Predictive value of red blood cell distribution width to platelet count ratio for prognosis of patients with sepsis in emergency department
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摘要: 目的 观察急诊科脓毒症患者红细胞分布宽度与血小板计数比值(RPR)的变化趋势并评价其对脓毒症患者预后的预测价值。方法 连续收集2018年11月—2020年12月期间中国康复研究中心急诊科收治的223例脓毒症患者，记录患者的一般临床资料、入院24 h内急性生理与慢性健康状况评分系统Ⅱ(APACHE Ⅱ)评分、序贯器官衰竭评分(SOFA)和入院后第1、2、4、7天的红细胞分布宽度(RDW)、血小板(PLT)计数，计算RPR(RPR=RDW/PLT)。根据是否发生院内死亡将患者分为死亡组110例和存活组113例。采用广义估计方程分析两组患者入院后第1、2、4、7天RPR的变化趋势及组间差异; 绘制受试者工作特征(ROC)曲线，评价不同时间RPR对脓毒症患者院内死亡的预测价值; 根据最佳截断值区分患者是否为高RPR，采用logistic回归分析法分析脓毒症患者院内死亡的危险因素。结果 入组223例脓毒症患者，其中院内死亡110例，院内病死率为49.33%。RPR的组间(Waldχ2=8.979，P=0.003)和时点(Waldχ2=13.028，P=0.005)的整体差异均有统计学意义，且组间和时点存在交互作用(Waldχ2=14.660，P=0.002)，即存活组和死亡组RPR随时间的变化不同。存活组的RPR第2天高于第1天(P=0.043)，第7天时降低，小于第4天(P＜0.001)，并降到第1天以下(P=0.048);而死亡组RPR随时间延长呈上升趋势，第7天时仍大于第1天(P=0.024)。与存活组相比，第4天(P=0.034)与第7天(P=0.001)时死亡组RPR高于存活组; 第1天和第2天时，与存活组相比，死亡组RPR有升高的趋势，但两组差异并无统计学意义(P＞0.05)。第7天RPR预测脓毒症患者院内死亡的ROC曲线下面积为0.741(95%CI：0.642~0.840，P＜0.001)，以0.093为最佳分界点，其敏感度为0.690，特异度为0.729，约登指数为0.419。logistic回归分析结果显示：年龄(OR=1.067，95%CI：1.018~1.119)、APACHE Ⅱ评分(OR=1.065，95%CI：1.004~1.131)、白蛋白(OR=0.826，95%CI：0.755~0.903)、肌钙蛋白T(OR=9.719，95%CI：1.206~78.311)、第7天高RPR(OR=4.560，95%CI：1.999~10.403)是脓毒症患者院内死亡的影响因素。结论 RPR持续升高可提示脓毒症患者预后不良，入院第7天RPR水平对评估脓毒症患者预后的价值最大，动态检测RPR水平有助于判断脓毒症患者的预后。Abstract: Objective To explore the predictive value of dynamic changes in red blood cell distribution width to platelet count ratio(RPR) for prognosis of sepsis patients in emergency department.Methods From November 2018 to December 2020, patients with sepsis admitted to the emergency department of China Rehabilitation Research Center were enrolled. Data of the patients' general clinical information, acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score, sequential organ failure assessment (SOFA) score in 24h after admission the red blood cell distribution width(RDW) and platelet count(PLT) on 1, 2, 4, 7 days after admission were collected. The ratio of RDW to PLT(RPR) was calculated. The patients were divided into the survival group and non-survival group according to the in-hospital outcome. The generalized estimating equations were conducted to compare data from repeated measures. Receiver operating characteristic(ROC) curve was plotted to evaluate the predictive value of dynamic RPR levels for prognosis of sepsis. The optimal cutoff value was used to distinguish patients with high RPR and logistic regression was used to analyze the risk factors of in-hospital mortality.Results A total of 223 sepsis patients were enrolled, and among them, 110 patients died in hospital with an in-hospital mortality of 49.33%. There were significant differences in RPR between groups(Waldχ2=8.979,P=0.003) and time points(Waldχ2=13.028,P=0.005), and an interaction effect was noted between groups and time(Waldχ2=14.660,P=0.002). The RPR level increased significantly on day 2(P=0.043 vs.day 1) and decreased