Coronary heart disease in primary care: accuracy of medical history and physical findings in patients with chest pain – a study protocol for a systematic review with individual patient data
1 Department of General Practice/ Family Medicine, University of Marburg, Marburg, D-35032, Germany
2 Universities of Leuven and Hasselt, Interuniversity Institute for Biostatistics and Bioinformatics, Leuven, Belgium
3 Department of General Practice, Katholieke Universities Leuven, Leuven, Belgium
4 Lausanne University Hospital, Lausanne, Switzerland
5 Institute of General Medicine, University of Lausanne, Lausanne, Switzerland
6 Department of General Practice, University of Maastricht, Maastricht, Netherlands
7 Department of Medical and Health Sciences, General Practice, Linköping University, Linköping, Sweden
8 The Dartmouth Institute for Health Policy and Clinical Practice/ , Dartmouth Medical School, Lebanon, USA
Citation and License
BMC Family Practice 2012, 13:81 doi:10.1186/1471-2296-13-81Published: 9 August 2012
Chest pain is a common complaint in primary care, with coronary heart disease (CHD) being the most concerning of many potential causes. Systematic reviews on the sensitivity and specificity of symptoms and signs summarize the evidence about which of them are most useful in making a diagnosis. Previous meta-analyses are dominated by studies of patients referred to specialists. Moreover, as the analysis is typically based on study-level data, the statistical analyses in these reviews are limited while meta-analyses based on individual patient data can provide additional information. Our patient-level meta-analysis has three unique aims. First, we strive to determine the diagnostic accuracy of symptoms and signs for myocardial ischemia in primary care. Second, we investigate associations between study- or patient-level characteristics and measures of diagnostic accuracy. Third, we aim to validate existing clinical prediction rules for diagnosing myocardial ischemia in primary care. This article describes the methods of our study and six prospective studies of primary care patients with chest pain. Later articles will describe the main results.
We will conduct a systematic review and IPD meta-analysis of studies evaluating the diagnostic accuracy of symptoms and signs for diagnosing coronary heart disease in primary care. We will perform bivariate analyses to determine the sensitivity, specificity and likelihood ratios of individual symptoms and signs and multivariate analyses to explore the diagnostic value of an optimal combination of all symptoms and signs based on all data of all studies. We will validate existing clinical prediction rules from each of the included studies by calculating measures of diagnostic accuracy separately by study.
Our study will face several methodological challenges. First, the number of studies will be limited. Second, the investigators of original studies defined some outcomes and predictors differently. Third, the studies did not collect the same standard clinical data set. Fourth, missing data, varying from partly missing to fully missing, will have to be dealt with.
Despite these limitations, we aim to summarize the available evidence regarding the diagnostic accuracy of symptoms and signs for diagnosing CHD in patients presenting with chest pain in primary care.
Centre for Reviews and Dissemination (University of York): CRD42011001170