作者：谷宏宏 ，焦建华 ，马瑞雪 ，曹秀丽 ，李有香 ，李建军

单位：

1.075000河北省张家口市第一医院检验科　2.075000河北省张家口市第一医院老年病二科　3.075000河北省张家口市 第一医院呼吸与危重症医学二科　4.075000河北省张家口市第一医院消化二科

Units：

1.Laboratory Department, Zhangjiakou First Hospital, Zhangjiakou 075000, China 2.Second Department of Geriatrics, Zhangjiakou First Hospital, Zhangjiakou 075000, China 3.Second Department of Respiratory and Critical Care Medicine, Zhangjiakou First Hospital, Zhangjiakou 075000, China 4.Second Department of Gastroenterology, Zhangjiakou First Hospital, Zhangjiakou 075000, China

关键词：

卒中；肺炎；卒中相关性肺炎；可溶性清道夫受体163；降钙素原；高迁移率族蛋白B1

Keywords：

Stroke; Pneumonia; Stroke-associated pneumonia; Soluble cluster differentiation 163; Procalcitonin; High mobility group box 1

CLC：

R 743 R 563.1

DOI：

10.12114/j.issn.1008-5971.2023.00.314

Funds：

河北省医学科学研究课题计划项目（20232072）

摘要：

目的　探讨血清可溶性清道夫受体163（sCD163）、降钙素原（PCT）联合高迁移率族蛋白B1 （HMGB1）在卒中相关性肺炎（SAP）诊断和预后预测中的应用价值。方法　选取2018年7月至2020年12月在张家口 市第一医院住院治疗的SAP患者78例为SAP组，未发生肺炎的急性脑卒中患者78例为非SAP组。收集患者一般资料及血 清sCD163、PCT、HMGB1，根据入院28 d后的肺炎严重指数（PSI）评分将SAP组患者分为预后良好亚组（PSI评分Ⅰ 级，18例）和预后不良亚组（PSI评分Ⅱ～Ⅴ级，60例）。采用多因素Logistic回归分析探讨急性脑卒中患者发生SAP 及SAP患者预后的影响因素；采用ROC曲线分析sCD163、PCT、HMGB1及三者联合对SAP的诊断价值及对SAP患者预 后不良的预测价值。结果　SAP组有慢性阻塞性肺疾病（COPD）史者占比、美国国立卫生研究院卒中量表（NIHSS） 评分、临床肺部感染评分（CPIS）、白细胞计数、sCD163、PCT、HMGB1高于非SAP组（P＜0.05）。多因素Logistic 回归分析结果显示，sCD163、PCT、HMGB1是急性脑卒中患者发生SAP的独立影响因素（P＜0.05）。ROC曲线分析 结果显示，sCD163、PCT、HMGB1及三者联合诊断SAP的AUC分别为0.856、0.888、0.929、0.986。三者联合诊断SAP 的AUC分别大于sCD163、PCT、HMGB1单独诊断SAP的AUC（P＜0.05）。预后不良亚组NIHSS评分、CPIS、白细胞计 数、sCD163、PCT、HMGB1高于预后良好亚组（P＜0.05）。多因素Logistic回归分析结果显示，NIHSS评分、CPIS、 sCD163、PCT、HMGB1是SAP患者预后的独立影响因素（P＜0.05）。ROC曲线分析结果显示，sCD163、PCT、HMGB1 及三者联合预测SAP患者预后不良的AUC分别为0.779、0.841、0.677、0.892。三者联合预测SAP患者预后不良的AUC分 别大于sCD163、PCT、HMGB1单独预测SAP患者预后不良的AUC（P＜0.05）。结论　sCD163、PCT、HMGB1是急性脑 卒中患者发生SAP及SAP患者预后的独立影响因素，且三者联合诊断SAP及预测SAP患者预后不良的价值较高。

Abstract：

Objective To investigate the application value of serum soluble cluster differentiation 163 (sCD163) , procalcitonin (PCT) combined with high mobility group box 1 (HMGB1) in the diagnosis and prognosis prediction of stroke associated pneumonia (SAP) . Methods Seventy-eight patients with SAP admitted to Zhangjiakou First Hospital from July 2018 to December 2020 were selected as the SAP group, and 78 acute stroke patients who did not develop pneumonia were selected as the non-SAP group. General information, serum sCD163, PCT, and HMGB1 of the patients were collected. The patients in the SAP group were divided into good prognosis subgroup [the Pneumonia Severity Index (PSI) score was grade Ⅰ, 18 cases] and poor prognosis subgroup (the PSI score was grade Ⅱ-Ⅴ, 60 cases) according to PSI score at 28 d after admission. Multivariate Logistic regression analysis was used to explore the influencing factors of SAP in patients with acute stroke and prognosis in SAP patients. The ROC curve was used to explore the diagnostic value of sCD163, PCT, HMGB1 and their combination for SAP and predictive value of them for the poor prognosis of SAP patients. Results The proportion of patients with chronic obstructive pulmonary disease (COPD) , National Institute of Health Stroke Scale (NIHSS) score, Clinical Pulmonary Infection Score (CPIS) , white blood cell count, sCD163, PCT, HMGB1 in the SAP group were higher than those in the non-SAP group (P < 0.05) . Multivariate Logistic regression analysis showed that sCD163, PCT, HMGB1 were the independent influencing factors of SAP in patients with acute stroke (P < 0.05) . ROC curve analysis showed that the AUC of the sCD163, PCT, HMGB1 and their combination in the diagnosis of SAP were 0.856, 0.888, 0.929, 0.986, respectively. The AUC of the three combination in the diagnosis of SAP was greater than that of sCD163, PCT, HMGB1 alone (P < 0.05) . The NIHSS score, CPIS, white blood cell count, sCD163, PCT, HMGB1 in the poor prognosis subgroup were higher than those in the good prognosis subgroup (P < 0.05) . Multivariate Logistic regression analysis showed that NIHSS score, CPIS, sCD163, PCT, HMGB1 were the independent influencing factors of prognosis of SAP patients (P < 0.05) . ROC curve analysis showed that the AUC of the sCD163, PCT, HMGB1 and their combination in predicting the poor prognosis of SAP patients were 0.779, 0.841, 0.677, 0.892, respectively. The AUC of the three combination in predicting the poor prognosis of SAP patients was greater than that of sCD163, PCT, HMGB1 alone (P < 0.05) . Conclusion sCD163, PCT, HMGB1 are the independent influencing factors of SAP in patients with acute stroke and prognosis in SAP patients. Their combination has good value for the diagnosis of SAP and prediction of poor prognosis in SAP patients.

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