02948.
    [28] ZHANG DJ, ZHOU B, HOU JL. Research progress in prognostic models of acute-on-chronic liver failure[J]. J Clini Hepatol, 2018, 34(6): 1351-1356. DOI: 10.3969/j.issn.1001-5256.2018.06.047.

    张东敬, 周彬, 侯金林. 慢加急性肝衰竭预后模型的研究进展[J]. 临床肝胆病杂志, 2018, 34(6): 1351-1356. DOI: 10.3969/j.issn.1001-5256.2018.06.047.
    [29] LI H, ZHENG J, CHEN L, et al. The scoring systems in predicting short-term outcomes in patients with hepatitis B virus-related acute-on-chronic liver failure[J]. Ann Palliat Med, 2020, 9(5): 3048-3058. DOI: 10.21037/apm-20-608.
    [30] WILLIAMS MA, BEVAN MJ. Effector and memory CTL differentiation[J]. Annu Rev Immunol, 2007, 25: 171-192. DOI: 10.1146/annurev.immunol.25.022106.141548.
    [31] WHERRY EJ, AHMED R. Memory CD8 T-cell differentiation during viral infection[J]. J Virol, 2004, 78(11): 5535-5545. DOI: 10.1128/JVI.78.11.5535-5545.2004.
    [32] MICHALEK RD, RATHMELL JC. The metabolic life and times of a T-cell[J]. Immunol Rev, 2010, 236: 190-202. DOI: 10.1111/j.1600-065X.2010.00911.x.
    [33] JACOBS SR, HERMAN CE, MACIVER NJ, et al. Glucose uptake is limiting in T cell activation and requires CD28-mediated Akt-dependent and independent pathways[J]. J Immunol, 2008, 180(7): 4476-4486. DOI: 10.4049/jimmunol.180.7.4476.
    [34] RATHMELL JC, ELSTROM RL, CINALLI RM, et al. Activated Akt promotes increased resting T cell size, CD28-independent T cell growth, and development of autoimmunity and lymphoma[J]. Eur J Immunol, 2003, 33(8): 2223-2232. DOI: 10.1002/eji.200324048.
    [35] VELLINGA N, BOERMA EC, KOOPMANS M, et al. Mildly elevated lactate levels are associated with microcirculatory flow abnormalities and increased mortality: a microSOAP post hoc analysis[J]. Crit Care, 2017, 21(1): 255. DOI: 10.1186/s13054-017-1842-7.
    [36] BAKKER J, NIJSTEN MW, JANSEN TC. Clinical use of lactate monitoring in critically ill patients[J]. Ann Intensive Care, 2013, 3(1): 12. DOI: 10.1186/2110-5820-3-12.
    [37] JEPPESEN JB, MORTENSEN C, BENDTSEN F, et al. Lactate metabolism in chronic liver disease[J]. Scand J Clin Lab Invest, 2013, 73(4): 293-299. DOI: 10.3109/00365513.2013.773591.
    [38] BOSOI CR, ROSE CF. Elevated cerebral lactate: Implications in the pathogenesis of hepatic encephalopathy[J]. Metab Brain Dis, 2014, 29(4): 919-925. DOI: 10.1007/s11011-014-9573-9.
  • 加载中
图(1) / 表(6)
计量
  • 文章访问数:  614
  • HTML全文浏览量:  205
  • PDF下载量:  92
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-12-06
  • 录用日期:  2022-01-22
  • 出版日期:  2022-07-20
  • 分享
  • 用微信扫码二维码

    分享至好友和朋友圈

目录

    /

    返回文章
    返回