Rationale and Objectives
To determine the accuracy of 64-section coronary computed tomography angiography (CCTA) in predicting 30 day major adverse cardiac events (MACE) for patients presenting with symptoms concerning for acute coronary syndrome (ACS).
Materials and Methods
Electronic databases between January 1, 2005, and May, 1, 2011, and reference lists from relevant published research articles were searched. We included studies on adult patients who presented with active symptoms suggestive of ACS, had immediate 64-section CCTA performed and were assessed for MACE at a minimum of 30 days past their initial presentation. Studies had to report or provide sufficient detail to determine sensitivity, specificity, positive predictive value, and negative predictive value in relation to MACE using a 50% diameter stenosis as cutoff criterion for coronary artery disease.
Results
Nine studies were included for a total of 1559 patients studied (42.3% women, mean age 51.9 ± 10.6). Patients ranged from low to intermediate risk for ACS. All had initial inconclusive electrocardiograms and negative cardiac biomarker results. A total of 14.8% of patients had a positive CCTA result. The pooled sensitivity was 93.3% (95% CI 88.3%–96.6%), specificity was 89.9% (95% CI 88.3%–91.3%), positive predictive value was 48.1% (95% CI 42.5%–53.8%), and negative predictive value was 99.3% (95% CI 98.7%–99.6%).
Conclusion
Sixty-four section CCTA had a 99.3% negative predictive value in excluding MACE for 30 days after initial symptom presentation in 85.2% of our study population. Although the value of 64-section CCTA is best for identifying patients who can safely be discharged home, it is less useful for patients who have positive results.
In 2006, the US prevalence of coronary artery disease (CAD) was 80 million people . Emergency departments (ED) saw more than 6.3 million patients complaining of chest pain and related symptoms and admitted 1.976 million patients into hospitals . More than 65% of these admitted patients were ultimately not found to have an acute coronary syndrome (ACS) , resulting in an estimated loss of $6–8 billion per year to the US health care system . Detecting ACS in patients with symptoms such as chest, back and arm pain, shortness of breath, nausea, and weakness is challenging. High-risk patients are appropriately admitted into the hospital and very low-risk patients are discharged to home. But the patients with some risk of ACS—those without diagnostic electrocardiogram (ECG) changes or cardiac biomarkers—are more difficult to disposition.
There have been numerous studies attempting to accurately risk-stratify patients but no single test has reliably proven to be >99% accurate in large numbers to exclude ACS in symptomatic patients . This may partially explain the estimated 2%–5% rate of missed ACS in the ED . A highly accurate diagnostic test that can exclude ACS could potentially save the US health care system billions of dollars. Coronary computed tomography angiography (CCTA) has emerged in recent years as a test that may be able to reliably exclude ACS. Using this technology, there have been many studies examining 64-section CCTA and correlating the findings to invasive coronary angiography (ICA) . Several systematic reviews and meta-analyses correlated CCTA with ICA but none of them focused on immediate CCTA for patients with acute symptoms . Although ICA is considered the gold standard for detecting CAD, it is not practical for widespread use in undifferentiated chest pain patients: it is not routinely available in most acute settings, it would not likely improve the outcome of the majority of patients and it carries a risk of major complications. A more practical approach may be noninvasive CCTA, which correlates well with ICA. Patients found to have mild to no CAD on ICA have been shown to have good long survival rates and can presumably be safely discharged from an ED.
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Materials and methods
Search Strategy
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Selection of Studies
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Data Extraction/Collection and Processing
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Quality Assessment
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Outcome Measures
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Primary Data Analyses
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Results
Quantitative Analysis
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Table 1
Study Characteristics
Author No. Patients for Meta-analysis Patient Population (ACS Risk Criterion) Age (Year ± SD) % Men % White Triple Rule-out Study MACE Follow-up (Months) Johnson et al, 2007 55 Low to intermediate risk 67 ± 10 64 NR Yes 5 Gallagher et al, 2007 85 ∗ Low risk (Goldman, Reilly criteria) 49 ± 11 53 NR No 1 Rubinshtein et al, 2007 58 Intermediate risk (ACC/AHA guideline risk groups) 56 ± 10 64 NR No 15 Johnson et al, 2008 109 Low to intermediate risk 63 ± 14 72 NR Yes 6 Takakuwa et al, 2008 197 Low to intermediate risk (TIMI) 49 ± 11 45 46 Yes 1 Ueno et al, 2009 36 Included some high risk 66 ± 12 53 NR No 1 Hollander et al, 2009 562 † Low risk (TIMI) 47 ± 9 44 26 No 1 Hoffman et al, 2009 368 Low to intermediate risk 53 ± 12 61 85 No 6 Hansen et al, 2010 89 Low to intermediate risk 56 ± 9 63 NR No 12
ACC, American College of Cardiology; ACS, acute coronary syndrome; AHA, American Heart Association; MACE, major adverse cardiac events; NR, not reported; TIMI, Thrombolysis in Myocardial Infarction risk scores.
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Table 2
Individual Study Results
Author True Positive True Negative False Positive False Negative Johnson et al, 2007 16 35 3 1 Gallagher et al, 2007 6 72 6 1 Rubinshtein et al, 2007 20 35 3 0 Johnson et al, 2008 13 96 0 0 Takakuwa et al, 2008 6 174 16 1 Ueno et al, 2009 11 20 4 1 Hollander et al, 2009 7 508 47 0 Hoffman et al, 2009 24 293 44 7 Hansen et al, 2010 3 85 1 0
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Qualitative Analysis
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Discussion
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Conclusions
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Limitations
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