Role of Coronary Artery Calcium Scoring in Detection of Coronary Artery Disease according to Framingham Risk Score in Populations with Low to Intermediate Risks.
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SUBMITTER: Kim WJ
PROVIDER: S-EPMC4853669 | biostudies-literature | 2016 Jun
REPOSITORIES: biostudies-literature
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Role of Coronary Artery Calcium Scoring in Detection of Coronary Artery Disease according to Framingham Risk Score in Populations with Low to Intermediate Risks.
Kim Won-Jang WJ Kwon Chang Hee CH Han Seungbong S Lee Woo Seok WS Kang Joon Won JW Ahn Jung-Min JM Lee Jong-Young JY Park Duk-Woo DW Kang Soo-Jin SJ Lee Seung-Whan SW Kim Young-Hak YH Lee Cheol Whan CW Park Seong-Wook SW Park Seung-Jung SJ
Journal of Korean medical science 20160418 6
Current guidelines recommend that coronary artery calcium (CAC) screening should only be used for intermediate risk groups (Framingham risk score [FRS] of 10%-20%). The CAC distributions and coronary artery disease (CAD) prevalence in various FRS strata were determined. The benefit to lower risk populations of CAC score-based screening was also assessed. In total, 1,854 participants (aged 40-79 years) without history of CAD, stroke, or diabetes were enrolled. CAC scores of > 0, ≥ 100, and ≥ 300 ...[more]
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Project description:This study aimed to evaluate the association between the atherogenic index of plasma (AIP), which has been suggested as a novel marker for atherosclerosis, and coronary artery calcification (CAC) progression according to the baseline coronary artery calcium score (CACS). We included 12,326 asymptomatic Korean adults who underwent at least two CAC evaluations from December 2012 to August 2016. Participants were stratified into four groups according to AIP quartiles, which were determined by the log of (triglyceride/high-density lipoprotein cholesterol). Baseline CACSs were divided into three groups: 0, 1?-?100, and?>?100. CAC progression was defined as a difference???2.5 between the square roots (?) of the baseline and follow-up CACSs (??transformed CACS). Annualized ??transformed CACS was defined as ??transformed CACS divided by the inter-scan period. During a mean 3.3-year follow-up period, the overall incidence of CAC progression was 30.6%. The incidences of CAC progression and annualized ??transformed CACS were markedly elevated with increasing AIP quartile in participants with baseline CACSs of 0 and 1?-?100, but not in those with a baseline CACS?>?100. The AIP level was associated with the annualized ??transformed CACS in participants with baseline CACSs of 0 (??=?0.016; P?<?0.001) and 1?-?100 (??=?0.035; P?<?0.001), but not in those with baseline CACS?>?100 (??=?0.032; P?=?0.385). After adjusting for traditional risk factors, the AIP was significantly associated with CAC progression in those with baseline CACS???100. The AIP has value for predicting CAC progression in asymptomatic adults without heavy baseline CAC.
| S-EPMC7721801 | biostudies-literature
Project description:PurposeTo extract radiomic features from coronary artery calcium (CAC) on CT images and to determine whether this approach could improve the ability to identify individuals at risk for a composite endpoint of clinical events.Materials and methodsParticipants from the Offspring and Third Generation cohorts of the community-based Framingham Heart Study underwent noncontrast cardiac CT (2002-2005) and were followed for more than a median of 9.1 years for composite major events. A total of 624 participants with CAC Agatston score (AS) of greater than 0 and good or excellent CT image quality were included for manual CAC segmentation and extraction of a predefined set of radiomic features reflecting intensity, shape, and texture. In a discovery cohort (n = 318), machine learning was used to select the 20 most informative and nonredundant CAC radiomic features, classify features predicting events, and define a radiomic-based score (RS). Performance of the RS was tested independently for the prediction of events in a validation cohort (n = 306).ResultsThe RS had a median value of 0.08 (interquartile range, 0.007-0.71) and a weak and modest correlation with Framingham risk score (FRS) (r = 0.2) and AS (r = 0.39), respectively. The continuous RS unadjusted, adjusted for age and sex, FRS, AS, and FRS plus AS were significantly associated with events (hazard ratio [HR] = 2.2, P < .001; HR = 1.8, P = .002; HR = 2.0, P < .001; HR = 1.7, P = .02; and HR = 1.8, P = .01, respectively). In participants with AS of less than 300, RS association with events remained significant when unadjusted and adjusted for age and sex, FRS, AS, and FRS plus AS (HR = 2.4, 2.8, 2.8, 2.3, and 2.6; P < .001, respectively). In the same subgroup of participants, adding the RS to AS resulted in a significant improvement in the discriminatory ability for events as compared with the AS (area under the receiver operating curve: 0.80 vs 0.68, respectively; P = .03).ConclusionA radiomic-based score, including the complex properties of CAC, may constitute an imaging biomarker to be further developed to identify individuals at risk for major adverse cardiovascular events in a community-based cohort. Supplemental material is available for this article. © RSNA, 2020.
