Clinical pre-test probability for obstructive coronary artery disease: insights from the European DISCHARGE pilot study
Jazyk angličtina Země Německo Médium print-electronic
Typ dokumentu klinické zkoušky, časopisecké články
Grantová podpora
EC-GA 603266
FP7 Ideas: European Research Council
PubMed
32902743
PubMed Central
PMC7880945
DOI
10.1007/s00330-020-07175-z
PII: 10.1007/s00330-020-07175-z
Knihovny.cz E-zdroje
- Klíčová slova
- Computed tomography angiography, Coronary artery disease, Prevalence, Probability of disease,
- MeSH
- CT angiografie MeSH
- hodnocení rizik MeSH
- koronární angiografie MeSH
- koronární stenóza * diagnostické zobrazování epidemiologie MeSH
- lidé MeSH
- nemoci koronárních tepen * diagnostické zobrazování epidemiologie MeSH
- pilotní projekty MeSH
- prediktivní hodnota testů MeSH
- propuštění pacienta MeSH
- rizikové faktory MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- klinické zkoušky MeSH
- Geografické názvy
- Evropa MeSH
OBJECTIVES: To test the accuracy of clinical pre-test probability (PTP) for prediction of obstructive coronary artery disease (CAD) in a pan-European setting. METHODS: Patients with suspected CAD and stable chest pain who were clinically referred for invasive coronary angiography (ICA) or computed tomography (CT) were included by clinical sites participating in the pilot study of the European multi-centre DISCHARGE trial. PTP of CAD was determined using the Diamond-Forrester (D+F) prediction model initially introduced in 1979 and the updated D+F model from 2011. Obstructive coronary artery disease (CAD) was defined by one at least 50% diameter coronary stenosis by both CT and ICA. RESULTS: In total, 1440 patients (654 female, 786 male) were included at 25 clinical sites from May 2014 until July 2017. Of these patients, 725 underwent CT, while 715 underwent ICA. Both prediction models overestimated the prevalence of obstructive CAD (31.7%, 456 of 1440 patients, PTP: initial D+F 58.9% (28.1-90.6%), updated D+F 47.3% (34.2-59.9%), both p < 0.001), but overestimation of disease prevalence was higher for the initial D+F (p < 0.001). The discriminative ability was higher for the updated D+F 2011 (AUC of 0.73 95% confidence interval [CI] 0.70-0.76 versus AUC of 0.70 CI 0.67-0.73 for the initial D+F; p < 0.001; odds ratio (or) 1.55 CI 1.29-1.86, net reclassification index 0.11 CI 0.05-0.16, p < 0.001). CONCLUSIONS: Clinical PTP calculation using the initial and updated D+F prediction models relevantly overestimates the actual prevalence of obstructive CAD in patients with stable chest pain clinically referred for ICA and CT suggesting that further refinements to improve clinical decision-making are needed. TRIAL REGISTRATION: https://www.clinicaltrials.gov/ct2/show/NCT02400229 KEY POINTS: • Clinical pre-test probability calculation using the initial and updated D+F model overestimates the prevalence of obstructive CAD identified by ICA and CT. • Overestimation of disease prevalence is higher for the initial D+F compared with the updated D+F. • Diagnostic accuracy of PTP assessment varies strongly between different clinical sites throughout Europe.
