Dataset Information

Incremental prognostic value of coronary computed tomography angiography over coronary calcium scoring for major adverse cardiac events in elderly asymptomatic individuals.

ABSTRACT:

Aims

Coronary computed tomography angiography (CCTA) and coronary artery calcium score (CACS) have prognostic value for coronary artery disease (CAD) events beyond traditional risk assessment. Age is a risk factor with very high weight and little is known regarding the incremental value of CCTA over CAC for predicting cardiac events in older adults.

Methods and results

Of 27?125 individuals undergoing CCTA, a total of 3145 asymptomatic adults were identified. This study sample was categorized according to tertiles of age (cut-off points: 52 and 62?years). CAD severity was classified as 0, 1-49, and??50% maximal stenosis in CCTA, and further categorized according to number of vessels??50% stenosis. The Framingham 10-year risk score (FRS) and CACS were employed as major covariates. Major adverse cardiovascular events (MACE) were defined as a composite of all-cause death or non-fatal MI. During a median follow-up of 26?months (interquartile range: 18-41?months), 59 (1.9%) MACE occurred. For patients in the top age tertile, CCTA improved discrimination beyond a model included FRS and CACS (C-statistic: 0.75 vs. 0.70, P-value?=?0.015). Likewise, the addition of CCTA improved category-free net reclassification (cNRI) of MACE in patients within the highest age tertile (e.g. cNRI?=?0.75; proportion of events/non-events reclassified were 50 and 25%, respectively; P-value <0.05, all). CCTA displayed no incremental benefit beyond FRS and CACS for prediction of MACE in the lower age tertiles.

Conclusion

CCTA provides added prognostic value beyond cardiac risk factors and CACS for the prediction of MACE in asymptomatic older adults.

SUBMITTER: Han D

PROVIDER: S-EPMC5963306 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

Incremental prognostic value of coronary computed tomography angiography over coronary calcium scoring for major adverse cardiac events in elderly asymptomatic individuals.

Han Donghee D Hartaigh Bríain Ó BÓ Gransar Heidi H Lee Ji Hyun JH Rizvi Asim A Baskaran Lohendran L Schulman-Marcus Joshua J Dunning Allison A Achenbach Stephan S Al-Mallah Mouaz H MH Berman Daniel S DS Budoff Matthew J MJ Cademartiri Filippo F Maffei Erica E Callister Tracy Q TQ Chinnaiyan Kavitha K Chow Benjamin J W BJW DeLago Augustin A Hadamitzky Martin M Hausleiter Joerg J Kaufmann Philipp A PA Raff Gilbert G Shaw Leslee J LJ Villines Todd C TC Kim Yong-Jin YJ Leipsic Jonathon J Feuchtner Gudrun G Cury Ricardo C RC Pontone Gianluca G Andreini Daniele D Marques Hugo H Rubinshtein Ronen R Hindoyan Niree N Jones Erica C EC Gomez Millie M Lin Fay Y FY Chang Hyuk-Jae HJ Min James K JK

European heart journal. Cardiovascular Imaging 20180601 6

<h4>Aims</h4>Coronary computed tomography angiography (CCTA) and coronary artery calcium score (CACS) have prognostic value for coronary artery disease (CAD) events beyond traditional risk assessment. Age is a risk factor with very high weight and little is known regarding the incremental value of CCTA over CAC for predicting cardiac events in older adults.<h4>Methods and results</h4>Of 27 125 individuals undergoing CCTA, a total of 3145 asymptomatic adults were identified. This study sample was ...[more]

PMID: 28977374

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Project description:BackgroundThe study aims to compare the prognostic performance of conventional scoring systems to a machine learning (ML) model on coronary computed tomography angiography (CCTA) to discriminate between the patients with and without major adverse cardiovascular events (MACEs) and to find the most important contributing factor of MACE.Materials and methodsFrom November to December 2019, 500 of 1586 CCTA scans were included and analyzed, then six conventional scores were calculated for each participant, and seven ML models were designed. Our study endpoints were all-cause mortality, non-fatal myocardial infarction, late coronary revascularization, and hospitalization for unstable angina or heart failure. Score performance was assessed by area under the curve (AUC) analysis.ResultsOf 500 patients (mean age: 60 ± 10; 53.8% male subjects) referred for CCTA, 416 patients have met inclusion criteria, 46 patients with early (<90 days) cardiac evaluation (due to the inability to clarify the reason for the assessment, deterioration of the symptoms vs. the CCTA result), and 38 patients because of missed follow-up were not enrolled in the final analysis. Forty-six patients (11.0%) developed MACE within 20.5 ± 7.9 months of follow-up. Compared to conventional scores, ML models showed better performance, except only one model which is eXtreme Gradient Boosting had lower performance than conventional scoring systems (AUC:0.824, 95% confidence interval (CI): 0.701-0.947). Between ML models, random forest, ensemble with generalized linear, and ensemble with naive Bayes were shown to have higher prognostic performance (AUC: 0.92, 95% CI: 0.85-0.99, AUC: 0.90, 95% CI: 0.81-0.98, and AUC: 0.89, 95% CI: 0.82-0.97), respectively. Coronary artery calcium score (CACS) had the highest correlation with MACE.ConclusionCompared to the conventional scoring system, ML models using CCTA scans show improved prognostic prediction for MACE. Anatomical features were more important than clinical characteristics.