| S-EPMC7051158 | biostudies-literature
Project description:BACKGROUND:Limited data exist regarding the use of a genetic risk score (GRS) for predicting risk of incident cardiovascular disease (CVD) in US-based samples. METHODS AND RESULTS:By using findings from recent genome-wide association studies, we constructed GRSs composed of 13 genetic variants associated with myocardial infarction or other manifestations of coronary heart disease (CHD) and 102 genetic variants associated with CHD or its major risk factors. We also updated the 13 single-nucleotide polymorphism (SNP) GRSs with 16 SNPs recently discovered by genome-wide association studies. We estimated the association, discrimination, and risk reclassification of each GRS for incident cardiovascular events and prevalent coronary artery calcium (CAC). In analyses adjusted for age, sex, CVD risk factors, and parental history of CVD, the 13 SNP GRSs were significantly associated with incident hard CHD (hazard ratio, 1.07; 95% CI, 1.00-1.15; P=0.04), CVD (hazard ratio per allele, 1.05; 95% CI, 1.01-1.09; P=0.03), and high CAC (defined as >75(th) age- and sex-specific percentile; odds ratio per allele, 1.18; 95% CI, 1.11-1.26; P=3.4×10(-7)). The GRS did not improve discrimination for incident CHD or CVD but led to modest improvements in risk reclassification. However, significant improvements in discrimination and risk reclassification were observed for the prediction of high CAC. The addition of 16 newly discovered SNPs to the 13 SNP GRSs did not significantly modify these results. CONCLUSIONS:A GRS composed of 13 SNPs associated with coronary disease is an independent predictor of cardiovascular events and of high CAC, modestly improves risk reclassification for incident CHD, and significantly improves discrimination for high CAC. The addition of recently discovered SNPs did not significantly improve the performance of this GRS.
| S-EPMC3292865 | biostudies-literature
Project description:BackgroundPrecision estimation of cardiovascular risk remains the cornerstone of atherosclerotic cardiovascular disease (ASCVD) prevention. While coronary artery calcium (CAC) scoring is the best available non-invasive quantitative modality to evaluate risk of ASCVD, it excludes risk related to prior myocardial infarction, cardiomyopathy, and arrhythmia which are implicated in ASCVD. The high-dimensional and inter-correlated nature of ECG data makes it a good candidate for analysis using machine learning techniques and may provide additional prognostic information not captured by CAC. In this study, we aimed to develop a quantitative ECG risk score (eRiS) to predict major adverse cardiovascular events (MACE) alone, or when added to CAC. Further, we aimed to construct and validate a novel nomogram incorporating ECG, CAC and clinical factors for ASCVD.MethodsWe analyzed 5,864 patients with at least 1 cardiovascular risk factor who underwent CAC scoring and a standard ECG as part of the CLARIFY study (ClinicalTrials.gov Identifier: NCT04075162). Events were defined as myocardial infarction, coronary revascularization, stroke or death. A total of 649 ECG features, consisting of measurements such as amplitude and interval measurements from all deflections in the ECG waveform (53 per lead and 13 overall) were automatically extracted using a clinical software (GE Muse™ Cardiology Information System, GE Healthcare). The data was split into 4 training (Str) and internal validation (Sv) sets [Str (1): Sv (1): 50:50; Str (2): Sv (2): 60:40; Str (3): Sv (3): 70:30; Str (4): Sv (4): 80:20], and the results were compared across all the subsets. We used the ECG features derived from Str to develop eRiS. A least absolute shrinkage and selection operator-Cox (LASSO-Cox) regularization model was used for data dimension reduction, feature selection, and eRiS construction. A Cox-proportional hazards model was used to assess the benefit of using an eRiS alone (Mecg), CAC alone (Mcac) and a combination of eRiS and CAC (Mecg+cac) for MACE prediction. A nomogram (Mnom) was further constructed by integrating eRiS with CAC and demographics (age and sex). The primary endpoint of the study was the assessment of the performance of Mecg, Mcac, Mecg+cac and Mnom in predicting CV disease-free survival in ASCVD.FindingsOver a median follow-up of 14 months, 494 patients had MACE. The feature selection strategy preserved only about 18% of the features