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Objectives To determine and compare the diagnostic performance of stress myocardial perfusion imaging (MPI) for the diagnosis of obstructive coronary artery disease (CAD), using conventional coronary angiography (CCA) as the reference standard. Methods We searched Medline and Embase for literature that evaluated stress MPI for the diagnosis of obstructive CAD using magnetic resonance imaging (MRI), contrast-enhanced echocardiography (ECHO), single-photon emission computed tomography (SPECT) and positron emission tomography (PET). Results All pooled analyses were based on random effects models. Articles on MRI yielded a total of 2,970 patients from 28 studies, articles on ECHO yielded a sample size of 795 from 10 studies, articles on SPECT yielded 1,323 from 13 studies. For CAD defined as either at least 50 %, at least 70 % or at least 75 % lumen diameter reduction on CCA, the natural logarithms of the diagnostic odds ratio (lnDOR) for MRI (3.63; 95 % CI 3.26–4.00) was significantly higher compared to that of SPECT (2.76; 95 % CI 2.28–3.25; P  = 0.006) and that of ECHO (2.83; 95 % CI 2.29–3.37; P  = 0.02). There was no significant difference between the lnDOR of SPECT and ECHO ( P  = 0.52). Conclusion Our results suggest that MRI is superior for the diagnosis of obstructive CAD compared with ECHO and SPECT. ECHO and SPECT demonstrated similar diagnostic performance. Key Points • MRI can assess myocardial perfusion . • MR perfusion diagnoses coronary artery disease better than echocardiography or SPECT . • Echocardiography and SPECT have similar diagnostic performance . • MRI can save coronary artery disease patients from more invasive tests . • MRI and SPECT show evidence of publication bias, implying possible overestimation .

Objectives To compare the diagnostic performance and radiation exposure of 128-slice dual-source CT coronary angiography (CTCA) protocols to detect coronary stenosis with more than 50 % lumen obstruction. Methods We prospectively included 459 symptomatic patients referred for CTCA. Patients were randomized between high-pitch spiral vs. narrow-window sequential CTCA protocols (heart rate below 65 bpm, group A), or between wide-window sequential vs. retrospective spiral protocols (heart rate above 65 bpm, group B). Diagnostic performance of CTCA was compared with quantitative coronary angiography in 267 patients. Results In group A (231 patients, 146 men, mean heart rate 58 ± 7 bpm), high-pitch spiral CTCA yielded a lower per-segment sensitivity compared to sequential CTCA (89 % vs. 97 %, P  = 0.01). Specificity, PPV and NPV were comparable (95 %, 62 %, 99 % vs. 96 %, 73 %, 100 %, P  > 0.05) but radiation dose was lower (1.16 ± 0.60 vs. 3.82 ± 1.65 mSv, P  < 0.001). In group B (228 patients, 132 men, mean heart rate 75 ± 11 bpm), per-segment sensitivity, specificity, PPV and NPV were comparable (94 %, 95 %, 67 %, 99 % vs. 92 %, 95 %, 66 %, 99 %, P  > 0.05). Radiation dose of sequential CTCA was lower compared to retrospective CTCA (6.12 ± 2.58 vs. 8.13 ± 4.52 mSv, P  < 0.001). Diagnostic performance was comparable in both groups. Conclusion Sequential CTCA should be used in patients with regular heart rates using 128-slice dual-source CT, providing optimal diagnostic accuracy with as low as reasonably achievable (ALARA) radiation dose. Key Points • 128-slice dual-source CT coronary angiography offers several different acquisition protocols. • Randomized comparison of protocols reveals an optimal protocol selection strategy. • Appropriate CTCA protocol selection lowers radiation dose, while maintaining high quality. • CTCA protocol selection should be based on individual patient characteristics. • A prospective sequential protocol is preferred for CTCA.