Berlin School of Public Health Berlin Berlin Germany
Centro de Investigación Biomédica en Red CV CIBER CV Barcelona Spain
Charité Universitätsmedizin Berlin Department of Radiology Berlin Institute of Health Berlin Germany
Department of Cardiology Aintree University Hospital Liverpool UK
Department of Cardiology ALB FILS KLINIKEN Goeppingen Germany
Department of Cardiology and Radiology Rigshospitalet University of Copenhagen Copenhagen Denmark
Department of Cardiology Basurto University Hospital Bilbao Bilbao Spain
Department of Cardiology Cardio Med Medical Center Targu Mures Târgu Mureș Romania
Department of Cardiology Centro Hospitalar de Vila Nova de Gaia Vila Nova de Gaia Portugal
Department of Cardiology Lithuanian University of Health Sciences Kaunas Lithuania
Department of Cardiology Southeastern Health and Social Care Trust Belfast Ireland
Department of Cardiology Wojewodzki Szpital Specjalistyczny We Wroclawiu Wrocław Poland
Department of Radiology and Department of Cardiology Medical University Innsbruck Innsbruck Austria
Department of Radiology Azienda Ospedaliero Universitaria di Cagliari Cagliari Italy
Department of Radiology Medical Imaging Centre Semmelweis University Budapest Hungary
Dept of Coronary and Structural Heart Diseases Institute of Cardiology Warsaw Poland
DZHK partner site Berlin Germany
Institute of Cardiovascular and Medical Sciences Glasgow University Glasgow UK
Latvian Centre of Cardiology Pauls Stradins Clinical University Hospital Riga Latvia
Royal Liverpool and Broadgreen University Hospital Liverpool UK
Turku PET Centre and Heart Centre Turku University Hospital Turku Finland
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Pryor DB, Shaw L, McCants CB, et al. Value of the history and physical in identifying patients at increased risk for coronary artery disease. Ann Intern Med. 1993;118:81–90. doi: 10.7326/0003-4819-118-2-199301150-00001. PubMed DOI
Almdahl SM, Veel T, Halvorsen P, Rynning SE. Immediate rescue operations after failed diagnostic or therapeutic cardiac catheterization procedures. Interact Cardiovasc Thorac Surg. 2013;17:314–317. doi: 10.1093/icvts/ivt214. PubMed DOI PMC
Shimony A, Joseph L, Mottillo S, Eisenberg MJ. Coronary artery perforation during percutaneous coronary intervention: a systematic review and meta-analysis. Can J Cardiol. 2011;27:843–850. doi: 10.1016/j.cjca.2011.04.014. PubMed DOI
Moscariello A, Vliegenthart R, Schoepf UJ, et al. Coronary CT angiography versus conventional cardiac angiography for therapeutic decision making in patients with high likelihood of coronary artery disease. Radiology. 2012;265:385–392. doi: 10.1148/radiol.12112426. PubMed DOI
Williams MC, Hunter A, Shah ASV, et al. Use of coronary computed tomographic angiography to guide management of patients with coronary disease. J Am Coll Cardiol. 2016;67:1759–1768. doi: 10.1016/j.jacc.2016.02.026. PubMed DOI PMC
Dewey M, Rief M, Martus P, et al. Evaluation of computed tomography in patients with atypical angina or chest pain clinically referred for invasive coronary angiography: randomised controlled trial. BMJ. 2016;355:i5441. doi: 10.1136/bmj.i5441. PubMed DOI PMC
Pugliese F, Mollet NR, Runza G, et al. Diagnostic accuracy of non-invasive 64-slice CT coronary angiography in patients with stable angina pectoris. Eur Radiol. 2006;16:575–582. doi: 10.1007/s00330-005-0041-0. PubMed DOI
Dharampal AS, Papadopoulou SL, Rossi A, et al. Computed tomography coronary angiography accuracy in women and men at low to intermediate risk of coronary artery disease. Eur Radiol. 2012;22:2415–2423. doi: 10.1007/s00330-012-2503-5. PubMed DOI PMC
Pryor DB, Harrell FE, Jr, Lee KL, Califf RM, Rosati RA. Estimating the likelihood of significant coronary artery disease. Am J Med. 1983;75:771–780. doi: 10.1016/0002-9343(83)90406-0. PubMed DOI
Montalescot G, Sechtem U, Achenbach S, et al. 2013 ESC guidelines on the management of stable coronary artery disease: the Task Force on the management of stable coronary artery disease of the European Society of Cardiology. Eur Heart J. 2013;34:2949–3003. doi: 10.1093/eurheartj/eht310.P4876. PubMed DOI
