A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero

Clinical Significance of Diabetes in Asymptomatic Individuals With Zero Coronary Artery Calcium Score

The clinical significance of diabetes mellitus (DM) on the cardiovascular disease in the zero coronary artery calcium (CAC) group is not well studied. This study investigated the impact of DM in an asymptomatic population with zero CAC scores. Overall, 9269 adults who received coronary computed tomography angiography (CCTA) scans for coronary disease evaluation during a general medical checkup were initially selected. After excluding participants with CAC >0, 4139 were included in the analysis. Baseline characteristics, CCTA findings including significant stenosis ≥50%, and clinical outcomes were assessed, including all-cause death, cardiovascular death, myocardial infarction (MI), or revascularization. The average age was 51.8 years, and 2706 participants (65.3%) were male. DM group had a higher prevalence of noncalcified plaque (16.7% vs 11.6%), significant stenosis (3.4% vs 1.5%), and a greater atherosclerosis burden than the non-DM group. DM was identified as a significant predictor of significant stenosis (adjusted odds ratio 1.88 [1.07-3.33], p = 0.029). During the median follow-up of 5.3 years, participants with DM experienced a higher rate of revascularization (1.2% vs 0.3%, adjusted hazard ratio 3.64 [1.25-10.56], p = 0.018), with a remarkably low incidence of cardiovascular death (0% vs 0.1%) and MI (both 0%). The risk of significant stenosis and revascularization increased gradually according to the severity of DM. In conclusion, asymptomatic patients with DM and zero CAC scores may face an increased risk of coronary artery disease presence compared to non-DM individuals. Despite zero CAC suggesting a low risk of cardiovascular disease, patients with DM may still exhibit a demonstrable atherosclerotic burden.

A LASSO-derived model for the prediction of nonattainment of target LDL-C reduction with PCSK9 inhibitors in patients with atherosclerotic cardiovascular disease

BACKGROUND

Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors have demonstrated significant efficacy in lowering low-density lipoprotein cholesterol (LDL-C) levels in patients with atherosclerotic cardiovascular disease (ASCVD), but some fail to achieve the target levels. This study aimed to explore the potential risk factors associated with this nonattainment of target LDL-C reduction (NTR-LDLC) and develop a prediction model.

METHODS

The population was randomly divided into derivation and verification subsets in a 7:3 ratio. Utilizing the Least Absolute Shrinkage and Selection Operator (LASSO) regression, we filtered the variables within the derivation set. Subsequently, we assessed the model's predictive accuracy for the NTR-LDLC in both subsets through the application of decision curve analysis (DCA) and the plotting of receiver operating characteristic (ROC) curves.

RESULTS

The study enrolled 748 patients, with 115 individuals experiencing NTR-LDLC. Using LASSO regression, five significant predictive factors associated with NTR-LDLC were identified: statin therapy, diastolic blood pressure (DBP), alanine aminotransferase (ALT), total cholesterol (TC), and LDL-C. Based on these results, a nomogram prediction model was constructed and validated, showing predictive accuracy with the area under the ROC curve (AUC) of 0.718 (95% confidence interval [CI]: 0.657 - 0.779) and 0.703 (95% CI: 0.605 - 0.801) for the derivation and validation sets, respectively.

CONCLUSIONS

This study presents a LASSO-derived predictive model that can be used to predict the risk of NTR-LDLC with PCSK9 inhibitors in patients with ASCVD.

Predicting the risk of coronary artery calcium progression in the general population: insights from the MESA and CARDIA studies

AIM

Coronary artery calcium (CAC) progression is a strong predictor of cardiovascular disease. This study aims to develop and validate a practical tool for predicting individual CAC progression in the general population.

MATERIALS AND METHODS

Data were utilized from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort, comprising 5486 participants (47.3% male, mean ± SD age: 61.9 ± 10.2 years), who were randomly assigned to either a training set or an internal validation set at a 7:3 ratio. Additionally, a separate cohort of 2447 participants (44.6% male, mean ± SD age: 40.4 ± 3.5 years) from the Coronary Artery Risk Development in Young Adults (CARDIA) study served as the external validation set. A nomogram was developed based on a Cox regression model incorporating 10 variables selected by the least absolute shrinkage and selection operator (LASSO) method to predict CAC progression.

RESULTS

From the 61 features considered, 10 key variables were identified: age, male sex, smoking status, waist circumference, systolic blood pressure, fasting glucose, lipid abnormalities, and the use of antihypertensive, glucose-lowering, and lipid-lowering medications. The nomogram demonstrated good discrimination with a C-statistic of 0.682 (95% confidence interval [CI], 0.665-0.699) in the training set and 0.750 (95% CI, 0.729-0.771) in the external validation set. Decision curve analysis further confirmed the nomogram's clinical utility in predicting the risk of CAC progression.

CONCLUSION

Our nomogram offers a practical tool for individualized prediction of CAC progression potentially aiding in the primary prevention of cardiovascular disease in clinical practice. REGISTRATION URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT00005130 (CARDIA), NCT00005487 (MESA).

