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Optimized prognostic score for coronary computed tomographic angiography results from the confirm registry (COronary CT Angiography EvaluatioNFor Clinical Outcomes: An InteRnational Multicenter Registry)


Hadamitzky, Martin; Achenbach, Stephan; Al-Mallah, Mouaz; Berman, Daniel; Budoff, Matthew; Cademartiri, Filippo; Callister, Tracy; Chang, Hyuk-Jae; Cheng, Victor; Chinnaiyan, Kavitha; Chow, Benjamin J W; Cury, Ricardo; Delago, Augustin; Dunning, Allison; Feuchtner, Gudrun; Gomez, Millie; Kaufmann, Philipp; Kim, Yong-Jin; Leipsic, Jonathon; Lin, Fay Y; Maffei, Erica; Min, James K; Raff, Gil; Shaw, Leslee J; Villines, Todd C; Hausleiter, Jörg (2013). Optimized prognostic score for coronary computed tomographic angiography results from the confirm registry (COronary CT Angiography EvaluatioNFor Clinical Outcomes: An InteRnational Multicenter Registry). Journal of the American College of Cardiology, 62(5):468-476.

Abstract

OBJECTIVE: to analyze the predictive value of coronary CT angiography and to model and validate an optimized score for prognosis of 2-year survival based on a patient population with suspected coronary artery disease (CAD). BACKGROUND: Coronary CT angiography (CCTA) carries important prognostic information in addition to the detection of obstructive coronary artery disease. But it is still unclear how the results of CCTA should be interpreted in the context of clinical risk predictors METHODS: The analysis is based on a test sample of 17,793 patients and a validation sample of 2,506 patients, all with suspected CAD, from the international CONFIRM registry. Based on CCTA data and clinical risk scores, an optimized score was modeled. The endpoint was all cause mortality. RESULTS: During a median follow-up of 2.3 years, 347 patients died. Best CCTA parameter for prediction of mortality was the number of proximal segments with mixed or calcified plaques (C-index 0.64, p<0.0001) and the number of proximal segments with a stenosis >50% (C-index 0.56, p=0.002). In an optimized score including both parameters, CCTA significantly improved overall risk prediction beyond NCEP ATP III score as best clinical score. According to this score, a proximal segment with either a mixed or calcified plaque or a stenosis >50% is equivalent to a 5 year increase in age or the risk of smoking. CONCLUSION: In CCTA, both plaque burden and stenosis, particularly in proximal segments, carry incremental prognostic value. A prognostic score based on this data can improve risk prediction beyond clinical risk scores.

OBJECTIVE: to analyze the predictive value of coronary CT angiography and to model and validate an optimized score for prognosis of 2-year survival based on a patient population with suspected coronary artery disease (CAD). BACKGROUND: Coronary CT angiography (CCTA) carries important prognostic information in addition to the detection of obstructive coronary artery disease. But it is still unclear how the results of CCTA should be interpreted in the context of clinical risk predictors METHODS: The analysis is based on a test sample of 17,793 patients and a validation sample of 2,506 patients, all with suspected CAD, from the international CONFIRM registry. Based on CCTA data and clinical risk scores, an optimized score was modeled. The endpoint was all cause mortality. RESULTS: During a median follow-up of 2.3 years, 347 patients died. Best CCTA parameter for prediction of mortality was the number of proximal segments with mixed or calcified plaques (C-index 0.64, p<0.0001) and the number of proximal segments with a stenosis >50% (C-index 0.56, p=0.002). In an optimized score including both parameters, CCTA significantly improved overall risk prediction beyond NCEP ATP III score as best clinical score. According to this score, a proximal segment with either a mixed or calcified plaque or a stenosis >50% is equivalent to a 5 year increase in age or the risk of smoking. CONCLUSION: In CCTA, both plaque burden and stenosis, particularly in proximal segments, carry incremental prognostic value. A prognostic score based on this data can improve risk prediction beyond clinical risk scores.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Nuclear Medicine
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2013
Deposited On:15 Jul 2013 08:34
Last Modified:05 Apr 2016 16:52
Publisher:Elsevier
ISSN:0735-1097
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.jacc.2013.04.064
PubMed ID:23727215
Permanent URL: https://doi.org/10.5167/uzh-79309

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