Objectives: To validate published prediction models for the presence of obstructive coronary artery disease (CAD) in patients with new onset stable typical or atypical angina pectoris and to assess the incremental value of the CT coronary calcium score (CTCS). Methods: We searched the literature for clinical prediction rules for the diagnosis of obstructive CAD, defined as ≥50% stenosis in at least one vessel on conventional coronary angiography. Significant variables were re-analysed in our dataset of 254 patients with logistic regression. CTCS was subsequently included in the models. The area under the receiver operating characteristic curve (AUC) was calculated to assess diagnostic performance. Results: Re-analysing the variables used by Diamond & Forrester yielded an AUC of 0.798, which increased to 0.890 by adding CTCS. For Pryor, Morise 1994, Morise 1997 and Shaw the AUC increased from 0.838 to 0.901, 0.831 to 0.899, 0.840 to 0.898 and 0.833 to 0.899. CTCS significantly improved model performance in each model. Conclusions: Validation demonstrated good diagnostic performance across all models. CTCS improves the prediction of the presence of obstructive CAD, independent of clinical predictors, and should be considered in its diagnostic work-up.

Doc number: O9

Abstract Coronary artery disease (CAD) remains one of the leading causes of morbidity and mortality globally. The most cost-effective imaging strategy to diagnose CAD in patients with stable chest pain is however uncertain. To review the evidence on comparative cost-effectiveness of different imaging strategies for patients presenting with stable chest pain symptoms suggestive for CAD. Systematic review. Studies performing a formal economic evaluation or decision analysis in the English language published between January 1995 and December 2015 were identified using PubMed, Medline (OvidSP), Embase, Web of Science, Cochrane economic evaluations library, and EconLit. Reviews and meta-analyses were excluded. Two independent reviewers assessed titles and abstracts. Of the 4498 titles identified, 70 met our selection criteria. One reviewer used a modified version of the CHEERS checklist to assess study quality. One reviewer extracted data on study details, which were checked by a second reviewer. There is a major heterogeneity between the available cost-effectiveness studies included in this study. The included studies compared very different testing strategies in very different ways and provided mostly short-term results. Strategies of no-testing and xECG were underrepresented. Nonetheless, the findings from this systematic review suggest that for patients with a low to intermediate prior probability of having obstructive CAD, computed tomography coronary angiography (CTCA) may be cost-effective as an initial diagnostic imaging test in comparison with CAG or other non-invasive diagnostic tests. If functional testing is required, stress echocardiography (SE) or single-photon emission computed tomography (SPECT) are suggested to be cost-effective initial strategies in patients with intermediate prior probability of CAD. Yet, other functional testing strategies such as xECG and positron-emission tomography (PET) scanning have not been studied as intensely. Immediate CAG is suggested to be a cost-effective strategy for patients at a high prior probability of having obstructive CAD whom may benefit from revascularization. The study emphasizes the inextricable link between clinical effectiveness and economic efficiency. Evidence suggests that the optimal diagnostic imaging strategy for individuals suspected of having CAD is CTCA for low and intermediate disease probability, followed by SE or SPECT as necessary, and invasive CAG for high disease probability. Further studies are needed to evaluate the cost-effectiveness of alternative non-invasive tests, including a no-testing strategy.

STUDY QUESTION How accurate are prediction models for estimating the pretest probability of obstructive coronary artery disease, and can they be further improved? SUMMARY ANSWER Updated prediction models including age, sex, symptoms, and cardiovascular risk factors estimated the probability of coronary artery disease accurately in low prevalence populations, and improved on current estimates. WHAT IS KNOWN AND WHAT THIS PAPER ADDS Guidelines from the National Institute for Health and Clinical Excellence require physicians to estimate the pretest probability of coronary artery disease in patients with recent onset chest pain. The currently recommended method, the Duke clinical score, overestimates the probability; we updated and validated a prediction model that improves the estimate.

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations.Design Retrospective pooled analysis of individual patient data.Setting 18 hospitals in Europe and the United States.Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively).Main outcome measures Obstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined.Results We included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory.Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates.