天津医药 ›› 2024, Vol. 52 ›› Issue (12): 1317-1321.doi: 10.11958/20241172

• 临床研究 • 上一篇    下一篇

SII、RAR与AECOPD患者病情严重程度及并发呼吸衰竭的关系

屠昌明(), 田园(), 汪鹏程, 任鹏, 赵寅生   

  1. 中国人民解放军联勤保障部队第九〇一医院检验输血科(邮编230031)
  • 收稿日期:2024-08-25 修回日期:2024-09-25 出版日期:2024-12-15 发布日期:2024-12-17
  • 通讯作者: △E-mail:523758894@qq.com
  • 作者简介:屠昌明(1986),男,主管技师,主要从事临床免疫学与血液学检验相关研究。E-mail:373906122@qq.com

Relationship between SII, RAR and severity of disease and respiratory failure in patients with AECOPD

TU Changming(), TIAN Yuan(), WANG Pengcheng, REN Peng, ZHAO Yinsheng   

  1. Department of Laboratory and Blood Transfusion, the 901st Hospital of the Joint Logistics Support Force of the People's Liberation Army of China, Hefei 230031, China
  • Received:2024-08-25 Revised:2024-09-25 Published:2024-12-15 Online:2024-12-17
  • Contact: △E-mail:523758894@qq.com

摘要:

目的 探究全身免疫炎症指数(SII)、红细胞分布宽度(RDW)与白蛋白(ALB)比值(RAR)与慢性阻塞性肺疾病急性加重期(AECOPD)患者病情严重程度及呼吸衰竭的关系。方法 110例AECOPD患者依病情分为重症组37例和非重症组73例,依据是否并发呼吸衰竭分为呼吸衰竭组26例和无呼吸衰竭组84例。对比各组血小板计数(PLT)、中性粒细胞计数(NEU)、淋巴细胞计数(LYM)、RDW、ALB、SII、RAR水平,重症、并发呼吸衰竭的影响因素分析应用多因素Logistic回归,绘制受试者工作特征(ROC)曲线分析指标对患者发生重症或并发呼吸衰竭的预测价值。结果 与非重症组比较,重症组NEU、SII、RDW、RAR水平增加,PLT、LYM水平降低(P<0.05);与无呼吸衰竭组比较,呼吸衰竭组NEU、SII、RDW、RAR水平增加,LYM、ALB水平降低(P<0.05);多因素Logistic回归分析示,SII、RAR水平高是AECOPD患者病情重症或并发呼吸衰竭的独立危险因素;ROC曲线分析示,SII联合RAR预测AECOPD患者病情重症及并发呼吸衰竭的ROC曲线下面积(AUC)分别为0.882(0.806~0.935)、0.908(0.837~0.954),均高于SII、RAR单独预测(P<0.05)。结论 AECOPD患者SII、RAR联合检测可有效评估AECOPD患者病情及呼吸衰竭发生风险。

关键词: 肺疾病, 慢性阻塞性, 急性肺损伤, 呼吸功能不全, 全身免疫炎症指数, 红细胞分布宽度与白蛋白比值

Abstract:

Objective To investigate the relationship between systemic immune-inflammation index (SII), red blood cell distribution width (RDW), albumin (ALB) ratio (RAR) and severity of disease and respiratory failure in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods A total of 110 patients with AECOPD were divided into the severe group (n=37) and the non-severe group (n=73). They were also divided into the respiratory failure group (n=26) and the non-respiratory failure group (n=84) according to whether they had respiratory failure. Platelet count (PLT), neutrophil count (NEU), lymphocyte count (LYM), RDW, ALB, SII and RAR were compared between different groups. Multiple Logistic regression method was used to analyze influencing factors of severe and concurrent respiratory failure. Receiver operating characteristic (ROC) curves were plotted to analyze the predictive value of indicators for severe condition and respiratory failure. Results Compared with the non-severe group, there were increased NEU, SII, RDW and RAR, and decreased PLT and LYM in the severe group (P<0.05). Compared with the non-respiratory failure group, there were increased NEU, SII, RDW and RAR, and decreased LYM and ALB in the respiratory failure group (P<0.05). Multivariate Logistic regression analysis showed that increased SII and RAR were independent risk factors for severe condition or respiratory failure in patients with AECOPD. ROC curves indicated that the area under the curve (AUC) of SII combined with RAR for predicting severe condition and respiratory failure in patients with AECOPD were 0.882 (0.806-0.935) and 0.908 (0.837-0.954), both of which were higher than those of SII or RAR alone (P<0.05). Conclusion Combination of SII and RAR can effectively help to evaluate the condition and the occurrence of respiratory failure in patients with AECOPD.

Key words: pulmonary disease, chronic obstructive, acute lung injury, respiratory insufficiency, systemic immune-inflammation index, red blood cell distribution width to albumin ratio

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