that were consistent across the various strata (Str). The Mecg model, comprising of eRiS alone was found to be significantly associated with MACE and had good discrimination of MACE (C-Index: 0.7, p = <2e-16). eRiS could predict time-to MACE (C-Index: 0.6, p = <2e-16 across all Sv). The Mecg+cac model was associated with MACE (C-index: 0.71). Model comparison showed that Mecg+cac was superior to Mecg (p = 1.8e-10) or Mcac (p < 2.2e-16) alone. The Mnom, comprising of eRiS, CAC, age and sex was associated with MACE (C-index 0.71). eRiS had the most significant contribution, followed by CAC score and other clinical variables. Further, Mnom was able to identify unique patient risk-groups based on eRiS, CAC and clinical variables.ConclusionThe use of ECG features in conjunction with CAC may allow for improved prognostication and identification of populations at risk. Future directions will involve prospective validation of the risk score and the nomogram across diverse populations with a heterogeneity of treatment effects.
| S-EPMC9580025 | biostudies-literature
Project description:Coronary artery disease (CAD) is caused by an acute myocardial infarction and is still feared as a life-threatening heart disease worldwide. In order to identify patients at high risk for CAD, previous studies have proposed various risk assessment scores for the prevention of CAD. The most commonly used risk assessment score for CAD worldwide is the Framingham Risk Score (FRS). The FRS is used for middle-aged people; hence, its appropriateness has not been demonstrated to predict the likelihood of CAD occurrence in very elderly people. This article examines the possible predictive value of FRS for CAD in very elderly people over 90 years of age.Data on all patients over 90 years of age who received a cardiac catheter were collected from hospital charts from the Department of Internal Medicine, Saarland University Medical Center, and HELIOS Hospital Wuppertal, Witten/Herdecke University Medical Center, Germany, within a study period from 2004 to 2013. The FRSs and cardiovascular risk profiles of patients over 90 years of age with and without CAD after cardiac catheterization were compared.One hundred and seventy-five (91.15%, mean age 91.51±1.80 years, 74 females [42.29%]; 95% confidence interval [CI], 0.87-0.95) of a total 192 of the very elderly patients were found to have CAD. Based on the results of our study, the FRS seems to provide weak predictive ability for CAD in very elderly people (P = 0.3792).We found weak prediction power of FRS for CAD in nonagenarians.
| S-EPMC4231135 | biostudies-other
Project description:BackgroundIn patients with suspected obstructive coronary artery disease (CAD), the risk factor-weighted clinical likelihood (RF-CL) model and the coronary artery calcium score-weighted clinical likelihood (CACS-CL) model improves the identification of obstructive CAD compared with basic pretest probability (PTP) models.ObjectivesThe aim of this study was to assess the prognostic value of the new models.MethodsThe incidences of myocardial infarction and death were stratified according to categories by the RF-CL and CACS-CL and compared with categories by the PTP model. We used cohorts from a Danish register (n = 41,177) and a North American randomized study (n = 3,952). All patients were symptomatic and were referred for diagnostic testing because of clinical indications.ResultsDespite substantial down-reclassification of patients to a likelihood ≤5% of CAD with either the RF-CL (45%) or CACS-CL (60%) models compared with the PTP (18%), the annualized event rates of myocardial infarction and death were low using all 3 models; RF-CL 0.51% (95% CI: 0.46-0.56), CACS-CL 0.48% (95% CI: 0.44-0.56), and PTP 0.37% (95% CI: 0.31-0.44), respectively. Overall, comparison of the predictive power of the 3 models using Harrell's C-statistics demonstrated superiority of the RF-CL (0.64 [95% CI: 0.63-0.65]) and CACS-CL (0.69 [95% CI: 0.67-0.70]) compared with the PTP model (0.61 [95% CI: 0.60-0.62]).ConclusionsThe simple clinical likelihood models that include classical risk factors or risk factors combined with CACS provide improved risk stratification for myocardial infarction and death compared with the standard PTP model. Hence, the optimized RF-CL and CACS-CL models identify 2.5 and 3.3 times more patients, respectively, who may not benefit from further diagnostic testing.
