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卒中相关性肺炎病原学特点及预后影响因素分析#br#
引用本文:黄兰 王宋平. 卒中相关性肺炎病原学特点及预后影响因素分析#br#[J]. 中国抗生素杂志, 2020, 45(10): 1092-1096
作者姓名:黄兰 王宋平
摘    要:目的 探讨卒中相关性肺炎(SAP)病原菌分布、耐药性特点,并分析SAP预后影响因素,为临床早期干预提供参考。方法 对2013年6月—2019年6月在西南医科大学附属医院诊治的216例SAP患者的痰液检验结果进行回顾性研究,分析其病原菌分布及耐药性特点;并根据患者预后情况分为预后良好组及预后不良组,多因素Logistic回归分析SAP预后影响因素。结果 216例SAP患者痰液标本中共分离出病原菌172株,革兰阴性菌119株,其中铜绿假单胞菌占28.6%(34/119),对左氧氟沙星、亚胺培南耐药率较高,对氨基糖苷类、美罗培南耐药率低;鲍曼/溶血不动杆菌占26.9%(32/119),对头孢菌素类、青霉素类、碳青霉烯类等药物耐药率均大于75%,对替加环素、头孢哌酮钠舒巴坦钠耐药率低;肺炎克雷伯菌占11.8%(14/119),对头孢类耐药率较高,对碳青霉烯类较敏感。革兰阳性菌14株,其中金黄色葡萄球菌占64.3%(9/14),对常用抗生素耐药率高,对万古霉素、利奈唑胺较敏感;肺炎链球菌占35.7%(5/14)株,对多种药物均敏感。真菌39株,白念珠菌占33.3%(13/39)。两组比较年龄、既往脑梗死、基础疾病≥3个、机械通气、低蛋白血症、低钠血症、意识障碍、CURB-65评分、淋巴细胞计数存在统计学差异(P<0.05)。二元Logistic回归分析显示年龄≥75岁(P=0.012)、机械通气(P=0)、低钠血症(P=0.017)、低蛋白血症(P=0)、CURB-65评分≥3分(P=0)与SAP预后不良相关。结论SAP以革兰阴性菌为主,多重耐药现象较常见,临床需根据病原学分布及耐药性特点合理选择抗生素;多种因素与SAP预后相关,应对其进行早期干预,降低病死率。

关 键 词:卒中相关性肺炎  病原学  耐药性  预后  影响因素  

Pathogenic characteristics and analysis of prognostic risk factors of stroke associated pneumonia#br#
Huang Lan and Wang Song-ping. Pathogenic characteristics and analysis of prognostic risk factors of stroke associated pneumonia#br#[J]. Chinese Journal of Antibiotics, 2020, 45(10): 1092-1096
Authors:Huang Lan and Wang Song-ping
Abstract:Objective To investigate the pathogen distribution and drug resistance of stroke associated pneumonia (SAP) and analyze prognostic risk factors of SAP, so as to provide guidance for early clinical intervention. Methods The sputum test results of 216 cases of SAP diagnosed and treated in the Affiliated Hospital of Southwest Medical University from June of 2013 to June of 2019 were retrospectively studied, and their pathogen distribution and drug resistance were analyzed. SAP cases were divided into a good prognosis group and a poor prognosis group, analyzing the prognostic risk factors of SAP by logistic regression analysis. Results A total of 172 pathogenic bacteria were isolated from the sputum specimens of 216 SAP patients, including 119 strains of Gram-negative bacteria. Pseudomonas aeruginosa accounted for 28.6% (34/119), which had high drug resistance to levofloxacin and imipenem, but low drug resistance to aminoglycosides and meropenem; Acinetobacter baumannii accounted for 26.9% (32/119), and the drug resistance rates of cephalosporins, penicillins and carbapenems were more than 75%, low resistance to tigecycline and cefoperazone sodium sulbactam sodium; Klebsiella pneumoniae accounted for 11.8% (14/119), which were resistant to cephalosporins, but sensitive to carbapenems. Among the 14 strains of Gram-positive bacteria, Staphylococcus aureus accounted for 64.3% (9/14), which were resistant to commonly used antibiotics, sensitive to vancomycin and linezolid; Streptococcus pneumoniae accounted for 35.7% (5/14), which were sensitive to a variety of drugs. Among the 39 strains of fungi, Candida albicans accounted for 33.3% (13/39). Univariate analysis showed that the difference of age, previous cerebral infarction, basic disease≥3, mechanical ventilation, hypoproteinemia, hyponatremia, disorder of consciousness, CURB-65 score, and lymphocyte counts were statistically significant. The logistic regression analysis showed that age ≥75 years (P=0.012), mechanical ventilation (P=0), hyponatremia (P=0.017), hypoalbuminemia (P=0), and CURB-65 score (P=0) were independent risk factors of SAP. Conclusion SAP was dominated by Gram-negative bacteria, and multidrug resistance was more and more common. Rational use of antibiotics should be applied according to the etiologic distribution and drug resistance characteristics clinically; a variety of factors were related with the prognosis of SAP, and early intervention was necessary to reduce mortality.
Keywords:Strokeassociated pneumonia  Pathogen distribution  Drug resistance  Prognosis  Prognosticrisk factors  
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