摘要目的:探讨血小板最大聚集率（MAR）对脓毒性休克及脓毒性休克合并弥散性血管内凝血（DIC）的预测价值。方法:采用回顾性病例对照研究，针对2021年1月至2022年11月郑州大学第一附属医院重症医学科收治的脓毒症患者，收集其基本资料及入院24 h内的动态MAR、血常规、炎症指标、序贯器官衰竭评分（SOFA）等指标。根据有无脓毒性休克将脓毒症患者分为休克组和非休克组；再参照国际血栓与止血学会（ISTH）标准，根据有无显性DIC将脓毒性休克患者分为休克DIC组和休克非DIC组。比较各组间血小板聚集功能有无差异，绘制受试者工作特征曲线（ROC曲线）评价MAR对脓毒性休克及脓毒性休克合并DIC的预测价值。采用Spearman相关法分析脓毒症患者MAR与炎症指标及病情严重程度的相关性。结果:共纳入153例脓毒症患者，其中脓毒性休克患者61例（包括有显性DIC者17例和无显性DIC者44例）。与非休克组患者比较，休克组患者降钙素原（PCT）、C-反应蛋白（CRP）及SOFA评分均明显升高〔PCT（mg/L）：6.90（2.50，23.50）比0.87（0.26，5.75），CRP（mg/L）：156.48（67.11，230.84）比90.39（46.43，182.76），SOFA评分（分）：11.00（8.00，14.00）比5.00（3.00，8.00），均 P<0.05〕，同时血小板计数（PLT）及分别以二磷酸腺苷（ADP）、肾上腺素（A）、胶原（COL）、花生四烯酸（AA）为诱导剂的MAR（ADP-MAR、A-MAR、COL-MAR、AA-MAR）均明显降低〔PLT（×10 9/L）：101.00（49.00，163.50）比175.50（108.25，254.50），ADP-MAR：28.50%（22.00%，38.05%）比45.90%（33.98%，60.28%），A-MAR：38.90%（30.00%，55.40%）比65.15%（54.38%，72.53%），COL-MAR：27.90%（20.85%，36.55%）比42.95%（33.73%，54.08%），AA-MAR：24.70%（16.40%，34.20%）比46.55%（28.33%，59.20%），均 P<0.05〕。亚组分析显示，与休克非DIC组比较，休克DIC组患者SOFA评分明显升高（分：13.29±5.23比10.39±3.58， P<0.05），PLT和COL-MAR明显降低〔PLT（×10 9/L）：36.00（22.00，67.50）比115.50（84.25，203.75），COL-MAR：21.50%（17.85%，32.60%）比30.95%（22.98%，38.53%），均 P<0.05〕。ROC曲线分析显示，A-MAR对脓毒性休克的预测价值较高，其ROC曲线下面积（AUC）为0.814〔95%可信区间（95% CI）为0.742~0.886， P＝0.000〕，最佳截断值为51.35%，敏感度为68.9%，特异度为82.6%，阳性预测值为0.724，阴性预测值为0.800；COL-MAR对脓毒性休克合并DIC有一定预测价值，其AUC为0.668（95% CI为0.513~0.823， P＝0.044），最佳截断值为21.90%，敏感度为52.9%，特异度为79.5%，阳性预测值为0.500，阴性预测值为0.813。Spearman相关分析显示，脓毒症患者中各诱导剂诱导的MAR与炎症指标和SOFA评分呈不同程度负相关，其中A-MAR与SOFA评分的相关性最强（ r＝-0.327， P＝0.000）。 结论:血小板聚集功能指标MAR对脓毒性休克及脓毒性休克合并DIC有一定的预测价值，并对脓毒症患者的病情严重程度有一定的评估价值，可作为一种监测指标用于预测脓毒症患者病情的变化和指导治疗。

abstractsObjective:To investigate the predictive value of the maximum aggregation rate (MAR) of platelet for septic shock and septic shock with disseminated intravascular coagulation (DIC).Methods:A retrospective case-control study enrolled patients with sepsis admitted to department of critical care medicine of the First Affiliated Hospital of Zhengzhou University from January 2021 to November 2022. The basic data, dynamic platelet aggregation rate, blood routine, inflammation indicators, sequential organ failure assessment (SOFA) and other clinical indicators within 24 hours after admission were collected. Septic patients were divided into the shock group and the non-shock group according to the presence of septic shock; then refer to the International Society on Thrombosis and Hemostasis (ISTH) standard, patients with septic shock were divided into the shock DIC group and the shock non-DIC group according to the presence of dominant DIC. Compared the differences in platelet aggregation function between these groups, and the receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of the MAR for septic shock and septic shock with DIC. Spearman correlation analysis was