| S-EPMC10466200 | biostudies-literature
Project description:BackgroundCoronary artery calcium score (CACS) is an established marker of coronary artery disease (CAD) and has been extensively used to stratify risk in asymptomatic individuals. However, the value of CACS in predicting plaque morphology in patients with advanced CAD is less established. The present analysis aims to assess the association between CACS and plaque characteristics detected by near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS) imaging in patients with obstructive CAD.MethodsSeventy patients with obstructive CAD underwent coronary computed tomography angiography (CTA) and 3-vessel NIRS-IVUS imaging were included in the present analysis. The CTA data were used to measure the CACS in the entire coronary tree and the segments assessed by NIRS-IVUS, and these estimations were associated with the NIRS-IVUS measurements at a patient and segment level.ResultsIn total, 65 patients (188 segments) completed the study protocol and were included in the analysis. A weak correlation was noted between the CACS, percent atheroma volume (r = 0.271, P = .002), and the calcific burden measured by NIRS-IVUS (r = 0.648, P < .001) at patient-level analysis. Conversely, there was no association between the CACS and the lipid content, or the incidence of high-risk plaques detected by NIRS. Linear regression analysis at the segment level demonstrated an association between the CACS and the total atheroma volume (coefficient, 0.087; 95% CI, 0.024-0.149; P = .008) and the calcific burden (coefficient, 0.117; 95% CI, 0.048-0.186; P = .001), but there was no association between the lipid content or the incidence of high-risk lesions.ConclusionsIn patients with obstructive CAD, the CACS is not associated with the lipid content or plaque phenotypes. These findings indicate that the CACS may have a limited value for screening or stratifying cardiovascular risk in symptomatic patients with a high probability of CAD.
| S-EPMC11307846 | biostudies-literature
Project description:ImportanceThe 2018 American Heart Association/American College of Cardiology Guideline on the Management of Blood Cholesterol recommends the use of risk-enhancing factor assessment and the selective use of coronary artery calcium (CAC) scoring to guide the allocation of statin therapy among individuals with an intermediate risk of atherosclerotic cardiovascular disease (ASCVD).ObjectiveTo examine the association between risk-enhancing factors and incident ASCVD by CAC burden among those at intermediate risk of ASCVD.Design, setting, and participantsThe Multi-Ethnic Study of Atherosclerosis is a multicenter population-based prospective cross-sectional study conducted in the US. Baseline data for the present study were collected between July 15, 2000, and July 14, 2002, and follow-up for incident ASCVD events was ascertained through August 20, 2015. Participants were aged 45 to 75 years with no clinical ASCVD or diabetes at baseline, were at intermediate risk of ASCVD (≥7.5% to <20.0%), and had a low-density lipoprotein cholesterol level of 70 to 189 mg/dL.ExposuresFamily history of premature ASCVD, premature menopause, metabolic syndrome, chronic kidney disease, lipid and inflammatory biomarkers, and low ankle-brachial index.Main outcomes and measuresIncident ASCVD over a median follow-up of 12.0 years.ResultsA total of 1688 participants (mean [SD] age, 65 [6] years; 976 men [57.8%]). Of those, 648 individuals (38.4%) were White, 562 (33.3%) were Black, 305 (18.1%) were Hispanic, and 173 (10.2%) were Chinese American. A total of 722 participants (42.8%) had a CAC score of 0. Among those with 1 to 2 risk-enhancing factors vs those with 3 or more risk-enhancing factors, the prevalence of a CAC score of 0 was 45.7% vs 40.3%, respectively. Over a median follow-up of 12.0 years (interquartile range [IQR], 11.5-12.6 years), the unadjusted incidence rate of ASCVD among those with a CAC score of 0 was less than 7.5 events per 1000 person-years for all individual risk-enhancing factors (with the exception of ankle-brachial index, for which the incidence rate was 10.4 events per 1000 person-years [95% CI, 1.5-73.5]) and combinations of risk-enhancing factors, including participants with 3 or more risk-enhancing factors. Although the individual and composite addition of risk-enhancing factors to the traditional risk factors was associated with improvement in the area under the receiver operating curve, the use of CAC scoring was associated with the greatest improvement in the C statistic (0.633 vs 0.678) for ASCVD events. For incident ASCVD, the net reclassification improvement for CAC was 0.067.Conclusions and relevanceIn this cross-sectional study, among participants with CAC scores of 0, the presence of risk-enhancing factors was generally not associated with an overall ASCVD risk that was higher than the recommended treatment threshold for the initiation of statin therapy. The use of CAC scoring was associated with significant improvements in the reclassification and discrimination of incident ASCVD. The results of this study support the utility of CAC scoring as an adjunct to risk-enhancing factor assessment to more accurately classify individuals with an intermediate risk of ASCVD who might benefit from statin therapy.