Project description:BackgroundAlthough coronary computed tomography angiography (CCTA) is currently utilized as the frontline test to accurately diagnose coronary artery disease (CAD) in clinical practice, there are still debates regarding its use as a screening tool for the asymptomatic population. Using deep learning (DL), we sought to develop a prediction model for significant coronary artery stenosis on CCTA and identify the individuals who would benefit from undergoing CCTA among apparently healthy asymptomatic adults.MethodsWe retrospectively reviewed 11,180 individuals who underwent CCTA as part of routine health check-ups between 2012 and 2019. The main outcome was the presence of coronary artery stenosis of ≥70% on CCTA. We developed a prediction model using machine learning (ML), including DL. Its performance was compared with pretest probabilities, including the pooled cohort equation (PCE), CAD consortium, and updated Diamond-Forrester (UDF) scores.ResultsIn the cohort of 11,180 apparently healthy asymptomatic individuals (mean age 56.1 years; men 69.8%), 516 (4.6%) presented with significant coronary artery stenosis on CCTA. Among the ML methods employed, a neural network with multi-task learning (19 selected features), one of the DL methods, was selected due to its superior performance, with an area under the curve (AUC) of 0.782 and a high diagnostic accuracy of 71.6%. Our DL-based model demonstrated a better prediction than the PCE (AUC, 0.719), CAD consortium score (AUC, 0.696), and UDF score (AUC, 0.705). Age, sex, HbA1c, and HDL cholesterol were highly ranked features. Personal education and monthly income levels were also included as important features of the model.ConclusionWe successfully developed the neural network with multi-task learning for the detection of CCTA-derived stenosis of ≥70% in asymptomatic populations. Our findings suggest that this model may provide more precise indications for the use of CCTA as a screening tool to identify individuals at a higher risk, even in asymptomatic populations, in clinical practice.

Project description:ImportanceAdverse pregnancy outcomes are recognized risk enhancers for cardiovascular disease, but the prevalence of subclinical coronary atherosclerosis after these conditions is unknown.ObjectiveTo assess associations between history of adverse pregnancy outcomes and coronary artery disease assessed by coronary computed tomography angiography screening.Design, setting, and participantsCross-sectional study of a population-based cohort of women in Sweden (n = 10 528) with 1 or more deliveries in 1973 or later, ascertained via the Swedish National Medical Birth Register, who subsequently participated in the Swedish Cardiopulmonary Bioimage Study at age 50 to 65 (median, 57.3) years in 2013-2018. Delivery data were prospectively collected.ExposuresAdverse pregnancy outcomes, including preeclampsia, gestational hypertension, preterm delivery, small-for-gestational-age infant, and gestational diabetes. The reference category included women with no history of these exposures.Main outcomes and measuresCoronary computed tomography angiography indexes, including any coronary atherosclerosis, significant stenosis, noncalcified plaque, segment involvement score of 4 or greater, and coronary artery calcium score greater than 100.ResultsA median 29.6 (IQR, 25.0-34.9) years after first registered delivery, 18.9% of women had a history of adverse pregnancy outcomes, with specific pregnancy histories ranging from 1.4% (gestational diabetes) to 9.5% (preterm delivery). The prevalence of any coronary atherosclerosis in women with a history of any adverse pregnancy outcome was 32.1% (95% CI, 30.0%-34.2%), which was significantly higher (prevalence difference, 3.8% [95% CI, 1.6%-6.1%]; prevalence ratio, 1.14 [95% CI, 1.06-1.22]) compared with reference women. History of gestational hypertension and preeclampsia were both significantly associated with higher and similar prevalence of all outcome indexes. For preeclampsia, the highest prevalence difference was observed for any coronary atherosclerosis (prevalence difference, 8.0% [95% CI, 3.7%-12.3%]; prevalence ratio, 1.28 [95% CI, 1.14-1.45]), and the highest prevalence ratio was observed for significant stenosis (prevalence difference, 3.1% [95% CI, 1.1%-5.1%]; prevalence ratio, 2.46 [95% CI, 1.65-3.67]). In adjusted models, odds ratios for preeclampsia ranged from 1.31 (95% CI, 1.07-1.61) for any coronary atherosclerosis to 2.21 (95% CI, 1.42-3.44) for significant stenosis. Similar associations were observed for history of preeclampsia or gestational hypertension among women with low predicted cardiovascular risk.Conclusions and relevanceAmong Swedish women undergoing coronary computed tomography angiography screening, there was a statistically significant association between history of adverse pregnancy outcomes and image-identified coronary artery disease, including among women estimated to be at low cardiovascular disease risk. Further research is needed to understand the clinical importance of these associations.

