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脓毒症患者细胞因子动态变化和免疫状态分型 被引量:31

The dynamic changes of cytokine profiles and immune status-associated classification in sepsis patients
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摘要 目的探讨细胞因子浓度与脓毒症病情程度、预后的相关性及动态变化规律,并利用简单的免疫状态分型标准探讨不同病情和预后的脓毒症患者免疫状态特点。方法收集2013年2月至2016年2月复旦大学附属中山医院急诊ICU收治的317例重症患者进行回顾性研究。化学发光法测定细胞因子(TNF-α、IL-1β、IL-2R、IL-6、IL-8、IL-10)的浓度;APACHEⅡ和SOFA评分评估病情程度。将脓毒症患者诊断24h内细胞因子浓度中位数作为分界点,高于中位数的记为"阳性(+)",低于中位数的记为"阴性(-)"。按生物活性分为炎性介质(TNF-α、IL-2R、IL-6、IL-8)和抗炎症介质(IL-10)两类。根据细胞因子是否阳性及阳性的个数,将患者的免疫状态分为3种类型即SIRS,CARS和MARS进行研究。结果①脓毒症患者TNF-α(P〈0.01)、IL-2R(P〈0.01)、IL-6(P〈0.01)、IL-8(P〈0.01)、IL-10(P〈0.01)血清浓度,APACHEⅡ(P〈0.01)和SOFA(P〈0.01)评分高于对照组;②与存活组相比,脓毒症死亡组患者血清IL-2R(P=0.003)、IL-6(P=0.016)、IL-8(P〈0.01)、IL-10(P=0.032)浓度明显升高;③在两组患者中细胞因子存在动态变化,存活组在第3天与第7天间IL-2R(P=0.048)、IL-6(P=0.014)、IL-8(P=0.006)和IL-10(P=0.001)浓度下降,而死亡组在第3与7天之间IL-8(P=0.021)和IL-10(P=0.024)浓度升高。细胞因子浓度在第1天和第3天变化不明显(P〉0.05)。细胞因子的趋势变化早于危重病评分;④不同病情程度和预后的脓毒症患者免疫状态不同,轻度脓毒症和存活组患者主要以SIRS为主,而严重脓毒症和死亡组患者主要为MARS或CARS状态。MARS状态是脓毒症患者死亡的高危因素(P=0.007,OR=2.70,95%CI:1.36-5.36)。结论根据TNF-α、IL-2R、IL-6、IL-8和IL-10浓度变化构建的免疫状态分型,有望成为判断脓毒症患者预后的敏感指标,细胞因子的变化发生在72h后,早于危重病评分。 Objective To investigate the correlation between concentration of cytokines and the severity, prognosis of sepsis using a criteria for immune status-associated categorization defined to judge immune statuses of sepsis patients with different clinical settings and prognosis. Methods From February 2013 to February 2016, a total of 317 severe inpatients in ICU were enrolled in this retrospectively study. They were subjected to serum cytokines (TNF-α, IL-113, IL-2R, IL-6, IL-8 and IL-10) screening by employing Chemol method. The scoring systems of APACHE Ⅱ and SOFA were also used to evaluate the illness severity. Three immune status-associated categories, namely SIRS (0 -4 pro- inflammatory cytokines/IL-10), CARS (0 - 2 pro-inflammatory cytokines/IL-10) and MARS (3 - 4 pro- inflammatory cytokines/IL-10), were defined according to the profiles of 4 pro-inflammatory cytokines, TNF-α, IL-2R, IL-6, IL-8, and one anti-inflammatory cytokine, IL-10, in which the positive criteria were distinguished by the median of levels of cytokines. Results ①The serum concentrations of TNF-α (P 〈 0.01), IL-2R (P〈0.01), IL-6 (P=0.034), IL-8 (P〈0.01), IL-10 (P〈0.01) and APACHE Ⅱ (P 〈 0. 01 ), SOFA (P 〈 0. 01 ) scores in the sepsis group were significantly higher than those in the control group. ②All septic patients were divided into survival and non-survival group according to 30-d survival. The serum levels of IL-2R (P =0. 003), IL-6 (P =0. 016), IL-8 (P 〈0. 01) and IL-10 (P =0. 032) in the non-survival group were significantly higher than those in the survival group.③In the survival and non-survival patients, the cytokine level was changed dynamically. The serum levels significantly decreased in survival group for IL-2R (P =0. 048), IL-6 (P =0. 014), IL-8 (P =0. 006) and IL-10 (P =0. 001 ) and upregulated for IL-8 (P = 0. 021 ) and IL-10 (P = 0. 024) in non-survival group between the 3rd and 7st day . while no variation in cytokines was observed between the 1st and 3rd day in both groups (P 〉 0. 05). These data showed that the change in cytokines occurred was earlier than that in APACHE Ⅱ and SOFA scores. ④The SIRS was a predominant immune status in the mild septic and survival patients, whereas CARS and MARS became the dominated statuses in the severe septic and non-survival patients. Therefore, MARS was a high-risk factor causing high mortality of sepsis patients ( P = 0. 007, OR = 2. 70, 95% CI: 1.36 - 5.36) . Conclusion The immune status-associated categorization defined by serum levels of IL-2R, IL-6, IL-8 and IL-10 were promising to become the sensitive prognosis markers for sepsis patients in view of their trend of change occurred 72 hours in advance of the changes in APACHE Ⅱ and SOFA scores.
出处 《中华急诊医学杂志》 CAS CSCD 北大核心 2017年第2期149-154,共6页 Chinese Journal of Emergency Medicine
基金 国家自然科学基金(81471840,81171837) 上海市中医药发展三年行动计划(ZY3-CCCX-3-3018) 国家临床重点专科建设项目 复旦大学附属中山医院优秀骨干人才培养基金.
关键词 脓毒症 细胞因子 TNF-α IL-2R IL-6 IL-8 IL-10 免疫状态分型 动态变化 Sepsis Cytokine TNF-α IL-2R IL-6 IL-8 IL-10 Immune status-associated classification Dynamic changes
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