4.4 Review

A Systematic Review of Clinical Decision Rules for the Diagnosis of Influenza

期刊

ANNALS OF FAMILY MEDICINE
卷 9, 期 1, 页码 69-77

出版社

ANNALS FAMILY MEDICINE
DOI: 10.1370/afm.1192

关键词

Influenza; clinical decision rule; systematic review; diagnosis; prediction model; decision model; clinical rule

向作者/读者索取更多资源

PURPOSE In this study, we assessed whether multivariate models and clinical decision rules can be used to reliably diagnose influenza. METHODS We conducted a systematic review of MEDLINE, bibliographies of relevant studies, and previous meta-analyses. We searched the literature (1962-2010) for articles evaluating the accuracy of multivariate models, clinical decision rules, or simple heuristics for the diagnosis of influenza. Each author independently reviewed and abstracted data from each article; discrepancies were resolved by consensus discussion. Where possible, we calculated sensitivity, specificity, predictive value, likelihood ratios, and areas under the receiver operating characteristic curve. RESULTS A total of 12 studies met our inclusion criteria. No study prospectively validated a multivariate model or clinical decision rule, and no study performed a split-sample or bootstrap validation of such a model. Simple heuristics such as the so-called fever and cough rule and the fever, cough, and acute onset rule were each evaluated by several studies in populations of adults and children. The areas under the receiver operating characteristic curves were 0.70 and 0.79, respectively. We could not calculate a single summary estimate, however, as the diagnostic threshold varied among studies. CONCLUSIONS The fever and cough, and the fever, cough, and acute onset heuristics have modest accuracy, but summary estimates could not be calculated. Further research is needed to develop and prospectively validate clinical decision rules to identify patients requiring testing, empiric treatment, or neither.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据