天津医药 ›› 2025, Vol. 53 ›› Issue (2): 170-175.doi: 10.11958/20241377

• 临床研究 • 上一篇    下一篇

PIV、HCAR、PCT/PLT在老年COPD肺部感染中的应用价值

张小庆(), 赵慧霞(), 曹鄂洪, 张连霞, 宫秀娟   

  1. 东南大学医学院附属南京同仁医院呼吸内科(邮编211000)
  • 收稿日期:2024-09-20 修回日期:2024-11-20 出版日期:2025-02-15 发布日期:2025-02-26
  • 通讯作者: E-mail:152089413@qq.com
  • 作者简介:张小庆(1992),女,主治医师,主要从事慢性阻塞性肺疾病、肺部感染方面研究。E-mail:1362466122@qq.com

Application value of PIV, HCAR and PCT/PLT in pulmonary infection in elderly patients with COPD

ZHANG Xiaoqing(), ZHAO Huixia(), CAO Ehong, ZHANG Lianxia, GONG Xiujuan   

  1. Department of Respiratory Medicine, the Affiliated Nanjing Tongren Hospital of Southeast University Medical College, Nanjing 211000, China
  • Received:2024-09-20 Revised:2024-11-20 Published:2025-02-15 Online:2025-02-26
  • Contact: E-mail:152089413@qq.com

摘要:

目的 探究泛免疫炎症值(PIV)、超敏C反应蛋白(hs-CRP)/白蛋白(ALB)比值(HCAR)、降钙素原/血小板计数比值(PCT/PLT)在老年慢性阻塞性肺疾病(COPD)肺部感染患者中的应用价值。方法 选取143例老年COPD伴肺部细菌感染患者为感染组,另选取同期就诊的143例老年COPD不伴肺部细菌感染患者作为未感染组。另依据感染程度将感染组分为轻度组47例、中度组51例和重度组45例;依预后情况分为预后良好组112例和预后不佳组31例。比较各组血生化指标、PIV、HCAR及PCT/PLT水平,分析上述指标与肺部感染、感染程度及预后的关系。结果 感染组中性粒细胞(NEU)、单核细胞(MON)、hs-CRP、PCT水平高于未感染组,淋巴细胞(LYM)、ALB水平低于未感染组(P<0.05);感染组、预后不佳组PIV、HCAR、PCT/PLT水平分别高于未感染组、预后良好组(P<0.05);轻度组、中度组、重度组PIV、HCAR及PCT/PLT水平依次升高(P<0.05)。Spearman相关性分析显示,PIV、HCAR及PCT/PLT均与肺部感染程度呈正相关(P<0.05)。多因素Logistic回归分析显示,高水平PIV、HCAR及PCT/PLT是老年COPD患者发生肺部感染的独立危险因素(P<0.05),亦是肺部感染患者预后不佳的独立危险因素(P<0.05)。PIV、HCAR及PCT/PLT三指标联合诊断老年COPD肺部感染及患者预后不佳的曲线下面积(AUC)分别为0.980和0.910(P<0.05)。结论 PIV、HCAR及PCT/PLT与老年COPD伴肺部感染有关,有助于识别肺部感染、判断肺部感染病情及评估患者预后。

关键词: 肺疾病, 慢性阻塞性, 感染, ROC曲线, 血小板计数, 泛免疫炎症值, 降钙素原

Abstract:

Objective To investigate the application value of pan-immune-inflammation value (PIV), hypersensitive C-reactive protein (hs-CRP)/albumin (ALB) ratio (HCAR) and procalcitonin/platelet count ratio (PCT/PLT) in pulmonary infection in elderly patients with chronic obstructive pulmonary disease (COPD). Methods A total of 143 elderly patients with COPD and pulmonary bacterial infection were selected as the infected group. Meanwhile, 143 elderly patients with COPD and without pulmonary infection were selected as the uninfected group. Patients in the infected group were furthrer divided into the mild group (47 cases), the moderate group (51 cases) and the severe group (45 cases) according to the degree of pulmonary infection. They were divided into the favorable prognosis group (112 cases) and the poor prognosis group (31 cases) according to the prognosis. Blood biochemical indicators, PIV, HCAR and PCT/PLT were compared between groups. The relationship between above indicators and pulmonary infection, infection degree and the prognosis was analyzed. Results Compared with the uninfected group, neutrophil (NEU), monocyte (MON), hs-CRP and PCT levels were higher, while lymphocyte (LYM) and ALB levels were lower in the infected group (P<0.05). PIV, HCAR and PCT/PLT were higher in the infected group and the poor prognosis group than those in the uninfected group and the favorable prognosis group, respectively (P<0.05). PIV, HCAR and PCT/PLT in the mild group, the moderate group and the severe group increased in sequence (P<0.05). Spearman correlation analysis showed that PIV, HCAR and PCT/PLT were positively correlated with the degree of pulmonary infection (P<0.05). Multivariate Logistic regression analysis showed that high levels of PIV, HCAR and PCT/PLT were independent risk factors for pulmonary infection in elderly patients with COPD (P<0.05), and also independent risk factors for poor prognosis in patients with pulmonary infection (P<0.05). The areas under the curve (AUC) of PIV combined with HCAR and PCT/PLT for diagnosing pulmonary infection in elderly patients with COPD and predicting poor prognosis in patients with pulmonary infection were 0.980 and 0.910 (P<0.05). Conclusion PIV, HCAR and PCT/PLT are related to COPD with pulmonary infection in the elderly. They can help to identify pulmonary infection, judge the condition of pulmonary infection and evaluate the prognosis in patients with pulmonary infection.

Key words: pulmonary disease, chronic obstructive, infections, ROC curve, platelet count, pan-immune inflammatory value, procalcitonin

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