| S-EPMC8281019 | biostudies-literature
Project description:ASCVD are the leading causes of mortality and morbidity among Globe. Evaluation of patients' comprehensive and personalized risk provides risk management strategies and preventive interventions to achieve gain for patients. Framingham Risk Score (FRS) and Systemic Coronary Risk Evaluation Score (SCORE) are two well studied risk scoring models, however, can miss some (20-35%) of future cardiovascular events. To obtain more accurate risk assessment recalibrating risk models through utilizing novel risk markers have been studied in last 3 decades and both ESC and AHA recommends assessing Family History, hs-CRP, CACS, ABI, and CIMT. Subclinical Cardiovascular Disease (SCVD) has been conceptually developed for investigating gradually progressing asymptomatic development of atherosclerosis and among these novel risk markers it has been well established by literature that CACS having highest improvement in risk assessment. This review study mainly selectively discussing studies with CACS measurement. A CACS = 0 can down-stratify risk of patients otherwise treated or treatment eligible before test and can reduce unnecessary interventions and cost, whereas CACS ≥ 100 is equivalent to statin treatment threshold of ≥ 7.5% risk level otherwise statin ineligible before test. Since inflammation, insulin resistance, oxidative stress, dyslipidemia and ongoing endothelial damage due to hypertension could lead to CAC, ASCVD linked with comorbidities. Recent cohort studies have shown a CACS 100-300 as a sign of increased cancer risk. Physical activity, dietary factors, cigarette use, alcohol consumption, metabolic health, family history of CHD, aging, exposures of neighborhood environment and non-cardiovascular comorbidities can determine CACs changes.
| S-EPMC8604741 | biostudies-literature
Project description:BackgroundThe use of the Coronary Artery Calcium Score (CACS) for risk categorization instead of the Framingham Risk Score (FRS) or European Heart SCORE (EHS) to improve classification of individuals is well documented. However, the impact of reclassifying individuals using CACS on initiating lipid lowering therapy is not well understood. We aimed to determine the percentage of individuals not requiring lipid lowering therapy as per the FRS and EHS models but are found to require it using CACS and vice versa; and to determine the level of agreement between CACS, FRS and EHS based models.MethodsData was collected for 500 consecutive patients who had already undergone CACS. However, only 242 patients met the inclusion criteria and were included in the analysis. Risk stratification comparisons were conducted according to CACS, FRS, and EHS, and the agreement (Kappa) between them was calculated.ResultsIn accordance with the models, 79.7% to 81.5% of high-risk individuals were down-classified by CACS, while 6.8% to 7.6% of individuals at intermediate risk were up-classified to high risk by CACS, with slight to moderate agreement. Moreover, CACS recommended treatment to 5.7% and 5.8% of subjects untreated according to European and Canadian guidelines, respectively; whereas 75.2% to 81.2% of those treated in line with the guidelines would not be treated based on CACS.ConclusionIn this simulation, using CACS for risk categorization warrants lipid lowering treatment for 5-6% and spares 70-80% from treatment in accordance with the guidelines. Current strong evidence from double randomized clinical trials is in support of guideline recommendations. Our results call for a prospective trial to explore the benefits/risks of a CACS-based approach before any recommendations can be made.
| S-EPMC4614893 | biostudies-literature