Project description:PURPOSE:Quantitative computed tomography (QCT) provides important prognostic information of coronary atherosclerosis. We investigated intraobserver and interobserver QCT reproducibility in asymptomatic individuals, patients with acute chest pain without acute coronary syndrome (ACS), and patients with acute chest pain and ACS. METHODS:Fifty patients from each cohort, scanned between 01/02/2010-14/11/2013 and matched according to age and gender, were retrospectively assessed for inclusion. Patients with no coronary artery disease, previous coronary artery bypass graft surgery, and poor image quality were excluded. Coronary atherosclerosis was measured semi-automatically by 2 readers. Reproducibility of minimal lumen area (MLA), minimal lumen diameter (MLD), area stenosis, diameter stenosis, vessel remodeling, plaque eccentricity, plaque burden, and plaque volumes was assessed using concordance correlation coefficient (CCC), Bland-Altman, coefficient of variation, and Cohen's kappa. RESULTS:A total of 84 patients (63 matched) were included. Intraobserver and interobserver reproducibility estimates were acceptable for MLA (CCC = 0.94 and CCC = 0.91, respectively), MLD (CCC = 0.92 and CCC = 0.86, respectively), plaque burden (CCC = 0.86 and CCC = 0.80, respectively), and plaque volume (CCC = 0.97 and CCC = 0.95, respectively). QCT detected area and diameter stenosis ?50%, positive remodeling, and eccentric plaque with moderate-good intraobserver and interobserver reproducibility (kappa: 0.64-0.66, 0.69-0.76, 0.46-0.48, and 0.41-0.62, respectively). Reproducibility of plaque composition decreased with decreasing plaque density (intraobserver and interobserver CCC for dense calcium (>0.99; 0.98), fibrotic (0.96; 0.93), fibro-fatty (0.95; 0.91), and necrotic core tissue (0.89; 0.84). Reproducibility generally decreased with worsening clinical risk profile. CONCLUSIONS:Semi-automated QCT of coronary plaque morphology is reproducible, albeit with some decline in reproducibility with worsening patient risk profile.

Project description:BackgroundPericoronary artery coronary tissue (PACT) is a type of epicardial fat that can reflect the state of the coronary artery (inflammation, etc.). However, it cannot be reasonably and efficiently utilized in routine computed tomography (CT) examination. The aim of this study was to use artificial intelligence (AI) software to analyze coronary computed tomography angiography (CCTA) and measure the coronary perivascular fat attenuation index (FAI) of patients. The relationship between FAI and the occurrence of coronary adverse events and the degree of coronary stenosis were further analyzed.MethodsThis study involved patients who experienced CCTA in West China Hospital, Sichuan University, from January 2012 to December 2012. These patients were followed up to 2020 and classified according to the occurrence of coronary adverse events and the degree of stenosis of the lumen. For all patients, AI software was used to analyze the CCTA images of patients, and the FAI of 3 coronary arteries, the left anterior descending artery (LAD), the left circumflex artery (LCX), and the right coronary artery (RCA), was measured. Moreover, the relationship between FAI and patients with different degrees of coronary stenosis and adverse coronary events was determined.ResultsComparisons between any 2 groups showed that the differences in the FAI among the 4 groups for the LAD were significant (all P values <0.05). There were no significant differences between the group with less-than-moderate stenosis (Mb) without adverse events and the group with moderate-or-above stenosis (M) with no adverse events for the LCX (P>0.05). For the remaining groups, FAI values exhibited statistically significant differences (P<0.05). According to the degree of lumen stenosis, the patients were divided into groups according to LAD, LCX, and RCA and the sum of the 3 vessels. There were significant differences in coronary FAI among the groups with different degrees of lumen stenosis for the sum of the 3 vessels, the LAD, and the LCX (P<0.05).ConclusionsFAI can reflect the state of the coronary artery, which is related to inflammation of the coronary lumen. Moreover, there is a relationship between FAI and the degree of stenosis in the coronary lumen: the narrower the coronary lumen is, the higher the FAI around the lumen.

Dataset Information

Incremental prognostic value of coronary computed tomography angiography over coronary calcium scoring for major adverse cardiac events in elderly asymptomatic individuals.

Aims

Methods and results

Conclusion

Publications

Incremental prognostic value of coronary computed tomography angiography over coronary calcium scoring for major adverse cardiac events in elderly asymptomatic individuals.

Similar Datasets

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