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铜绿假单胞菌感染囊性纤维化患者:临床影响、诊断和治疗的科学证据。

Pseudomonas aeruginosa infection in patients with cystic fibrosis: scientific evidence regarding clinical impact, diagnosis, and treatment.

机构信息

Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Instituto da Criança, São PauloSP, Brasil.

出版信息

J Bras Pneumol. 2013 Jun-Aug;39(4):495-512. doi: 10.1590/S1806-37132013000400015.

Abstract

Evidence-based techniques have been increasingly used in the creation of clinical guidelines and the development of recommendations for medical practice. The use of levels of evidence allows the reader to identify the quality of scientific information that supports the recommendations made by experts. The objective of this review was to address current concepts related to the clinical impact, diagnosis, and treatment of Pseudomonas aeruginosa infections in patients with cystic fibrosis. For the preparation of this review, the authors defined a group of questions that would be answered in accordance with the principles of PICO-an acronym based on questions regarding the Patients of interest, Intervention being studied, Comparison of the intervention, and Outcome of interest. For each question, a structured review of the literature was performed using the Medline database in order to identify the studies with the methodological design most appropriate to answering the question. The questions were designed so that each of the authors could write a response. A first draft was prepared and discussed by the group. Recommendations were then made on the basis of the level of scientific evidence, in accordance with the classification system devised by the Oxford Centre for Evidence-Based Medicine, as well as the level of agreement among the members of the group.

摘要

循证技术已越来越多地应用于临床指南的制定和医疗实践建议的制定。使用证据级别可以让读者识别出支持专家建议的科学信息的质量。本综述的目的是解决当前与囊性纤维化患者铜绿假单胞菌感染的临床影响、诊断和治疗相关的概念。为了编写本综述,作者定义了一组问题,这些问题将根据 PICO 原则(基于患者、干预措施、干预比较和感兴趣的结果的问题的缩写)来回答。对于每个问题,使用 Medline 数据库进行了文献的结构化综述,以确定最适合回答问题的方法学设计的研究。问题的设计使得每个作者都可以写一个回复。然后根据科学证据的水平,并根据牛津循证医学中心制定的分类系统,以及小组成员之间的一致性水平,提出建议。

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