Abstract
BackgroundChest 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.Methods/DesignWe 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.DiscussionOur 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.Review registrationCentre for Reviews and Dissemination (University of York): CRD42011001170
Highlights
Chest pain is a common complaint in primary care, with coronary heart disease (CHD) being the most concerning of many potential causes
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
Systematic reviews on the accuracy of diagnostic tests with subsequent meta-analysis of the measures of diagnostic accuracy can play an important role in decision making
Summary
Chest pain is a common complaint in primary care, with coronary heart disease (CHD) being the most concerning of many potential causes. In unselected patients presenting with chest pain in primary care, the overall prevalence of coronary heart disease is between 12.8 and 14.6% [2,3]. Patients with CHD often present in the early stages of their disease, often with uncharacteristic clinical findings that make the separation from other etiologies difficult. PCPs must reliably identify serious cardiac disease while protecting patients from unnecessary testing and hospital admissions They must rely on the history, physical findings, and their accumulated knowledge of an individual patient to determine the clinical probability of CHD and decide whether testing, specialist referral or hospital admission is indicated. Tests ( i.e. troponin levels, and the electrocardiogram) lack sensitivity in the early stages of myocardial infarction (MI) and cannot exclude acute ischemia in patients with a high clinical probability. The optimal early evaluation of possible CHD uses the patient’s clinical probability in order to decide on the value of further testing and to interpret test results using probabilistic reasoning, a form of thinking that many physicians do not use [4]
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