on day 7(P< 0.001 vs.day 4) in survival group, while in non-survival group, an overall upward trend of RPR level according to the time was observed. The RPR level on day 7 was significantly lower than that on day 1(P=0.048) in survival group, but still significantly higher than that on day 1(P=0.024) in non-survival group. Compared with patients in survival group, patients in non-survival group showed a higher RPR level on day 4(P=0.034) and day 7(P=0.001), while there was no significant difference between the two groups on day 1 and day 2(P> 0.05). The area under ROC curve of RPR on day 7 for predicting in-hospital death of sepsis patients was 0.741(95%CI: 0.642-0.840,P< 0.001). The cutoff value of prediction was 0.093 with the Yoden index of 0.419, which yielded a sensitivity of 0.690 and a specificity of 0.729. Binary logistic regression analysis showed that age(OR=1.067, 95%CI: 1.018-1.119)、APACHE Ⅱscore(OR=1.065, 95%CI: 1.004-1.131)、albumin(OR=0.826, 95%CI: 0.755-0.903)、troponin-T(OR=9.719, 95%CI: 1.206-78.311) and high RPR on day 7(OR=4.560, 95%CI: 1.999-10.403) were independent risk factors for in-hospital mortality of patients with sepsis.Conclusion The continuous increase of RPR indicates poor prognosis, and the RPR level on day 7 is one of the most important indicators to evaluate the prognosis of patients with sepsis. Dynamic determination of RPR can evaluate the prognosis of sepsis patients.
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Key words:
- sepsis /
- prognosis /
- red blood cell distribution width /
- platelet count /
- ratio
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表 1 两组患者临床资料比较
例(%)，M(P25，P75) 项目 死亡组(110例) 存活组(113例) Z/χ2 P 年龄/岁 85.00(78.75，88.00) 81.00(70.00，87.50) -3.095 0.002 男性 59(53.64) 74(65.49) 3.252 0.071 合并疾病 高血压 67(60.91) 66(58.41) 0.145 0.703 糖尿病 47(42.73) 46(40.71) 0.093 0.760 冠心病 37(33.64) 34(30.09) 0.323 0.570 脑血管病 35(31.82) 32(28.32) 0.325 0.569 慢性肾脏病 6(5.45) 7(6.19) 0.056 0.814 其他 63(57.27) 58(51.33) 0.794 0.373 感染部位 呼吸道 93(84.55) 84(74.34) 2.243 0.134 腹腔 20(18.18) 30(26.55) 2.033 0.154 泌尿道 24(21.82) 29(25.66) 0.455 0.500 皮肤和软组织 10(9.09) 4(3.54) 2.919 0.088 其他 4(3.64) 1(0.88) 0.874 0.350 SOFA评分/分 7.00(5.00，9.00) 6.00(4.00，8.00) -4.902 ＜0.001 APACHE Ⅱ评分/分 25.00(21.75，29.00) 21.00(17.00，27.00) -5.425 ＜0.001 脓毒性休克 51(46.36) 27(23.89) 12.374 ＜0.001 ICU入住时间/d 11.00(3.00，18.00) 13.00(7.50，40.00) -0.851 0.395 实验室指标 WBC/(×109·L-1) 13.61(8.77，18.14) 13.32(9.52，18.56) -0.249 0.803 CRP/(mg·L-1) 83.65(31.06，208.82) 99.69(23.58，202.96) -0.108 0.914 PCT/(ng·mL-1) 4.60(1.08，16.00) 2.10(0.43，9.50) -3.290 0.001 白蛋白/(g·L-1) 31.40(27.53，35.03) 35.80(32.55，39.10) -4.776 ＜0.001 肌酐/(μmol·L-1) 176.85(81.25，229.33) 132.20(90.10，199.60) -2.291 0.022 TnT/(μg·L-1) 0.079(0.047，0.228) 0.037(0.012，0.097) -4.398 ＜0.001 乳酸/(mmol·L-1) 2.85(1.68，4.19) 2.10(1.20，4.18) -3.593 ＜0.001 
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表 2 不同时点两组RPR的估测边际均值
