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中华临床医师杂志(电子版) ›› 2022, Vol. 16 ›› Issue (06) : 524 -528. doi: 10.3877/cma.j.issn.1674-0785.2022.06.011

所属专题: 急危重症

临床研究

呼吸重症监护病房院内获得性肺炎病原学特点及多因素Logistic回归分析
高磊1, 赵卉1,(), 郑凌1, 叶静1   
  1. 1. 230601 安徽合肥,安徽医科大学第二附属医院呼吸与危重症医学科
  • 收稿日期:2021-10-28 出版日期:2022-06-15
  • 通信作者: 赵卉
  • 基金资助:
    安徽医科大学校青年科学基金(2021xkj045)

Etiological characteristics and risk factors of hospital-acquired pneumonia in respiratory intensive care unit

Lei Gao1, Hui Zhao1,(), Ling Zheng1, Jing Ye1   

  1. 1. Department of Pulmonary and Critical Care Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
  • Received:2021-10-28 Published:2022-06-15
  • Corresponding author: Hui Zhao
引用本文:

高磊, 赵卉, 郑凌, 叶静. 呼吸重症监护病房院内获得性肺炎病原学特点及多因素Logistic回归分析[J/OL]. 中华临床医师杂志(电子版), 2022, 16(06): 524-528.

Lei Gao, Hui Zhao, Ling Zheng, Jing Ye. Etiological characteristics and risk factors of hospital-acquired pneumonia in respiratory intensive care unit[J/OL]. Chinese Journal of Clinicians(Electronic Edition), 2022, 16(06): 524-528.

目的

探讨呼吸重症监护病房(RICU)院内获得性肺炎(HAP)病原学特点及多因素Logistic回归分析。

方法

选择安徽医科大学第二附属医院于2018年3月至2021年8月入住RICU病房患者160例,并发HAP患者54例。分离培养HAP患者病原菌,采用微生物鉴定系统分离鉴定病原菌;采用纸片法进行药敏试验。采用单因素分析影响HAP相关因素;采用多因素Logistic回归分析影响HAP独立危险因素。

结果

HAP感染患者54例中,分离病原菌81株,其中革兰氏阴性菌62株,革兰氏阳性菌6株,真菌13株。肺炎克雷伯杆菌对头孢他啶(85.19%)和头孢唑啉(77.78%)耐药率较高;铜绿假单胞菌对头孢他啶(94.74%)和头孢哌酮/舒巴坦(78.95%)耐药率较高。经单因素分析显示,HAP组与无HAP组性别、体质量指数、吸烟史和高血压史比较差异无统计学意义(P>0.05);HAP组与无HAP组年龄、糖尿病史、机械通气时间、口腔清洁状况、白蛋白水平、合并肺内疾病、住院时间和广谱抗生素应用比较差异具有统计学意义(P<0.05)。将上述单因素分析具有统计学差异的纳入多因素Logistic回归分析显示,年龄>70岁、机械通气时间>7 d、糖尿病史、口腔清洁状况、白蛋白<30 g/L、合并肺内疾病、住院时间和广谱抗生素应用为影响RICU的HAP患者独立危险因素。

结论

RICU的HAP患者病原菌以革兰氏阴性菌为主,其中年龄、机械通气时间、糖尿病史、口腔清洁状况、白蛋白水平、合并肺内疾病、住院时间和广谱抗生素应用为影响RICU的HAP患者独立危险因素。

Objective

To investigate the etiological characteristics and risk factors of hospital acquired pneumonia (HAP) in respiratory intensive care unit (RICU).

Methods

One hundred and sixty patients admitted to the RICU of Second Affiliated Hospital of Anhui Medical University from March 2018 to August 2021, and 54 patients complicated with HAP were selected. The pathogenic bacteria of HAP were isolated and identified using the microbial identification system. The paper method was used to test drug sensitivity. Univariate analysis was used to identify the influencing factors of HAP. Multivariate Logistic regression was used to identify the independent risk factors for HAP.

Results

Among the 54 HAP patients, 81 strains of pathogenic bacteria were isolated, including 62 Gram-negative bacteria, 6 Gram-positive bacteria, and 13 fungi. The drug resistance rates of Klebsiella pneumoniae to ceftazidime (85.19%) and cefazolin (77.78%) were high. Pseudomonas aeruginosa had high resistance rates to ceftazidime (94.74%) and cefoperazone/sulbactam (78.95%). Univariate analysis showed that there were no significant differences in gender, body mass index, smoking history, or hypertension history between the HAP group and non-HAP group (P>0.05), but there were statistically significant differences in age, diabetes history, mechanical ventilation time, oral cleanliness, albumin level, pulmonary disease, hospital stay, and broad-spectrum antibiotic application between the two groups (P<0.05). Multivariate Logistic regression analysis showed that age>70 years, mechanical ventilation time>7 d, history of diabetes mellitus, oral cleanliness, albumin<30 g/L, pulmonary disease, length of hospital stay, and broad-spectrum antibiotic use were the independent risk factors for HAP among RICU patients.

Conclusion

Gram-negative bacteria are the main pathogenic bacteria of HAP among RICU patients. Age, mechanical ventilation time, diabetes history, oral cleanliness, albumin level, pulmonary disease, hospital stay, and broad-spectrum antibiotic use are the independent risk factors for HAP among RICU patients.

表1 院内AP患者病原菌分布情况
表2 主要病原菌耐药情况
表3 单因素分析影响HAP相关因素
表4 多因素Logistic回归分析影响HAP独立危险因素
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