used to analyze the correlation of MAR with inflammation indicators and the severity of illness in patients with sepsis.Results:A total of 153 sepsis patients were included and 61 with septic shock (including 17 with dominant DIC and 44 without dominant DIC). Compared with the non-shock group, the level of procalcitonin (PCT), C-reactive protein (CRP), and SOFA score were significantly higher in the shock group [PCT (mg/L): 6.90 (2.50, 23.50) vs. 0.87 (0.26, 5.75), CRP (mg/L): 156.48 (67.11, 230.84) vs. 90.39 (46.43, 182.76), SOFA score: 11.00 (8.00, 14.00) vs. 5.00 (3.00, 8.00), all P < 0.05]. The platelet count (PLT) and the MAR induced by adenosine diphosphate (ADP), adrenaline (A), collagen (COL), and arachidonic acid (AA; ADP-MAR, A-MAR, COL-MAR, AA-MAR) in the shock group were significantly decreased [PLT (×10 9/L): 101.00 (49.00, 163.50) vs. 175.50 (108.25, 254.50), ADP-MAR: 28.50% (22.00%, 38.05%) vs. 45.90% (33.98%, 60.28%), A-MAR: 38.90% (30.00%, 55.40%) vs. 65.15% (54.38%, 72.53%), COL-MAR: 27.90% (20.85%, 36.55%) vs. 42.95% (33.73%, 54.08%), AA-MAR: 24.70% (16.40%, 34.20%) vs. 46.55% (28.33%, 59.20%), all P < 0.05]. Subgroup analysis revealed that, compared with the shock non-DIC group, the SOFA scores were significantly higher in patients in the shock DIC group (13.29±5.23 vs. 10.39±3.58, P < 0.05), the PLT and COL-MAR in the shock DIC group were significantly reduced [PLT (×10 9/L): 36.00 (22.00, 67.50) vs. 115.50 (84.25, 203.75), COL-MAR: 21.50% (17.85%, 32.60%) vs. 30.95% (22.98%, 38.53%), all P < 0.05]. ROC curve analysis showed that A-MAR had a higher predictive value for septic shock, and the area under the ROC curve (AUC) was 0.814 [95% confidence interval (95% CI) was 0.742-0.886, P = 0.000]. When the optimal cut-off value was 51.35%, the sensitivity was 68.9%, the specificity was 82.6%, the positive predictive value was 0.724 and the negative predictive value was 0.800. COL-MAR had some predictive value for septic shock with DIC, and the AUC was 0.668 (95% CI was 0.513-0.823, P = 0.044). When the optimal cut-off value was 21.90%, the sensitivity was 52.9%, the specificity was 79.5%, the positive predictive value was 0.500, and the negative predictive value was 0.813. Spearman correlation analysis showed that the MAR induced by each inducer was negatively correlated with inflammatory indicators and SOFA scores in sepsis patients, with A-MAR showing the strongest correlation with SOFA score ( r = -0.327, P = 0.000). Conclusions:MAR, an indicator of platelet aggregation function, shows predictive value for septic shock and septic shock with DIC, and it could be used to for evaluating the severity of patients with sepsis. In addition, tt alsocan be used as a monitoring index to predict the changes of sepsis patients and to guide the treatment.