血清高速泳动族蛋白B1在评估脓毒症患者预后中的作用
Role of serum high mobility group box-B1 in evaluating prognosis of sepsis
Received date: 2022-06-22
Online published: 2023-05-15
目的: 探讨血清高速泳动族蛋白B1(high-mobility group box-B1, HMGB1)对脓毒症患者预后评估的价值。方法: 选取2018年1月至2021年12月上海交通大学医学院附属仁济医院南院收治的342例脓毒症患者作为研究对象,其中男性192例,女性150例,平均年龄(60.54±17.85)岁。根据28 d预后结局分为生存组和死亡组,收集各种临床资料,并测定入院第1天的HMGB1水平。利用COX多元回归分析脓毒症患者预后不良的危险因素。采用Pearson分析血清HMGB1与序贯器官衰竭评估(sequential organ failure assessment, SOFA)评分、急性生理学和慢性健康状况评价Ⅱ(acute physiology and chronic health evaluation Ⅱ,APACHEⅡ)评分的相关性。绘制受试者操作特征曲线(receiver operator characteristic curve,ROC曲线),分析血清HMGB1评估脓毒症预后的曲线下面积(area under the curve,AUC)及截断值。根据ROC曲线确定的血清HMGB1截断值将患者分成高HMGB1水平组、低HMGB1水平组,绘制Kaplan Meier生存曲线图,进一步分析血清HMGB1与预后的关系。结果: 所有入组患者的死亡率为29.2%(100例)。死亡组中血清HMGB1、C反应蛋白、降钙素原、白细胞计数、乳酸水平、SOFA及APACHEⅡ评分、呼吸道感染、并发脓毒症休克及弥散性血管内凝血、接受机械通气的比例均明显高于生存组(均P<0.05),合并糖尿病、泌尿道感染比例明显低于生存组(均P<0.05)。多元回归分析显示血清HMGB1水平、SOFA评分、白细胞计数、呼吸道感染均是脓毒症28 d死亡的影响因素。Pearson相关性分析发现脓毒症患者血清HMGB1水平与SOFA评分、APACHEⅡ评分呈正相关(P<0.001)。ROC曲线显示HMGB1、SOFA评分、APACHEⅡ评分预测脓毒症28 d死亡的AUC分别为0.776、0.774、0.760。Kaplan Meier生存曲线发现高HMGB1水平组患者的28 d死亡率明显高于低HMGB1水平组(P<0.001)。结论: 血清HMGB1水平在脓毒症死亡组中明显升高,是预测脓毒症28 d死亡的危险因素之一,其预测效能不劣于SOFA评分、APACHEⅡ评分。
关键词: 脓毒症; 血清高速泳动族蛋白B1; 急性生理学和慢性健康状况评价Ⅱ; 预后
乔敏捷, 周巍, 陈怡 . 血清高速泳动族蛋白B1在评估脓毒症患者预后中的作用[J]. 内科理论与实践, 2023 , 18(02) : 70 -75 . DOI: 10.16138/j.1673-6087.2023.02.002
Objective To investigate the prognostic value of serum high mobility group box-B1 (HMGB1) in the patients with sepsis. Methods A total of 342 patients with sepsis who were admitted to Renji Hospital (South Campus) Shanghai Jiao Tong University School of Medicine, from January 2018 to December 2021 were enrolled. There were 192 male and 150 female sepsis patients, with an average age of (60.54±17.85) years. The patients were divided into the survival group and the death group based on 28-day outcome. The clinical data were collected and the level of HMGB1 on admission was tested. COX multivariate regression was used to analyze the risk factors for poor prognosis of the sepsis patients. Pearson correlation analysis was performed to analyze the correlation between serum HMGB1, sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation Ⅱ(APACHEⅡ) score. Receiver operator characteristic (ROC) curves were drawn to analyze the area under the ROC curve (AUC) and cut-off value of serum HMGB1 to evaluate the prognosis of sepsis. According to the cut-off value of serum HMGB1, the patients were divided into high level group and low level group. Kaplan Meier survival curve was drawn to further analyze the relationship between serum HMGB1 and prognosis. Results The mortality rate of sepsis patients was 29.2% (n=100). The indexes which included the level of serum HMGB1, C-reactive protein, procalcitonin, white blood cell count, lactic acid level, SOFA and APACHEⅡ score, the proportion of respiratory tract infection, septic shock, disseminated intravascular coagulation and mechanical ventilation in sepsis death group were significantly higher than those in survival group (all P<0.05), while the proportion of diabetes mellitus and urinary tract infection were significantly lower than those in survival group (all P<0.05). Multiple regression analysis showed that serum HMGB1 level, SOFA score, white blood cell count and respiratory tract infection were the risk factors for 28-day mortality. Pearson correlation analysis presented that serum HMGB1 level was positively correlated with SOFA score and APACHEⅡ score in the sepsis patients (P<0.001). The ROC curve showed that AUC of HMGB1, SOFA score and APACHEⅡ score for predicting 28-day mortality were 0.776, 0.774 and 0.760, respectively. Kaplan Meier survival curve found that 28-day mortality was significantly higher in the patients with higher HMGB1 levels than those with lower HMGB1 levels (P<0.001). Conclusions Serum HMGB1 level increased significantly in the death group, which was one of the risk factors for predicting 28-day mortality, and its predictive efficacy was not inferior to SOFA and APACHEⅡ score.