时点 分组 Mean SE 95%CI 下限 上限 第1天 存活组 0.103 0.009 0.085 0.120 死亡组 0.165 0.031 0.103 0.226 第2天 存活组 0.121 0.010 0.102 0.139 死亡组 0.208 0.046 0.119 0.298 第4天 存活组 0.128 0.015 0.099 0.157 死亡组 0.258 0.060 0.142 0.375 第7天 存活组 0.085 0.005 0.074 0.096 死亡组 0.287 0.060 0.169 0.405
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表 3 二分类logistic回归分析脓毒症患者死亡危险因素结果
变量 β SE Wald P OR 95%CI 下限 上限 年龄 0.065 0.024 7.407 0.006 1.067 1.018 1.119 APACHE Ⅱ评分 0.063 0.030 4.352 0.037 1.065 1.004 1.131 白蛋白 -0.192 0.045 17.751 ＜0.001 0.826 0.755 0.903 TnT 2.274 1.065 4.563 0.033 9.719 1.206 78.311 第7天高RPR 1.517 0.421 13.006 ＜0.001 4.560 1.999 10.403 常数 -2.272 2.357 0.930 0.335 0.103
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[1] 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. doi: 10.1001/jama.2016.0287
[2] Reinhart K, Daniels R, Kissoon N, et al. Recognizing sepsis as a global health priority-A WHO Resolution[J]. N Engl J Med, 2017, 377(5): 414-417. doi: 10.1056/NEJMp1707170
[3] 中国医疗保健国际交流促进会急诊医学分会, 中华医学会急诊医学分会, 中国医师协会急诊医师分会, 等. 中国脓毒症早期预防与阻断急诊专家共识[J]. 临床急诊杂志, 2020, 21(7): 517-529. http://zzlc.cbpt.cnki.net/WKC/WebPublication/paperDigest.aspx?paperID=e3d5ade2-9b78-45b6-b933-5af62fe3594a
[4] Wang M, Jiang L, Zhu B, et al. The prevalence, risk factors, and outcomes of sepsis in critically ill patients in China: a multicenter prospective cohort study[J]. Front Med, 2020, 7: 593808. doi: 10.3389/fmed.2020.593808
[5] Chen B, Ye B, Zhang J, et al. RDW to platelet ratio: a novel noninvasive index for predicting hepatic fibrosis and cirrhosis in chronic hepatitis B[J]. PLoS One, 2013, 8(7): e68780. doi: 10.1371/journal.pone.0068780
[6] Tekin YK, Tekin G. Mean platelet volume-to-platelet count ratio, mean platelet volume-to-lymphocyte ratio, and red blood cell distribution width-platelet count ratio as markers of inflammation in patients with ascending thoracic aortic aneurysm[J]. Braz J Cardiovasc Surg, 2020, 35(2): 175-180.
[7] Qiu L, Chen C, Li SJ, et al. Prognostic values of red blood cell distribution width, platelet count, and red cell distribution width-to-platelet ratio for severe burn injury[J]. Sci Rep, 2017, 7(1): 13720. doi: 10.1038/s41598-017-13151-3
[8] Ge S, Lin S, Zhang L, et al. The association of red blood cell distribution width to platelet count ratio and 28-day mortality of patients with sepsis: a retrospective cohort study[J]. Ther Clin Risk Manag, 2020, 16: 999-1006. doi: 10.2147/TCRM.S268523
[9] 冯国双. 重复测量数据的常用统计分析方法[J]. 中华预防医学杂志, 2020, 54(7): 804-812. doi: 10.3760/cma.j.cn112150-20200514-00728
[10] Silva Litao MK, Kamat D. Back to basics: red blood cell distribution width: clinical use beyond hematology[J]. Pediatr Rev, 2018, 39(4): 204-209. doi: 10.1542/pir.2017-0118
[11] Zou XL, Lin XJ, Ni X, et al. Baseline red blood cell distribution width correlates with disease activity and therapeutic outcomes in patients with systemic lupus erythematosus, irrespective of anemia status[J]. Clin Lab, 2016, 62(10): 1841-1850.
