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慢性阻塞性肺疾病急性加重期细菌病因的预测模型。

A prediction model for bacterial etiology in acute exacerbations of COPD.

作者信息

Lode H, Allewelt M, Balk S, De Roux A, Mauch H, Niederman M, Schmidt-Ioanas M

机构信息

Helios Klinikum Emil von Behring, affiliated Free University Berlin, Chest Hospital Heckeshorn (Infectious Disease and Immunology), Zum Heckeshorn 33, 14109, Berlin, Germany.

出版信息

Infection. 2007 Jun;35(3):143-9. doi: 10.1007/s15010-007-6078-z.

Abstract

OBJECTIVES

Bacteria play a leading role in acute exacerbations of chronic obstructive pulmonary disease (COPD), but we lack predictors of bacterial etiology. We developed a prediction model for infection with gram-negative enteric bacteria (GNEB) and Pseudomonas aeruginosa.

METHODS

Clinical presentation, sputum characteristics, microbial sputum patterns, lung function and previous and concomitant medication were prospectively recorded in patients with moderate to severe exacerbation of COPD. Risk factors for a specific bacterial etiology were calculated and a prediction model developed.

RESULTS

A total of 193 patients with acute exacerbation were included. In 121 (62.6%) of them a microbial etiology could be identified, most frequently Haemophilus influenzae (32 strains), Streptococcus pneumoniae (22 strains) and P. aeruginosa (12 strains). Multivariate analysis identified severe airflow obstruction and use of systemic steroids as predictors for exacerbation due to gram-negative enteric bacilli and P. aeruginosa. A prediction model including FEV1 < 35% of predicted value, systemic steroid use and prior antibiotic therapy within preceeding 3 months had a negative predictive of 89%, being a helpful tool in excluding patients at risk of exacerbation due to gram-negative enteric bacilli and P. aeruginosa when all criteria are absent.

CONCLUSION

A simple prediction model based on three factors may identify COPD patients at low risk for exacerbations with gram-negative enteric bacilli and P. aeruginosa. Bacterial Etiology in COPD Exacerbations.

摘要

目的

细菌在慢性阻塞性肺疾病(COPD)急性加重中起主导作用,但我们缺乏细菌病因的预测指标。我们开发了一种针对革兰氏阴性肠道细菌(GNEB)和铜绿假单胞菌感染的预测模型。

方法

前瞻性记录中重度COPD急性加重患者的临床表现、痰液特征、痰液微生物模式、肺功能以及既往和同时使用的药物。计算特定细菌病因的危险因素并开发预测模型。

结果

共纳入193例急性加重患者。其中121例(62.6%)可确定微生物病因,最常见的是流感嗜血杆菌(32株)、肺炎链球菌(22株)和铜绿假单胞菌(12株)。多因素分析确定严重气流受限和全身使用类固醇是革兰氏阴性肠道杆菌和铜绿假单胞菌所致急性加重的预测指标。一个包含FEV1<预测值的35%、全身使用类固醇以及前3个月内曾使用抗生素治疗的预测模型,其阴性预测值为89%,当所有标准均不存在时,是排除革兰氏阴性肠道杆菌和铜绿假单胞菌所致急性加重风险患者的有用工具。

结论

基于三个因素的简单预测模型可识别革兰氏阴性肠道杆菌和铜绿假单胞菌所致急性加重风险较低的COPD患者。COPD急性加重中的细菌病因。

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