[1] | Rhodes A, Evans LE, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock: 2016[J]. Intensive Care Med, 2017, 43(3): 304-377. |
[2] | Deutschman CS, Tracey KJ. Sepsis: current dogma and new perspectives[J]. Immunity, 2014, 40(4): 463-475. |
[3] | 曹钰, 柴艳芬, 邓颖, 等. 中国脓毒症/脓毒性休克急诊治疗指南(2018)[J]. 临床急诊杂志, 2018, 19(09): 567-588. |
[4] | Cecconi M, Evans L, Levy M, et al. Sepsis and septic shock[J]. Lancet, 2018, 392(10141): 75-87. |
[5] | Keeley A, Hine P, Nsutebu E. The recognition and management of sepsis and septic shock: a guide for non-intensivists[J]. Postgrad Med J, 2017, 93(1104): 626-634. |
[6] | Vincent JL, Sakr Y, Sprung CL, et al. Sepsis in European intensive care units: results of the SOAP study[J]. Crit Care Med, 2006, 34(2): 344-353. |
[7] | Martin GS, Mannino DM, Eaton S, et al. The epidemiology of sepsis in the United States from 1979 through 2000[J]. N Engl J Med, 2003, 348(16): 1546-1554. |
[8] | Vincent JL, Marshall JC, Namendys-Silva SA, et al. Assessment of the worldwide burden of critical illness: the Intensive Care Over Nations(ICON) audit[J]. Lancet Respir Med, 2014, 2: 380-386. |
[9] | van der Poll T, Shankar-Hari M, Wiersinga WJ. The immunology of sepsis[J]. Immunity, 2021, 54(11): 2450-2464. |
[10] | Casserly B, Phillips GS, Schorr C, et al. Lactate measurements in sepsis-induced tissue hypoperfusion: results from the Surviving Sepsis Campaign database[J]. Crit Care Med, 2015, 43(3): 567-573. |
[11] | Gu WJ, Zhang Z, Bakker J. Early lactate clearance-guided therapy in patients with sepsis: a meta-analysis with trial sequential analysis of randomized controlled trials[J]. Intensive Care Med, 2015, 41(10): 1862-1863. |
[12] | Jones AE, Shapiro NI, Trzeciak S, et al. Lactate clearance vs central venous oxygen saturation as goals of early sepsis therapy: a randomized clinical trial[J]. JAMA, 2010, 303(8): 739-746. |
[13] | Liu Z, Meng Z, Li Y, et al. Prognostic accuracy of the serum lactate level, the SOFA score and the qSOFA score for mortality among adults with sepsis[J]. Scand J Trauma Resusc Emerg Med, 2019, 27(1): 51. |
[14] | Singer M, Deutschman CS, Seymour CW, et al. The third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)[J]. JAMA, 2016, 315(8): 801-810. |
[15] | Silvestre J, Póvoa P, Coelho L, et al. Is C-reactive protein a good prognostic marker in septic patients?[J]. Intensive Care Med, 2009, 35(5): 909-913. |
[16] | van der Poll T, van de Veerdonk FL, Scicluna BP, et al. The immunopathology of sepsis and potential therapeutic targets[J]. Nat Rev Immunol, 2017, 17(7): 407-420. |
[17] | Chousterman BG, Swirski FK, Weber GF. Cytokine storm and sepsis disease pathogenesis[J]. Semin Immunopathol, 2017, 39(5): 517-528. |
[18] | Deng M, Tang Y, Li W, et al. The endotoxin delivery protein HMGB1 mediates caspase-11-dependent lethality in sepsis[J]. Immunity, 2018, 49(4): 740-753. |
[19] | Kazama H, Ricci JE, Herndon JM, et al. Induction of immunological tolerance by apoptotic cells requires caspase-dependent oxidation of high-mobility group box-1 protein[J]. Immunity, 2008, 29(1): 21-32. |
[20] | Ge Y, Huang M, Yao YM. The effect and regulatory mechanism of high mobility group Box-1 protein on immune cells in inflammatory diseases[J]. Cells, 2021, 10(5): 1044. |
[21] | Wang H, Bloom O, Zhang M, et al. HMG-1 as a late mediator of endotoxin lethality in mice[J]. Science, 1999, 285(5425): 248-251. |
[22] | Sunden-Cullberg J, Norrby-Teglund A, Treutiger CJ. The role of high mobility group box-1 protein in severe sepsis[J]. Curr Opin Infect Dis, 2006, 19(3): 231-236. |
/
〈 |
|
〉 |