[12] Al-Rawi ZS, Gorial FI, Al-Bayati AA. Red cell distribution width in rheumatoid arthritis[J]. Mediterr J Rheumatol, 2018, 29(1): 38-42. doi: 10.31138/mjr.29.1.38
[13] 王卿语, 陈新军, 武冬, 等. 中性粒细胞与淋巴细胞比值及红细胞分布宽度对脓毒症患者预后评估价值性[J]. 临床急诊杂志, 2021, 22(2): 136-140. http://zzlc.cbpt.cnki.net/WKC/WebPublication/paperDigest.aspx?paperID=164cc8f5-e091-40a8-849b-4b0d07f86024
[14] Hu ZD, Lippi G, Montagnana M. Diagnostic and prognostic value of red blood cell distribution width in sepsis: A narrative review[J]. Clin Biochem, 2020, 77: 1-6. doi: 10.1016/j.clinbiochem.2020.01.001
[15] Fraenkel PG. Anemia of inflammation: A review[J]. Med Clin North Am, 2017, 101(2): 285-296. doi: 10.1016/j.mcna.2016.09.005
[16] Yuan T, Cong Y, Meng J, et al. Arachidonic acid causes hidden blood loss-like red blood cell damage through oxidative stress reactions[J]. J Surg Res, 2017, 211: 14-20.
[17] Subramani K, Raju SP, Chu X, et al. Effect of plasma-derived extracellular vesicles on erythrocyte deformability in polymicrobial sepsis[J]. Int Immunopharmacol, 2018, 65: 244-247. doi: 10.1016/j.intimp.2018.10.011
[18] Venkata C, Kashyap R, Farmer JC, et al. Thrombocytopenia in adult patients with sepsis: incidence, risk factors, and its association with clinical outcome[J]. J Intensive Care, 2013, 1(1): 9-18. doi: 10.1186/2052-0492-1-9
[19] Bedet A, Razazi K, Boissier F, et al. Mechanisms of thrombocytopenia during septic shock: a multiplex cluster analysis of endogenous sepsis mediators[J]. Shock, 2018, 49(6): 641-648. doi: 10.1097/SHK.0000000000001015
[20] Vardon-Bounes F, Ruiz S, Gratacap MP, et al. Platelets are critical key players in sepsis[J]. Int J Mol Sci, 2019, 20(14): 3494.
[21] 王莉, 蔡强. 红细胞分布宽度与血小板计数比值对脓毒症患儿预后的预测价值[J]. 中国当代儿科杂志, 2019, 21(11): 1079-1083. doi: 10.7499/j.issn.1008-8830.2019.11.005
[22] 郑金浩, 刁孟元, 单怡, 等. 动态检测红细胞分布宽度评估脓毒症预后的价值[J]. 中国急救医学, 2015, 35(5): 390-393.
[23] Akca S, Haji-Michael P, de Mendonça A, et al. Time course of platelet counts in critically ill patients[J]. Crit Care Med, 2002, 30(4): 753-756.
[24] 张玉坤, 霍书花, 田英平, 等. 降钙素原及其清除率对脓毒症预后评估的价值研究[J]. 中国急救医学, 2019, 39(11): 1098-1101. https://www.cnki.com.cn/Article/CJFDTOTAL-ZJJY201911018.htm
[25] Schuetz P, Birkhahn R, Sherwin R, et al. Serial procalcitonin predicts mortality in severe sepsis patients: results from the multicenter procalcitonin monitoring sepsis(MOSES)Study[J]. Crit Care Med, 2017, 45(5): 781-789.
[26] 王静波, 燕宪亮, 王厚清, 等. 血清microRNA-25对脓毒症患者病情严重程度及预后的评估价值[J]. 临床急诊杂志, 2020, 21(6): 493-498. http://zzlc.cbpt.cnki.net/WKC/WebPublication/paperDigest.aspx?paperID=37f07117-062e-42b8-a8b0-81a6f052cecb
[27] 张运君, 卓小岸, 周小曼, 等. 急诊脓毒症患者血清降钙素原的变化及预后危险因素分析[J]. 重庆医学, 2017, 46(24): 3392-3395. https://www.cnki.com.cn/Article/CJFDTOTAL-CQYX201724024.htm
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