Moschovitis A, Cook S, Meier B. Percutaneous coronary interventions in Europe in 2006. EuroIntervention. 2010;6:189–194. doi: 10.4244/EIJV6I2A31. PubMed DOI
Knuuti J, Ballo H, Juarez-Orozco LE, et al. The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: a meta-analysis focused on post-test disease probability. Eur Heart J. 2018;39:3322–3330. doi: 10.1093/eurheartj/ehy267. PubMed DOI
Diamond GA, Forrester JS. Analysis of probability as an aid in the clinical diagnosis of coronary-artery disease. N Engl J Med. 1979;300:1350–1358. doi: 10.1056/NEJM197906143002402. PubMed DOI
Cheng VY, Berman DS, Rozanski A, et al. Performance of the traditional age, sex, and angina typicality-based approach for estimating pretest probability of angiographically significant coronary artery disease in patients undergoing coronary computed tomographic angiography: results from the multinational coronary CT angiography evaluation for clinical outcomes: an international multicenter registry (CONFIRM) Circulation. 2011;124(2423-2432):2421–2428. PubMed PMC
Zhou J, Liu Y, Huang L, et al. Validation and comparison of four models to calculate pretest probability of obstructive coronary artery disease in a Chinese population: a coronary computed tomographic angiography study. J Cardiovasc Comput Tomogr. 2017;11:317–323. doi: 10.1016/j.jcct.2017.05.004. PubMed DOI
Genders TS, Steyerberg EW, Alkadhi H, et al. A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension. Eur Heart J. 2011;32:1316–1330. doi: 10.1093/eurheartj/ehr014. PubMed DOI
(1994) Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). Lancet 344:1383–1389 PubMed
Napp AE, Haase R, Laule M, et al. Computed tomography versus invasive coronary angiography: design and methods of the pragmatic randomised multicentre DISCHARGE trial. Eur Radiol. 2017;27:2957–2968. doi: 10.1007/s00330-016-4620-z. PubMed DOI
Zimmermann E, Germershausen C, Greupner J, et al. Improvement of skills and knowledge by a hands-on cardiac CT course: before and after evaluation with a validated questionnaire and self-assessment. Rofo. 2010;182:589–593. doi: 10.1055/s-0028-1109950. PubMed DOI
Diamond GA. A clinically relevant classification of chest discomfort. J Am Coll Cardiol. 1983;1:574–575. doi: 10.1016/S0735-1097(83)80093-X. PubMed DOI
Team RC (2017) R: A language and environment for statistical computing. https://www.R-project.org
Eagle KA. Medical decision making in patients with chest pain. N Engl J Med. 1991;324:1282–1283. doi: 10.1056/NEJM199105023241811. PubMed DOI
Adamson PD, Newby DE, Hill CL, Coles A, Douglas PS, Fordyce CB (2018) Comparison of international guidelines for assessment of suspected stable angina: insights from the PROMISE and SCOT-HEART. JACC Cardiovasc Imaging 11:1301–1310 PubMed PMC
Wasfy MM, Brady TJ, Abbara S, et al. Comparison of the Diamond-Forrester method and Duke Clinical Score to predict obstructive coronary artery disease by computed tomographic angiography. Am J Cardiol. 2012;109:998–1004. doi: 10.1016/j.amjcard.2011.11.028. PubMed DOI
Baskaran L, Danad I, Gransar H et al (2018) A comparison of the updated Diamond-Forrester, CAD consortium, and CONFIRM history-based risk scores for predicting obstructive coronary artery disease in patients with stable chest pain: the SCOT-HEART Coronary CTA Cohort. JACC Cardiovasc Imaging. 10.1016/j.jcmg.2018.02.020 PubMed
Foldyna B, Udelson JE, Karady J et al (2018) Pretest probability for patients with suspected obstructive coronary artery disease: re-evaluating Diamond-Forrester for the contemporary era and clinical implications: insights from the PROMISE trial. Eur Heart J Cardiovasc Imaging. 10.1093/ehjci/jey182 PubMed PMC
Schuetz GM, Zacharopoulou NM, Schlattmann P, Dewey M. Meta-analysis: noninvasive coronary angiography using computed tomography versus magnetic resonance imaging. Ann Intern Med. 2010;152:167–177. doi: 10.7326/0003-4819-152-3-201002020-00008. PubMed DOI
ClinicalTrials.gov
NCT02400229