标题：含血常规和凝血四项指标的风险模型对恶性血液病继发脓毒症的预测价值及临床效用

      作者：陈超华 1，孙立涛 2，陶毅森 1，许春江 3    陈超华 1，孙立涛 2，陶毅森 1，许春江 31.平顶山市第一人民医院检验科，河南 平顶山 467000；2.南阳医学高等专科学校第一附属医院输血科，河南 南阳 473000；3.开封市人民医院检验科，河南 开封 475000

      卷次： 2024年35卷14期

      【摘要】 目的 构建含血常规和凝血四项指标预测恶性血液病继发脓毒症的风险模型，并分析其预测价值及临床效用，为临床工作提供有利参考。方法 回顾性选取2020年6月至2023年10月平顶山市第一人民医院收治的326例恶性血液病患者的临床资料，根据是否继发脓毒症分为继发组150例和未继发组176例，比较两组患者的临床资料、血常规和凝血四项指标；采用Logistic回归分析恶性血液病继发脓毒症的影响因素，并构建风险模型；绘制受试者工作特征(ROC)曲线分析含与不含血常规和凝血四项指标的风险模型的预测价值，采用"rmda"软件包绘制决策(DCA)曲线分析含与不含血常规和凝血四项指标的风险模型对恶性血液病继发脓毒症的预测价值及临床效用。结果 继发组患者的机械通气占比、总胆红素、肌酐、血清白介素-6 (IL-6)、中性粒细胞表面分子 CD64(CD64)、超敏C-反应蛋白(hs-CRP)水平明显高于未继发组，差异均有统计学意义(P<0.05)；继发组患者的红细胞计数(RBC)、血红蛋白(Hb)、纤维蛋白原(FIB)水平分别为(88.06±18.40)×109/L、(2.82±0.83) g/L、(2.15±0.28) g/L，明显低于未继发组的(117.52±23.81)×109/L、(3.96±0.88) g/L、(3.73±0.35) g/L，差异均有统计学意义(P<0.05)；继发组患者的PT、APTT、TT水平分别为(15.24±2.52) s、(41.47±9.42) s、(21.51±2.47) s，明显高于未继发组的(11.64±1.43) s、(28.84±7.81) s、(12.43±1.16) s，差异均有统计学意义(P<0.05)；经Logistic回归分析结果显示，RBC、Hb、PT、APTT、TT、FIB、机械通气、IL-6、CD64、hs-CRP均为恶性血液病继发脓毒症的危险因素(P<0.05)；经ROC分析结果显示，含与不含血常规和凝血四项指标的风险模型的AUC值分别为 0.948 (95%CI：0.911~0.973)、0.869 (95%CI：0.818~0.910)；经DCA曲线分析结果显示，与不含血常规和凝血四项指标曲线相比，含血常规和凝血四项指标的复合风险模型具有较高的净获益率。结论 恶性血液病患者RBC、Hb、PT、APTT、TT、FIB与继发脓毒症有关，建立含上述血常规和凝血四项指标的风险模型对继发脓毒症有较高预测价值及临床效用。
      【关键词】 恶性血液病；继发脓毒症；血常规；凝血四项；预测价值
      【中图分类号】 R552 【文献标识码】 A 【文章编号】 1003—6350（2024）14—2031—06

Predictive value and clinical utility of a risk model containing blood routine and four items of blood coagulationfor sepsis secondary to hematological malignancies.
CHEN Chao-hua 1, SUN Li-tao 2, TAO Yi-sen 1, XU Chun-jiang 3.1. Department of Clinical Laboratory, Pingdingshan First People's Hospital, Pingdingshan 467000, Henan, CHINA;2. Department of Blood Transfusion, the First Affiliated Hospital of Nanyang Medical College, Nanyang 473000, Henan,CHINA; 3. Department of Clinical Laboratory, Kaifeng People's Hospital, Kaifeng 475000, Henan, CHINA
【Abstract】 Objective To construct a risk model containing blood routine and four items of blood coagulationfor predicting sepsis secondary to hematological malignancies, and to analyze its predictive value and clinical utility, soas to provide a favorable reference for clinical work.Methods The clinical data of 326 patients with hematological ma-lignancies admitted to Pingdingshan First People's Hospital from June 2020 to October 2023 were retrospectively select-ed. According to whether secondary sepsis occurred, they were divided into secondary group (150 cases) and non-sec-ondary group (176 cases). The clinical data, blood routine, and four items of blood coagulation were compared betweenthe two groups. Logistic regression was used to analyze the influencing factors of sepsis secondary to hematologicalmalignancies, and a risk model was constructed. The receiver operating characteristic (ROC) curve was drawn to ana-lyze the predictive value of the risk model with and without blood routine and four items of blood coagulation. The 'rm-da' software package was used for decision curve analysis (DCA) to analyze the predictive value and clinical utility ofthe risk model with and without blood routine and four items of blood coagulation for sepsis secondary to hematologi-cal malignancies. Results The proportion of mechanical ventilation, total bilirubin, creatinine, serum interleukin-6(IL-6), neutrophil surface molecule CD64 (CD64), and high-sensitivity C-reactive protein (hs-CRP) levels in the sec-ondary group were significantly higher than those in the non-secondary group (P<0.05). The levels of red blood cellcount (RBC), hemoglobin (Hb), and fibrinogen (FIB) in the secondary group were (88.06±18.40)×109/L, (2.82±0.83) g/L,and (2.15±0.28) g/L, respectively, which were significantly lower than (117.52±23.81)×109/L, (3.96±0.88) g/L, and (3.73±0.35) g/L in the non-secondary group (P<0.05). The levels of PT, APTT, and TT in the secondary group were (15.24±2.52) s, (41.47±9.42) s, and (21.51±2.47) s, respectively, which were significantly higher than (11.64±1.43) s, (28.84±7.81) s, and (12.43±1.16) s in the non-secondary group (P<0.05). The results of logistic regression analysis showedthat RBC, Hb, PT, APTT, TT, FIB, mechanical ventilation, IL-6, CD64, and hs-CRP were all risk factors for second-ary sepsis in hematologic malignancies (P<0.05). The results of ROC analysis showed that the AUC values of the riskmodels with and without blood routine and coagulation indicators were 0.948 (95%CI: 0.911-0.973) and 0.869 (95%CI:0.818-0.910), respectively. The results of DCA showed that the risk model with blood routine and four items of blood co-agulation had a higher net benefit rate compared with that without blood routine and four items of blood coagulation.Conclusion RBC, Hb, PT, APTT, TT and FIB in patients with hematological malignancies are related to secondary sep-sis. The establishment of a risk model containing blood routine and four items of blood coagulation has high predictivevalue and clinical utility for secondary sepsis.
      【Key words】 Hematological malignancies; Secondary sepsis; Blood routine examination; Four indicators of coag-ulation; Predictive value