Establishment and validation of apnea risk prediction models in preterm infants: a retrospective case control study

BACKGROUND

Apnea is common in preterm infants and can be accompanied with severe hypoxic damage. Early assessment of apnea risk can impact the prognosis of preterm infants. We constructed a prediction model to assess apnea risk in premature infants for identifying high-risk groups.

METHODS

A total of 162 and 324 preterm infants with and without apnea who were admitted to the neonatal intensive care unit of Xiamen University between January 2018 and December 2021 were selected as the case and control groups, respectively. Demographic characteristics, laboratory indicators, complications of the patients, pregnancy-related factors, and perinatal risk factors of the mother were collected retrospectively. The participants were randomly divided into modeling (n = 388) and validation (n = 98) sets in an 8:2 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate logistic regression analyses were used to independently filter variables from the modeling set and build a model. A nomogram was used to visualize models. The calibration and clinical utility of the model was evaluated using consistency index, receiver operating characteristic (ROC) curve, calibration curve, and decision curve, and the model was verified using the validation set.

RESULTS

Results of LASSO combined with multivariate logistic regression analysis showed that gestational age at birth, birth length, Apgar score, and neonatal respiratory distress syndrome were predictors of apnea development in preterm infants. The model was presented as a nomogram and the Hosmer-Lemeshow goodness of fit test showed a good model fit (χ2=5.192, df=8, P=0.737), with Nagelkerke R2 of 0.410 and C-index of 0.831. The area under the ROC curve and 95% CI were 0.831 (0.787-0.874) and 0.829 (0.722-0.935), respectively. Delong's test comparing the AUC of the two data sets showed no significant difference (P=0.976). The calibration curve showed good agreement between the predicted and actual observations. The decision curve results showed that the threshold probability range of the model was 0.07-1.00, the net benefit was high, and the constructed clinical prediction model had clinical utility.

CONCLUSIONS

Our risk prediction model based on gestational age, birth length, Apgar score 10 min post-birth, and neonatal respiratory distress syndrome was validated in many aspects and had good predictive efficacy and clinical utility.

New look at the power of zero coronary artery calcium (CAC) in Asian population: a systemic review and meta-analysis

Background

Numerous studies have validated a 5-year warranty period for heart health in Western populations with a coronary artery calcium (CAC) score of zero. While the calcium score is a crucial cardiovascular risk indicator, its interpretation in Asian populations remains unclear. This meta-analysis aimed to clarify the uncertainty surrounding the prevalence, warranty period, and prognostic implications of zero CAC scores in Asian populations. It also examined the impact of sex on subclinical CAC progression. While the calcium score is a crucial cardiovascular risk indicator, its interpretation in Asian populations remains unclear. The study aimed to shed light on these issues by exploring the specificities of subclinical CAC progression in the Asian context.

Methods

Our systematic literature search, from the study's inception to October 2023, targeted studies on subclinical CAC progression in the Asian population with a zero CAC score. We searched the Cochrane Library, and PubMed. The search terms included "zero score", "coronary calcification", "zero CAC score", and "CAC scan".

Results

We evaluated seven published studies through a meta-analysis and assessed the risk of bias using the Newcastle-Ottawa Scale (NOS). In this meta-analysis of three observational studies addressing zero CAC prevalence (n=7,661), the pooled prevalence of zero CAC scores in the Asian population was 18.2% [95% confidence interval (CI): 12.5-25.9%]. A significant difference in follow-up warranty period was observed between the CAC zero group and subclinical CAC progression group (mean difference, 1.26 years; 95% CI: 0.94-1.58; P<0.001). Furthermore, the conversion rate of subclinical CAC progression differed significantly between males and females (risk ratio, 2.37; 95% CI: 1.98-2.84; P<0.001). Analysis of four studies revealed a notable discrepancy in the major adverse cardiovascular event (MACE) rate between the CAC (-) and CAC (+) groups (risk ratio, 4.78; 95% CI: 2.21-10.36; P<0.001).

Conclusions

The meta-analysis of zero CAC scores in Asian populations suggested an 18.2% prevalence. A 5-year warranty period was noted, with heightened subclinical CAC progression likelihood after this duration. Additionally, sex-based differences were observed in subclinical CAC progression rates. These findings will provide clinical cardiovascular risk stratification for guiding gender-specific clinical decision-making in asymptomatic in Asian individuals.

The association between C-reactive protein and coronary artery calcification: a systematic review and meta-analysis

BACKGROUND

While coronary artery calcification (CAC) is recognized as a reliable marker for coronary atherosclerosis, the relationship between the concentration of C-reactive protein (CRP) and the incidence and progression of CAC remains controversial.

METHOD

PubMed, Embase, Web of Science, and Scopus were systematically searched to identify relevant observational studies until October 2023. The methodological quality of the included studies was evaluated using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis was employed to calculate pooled odd ratios (OR) and corresponding 95% confidence intervals, considering heterogeneity among the studies.

RESULTS

Out of the 2545 records, 42 cross-sectional and 9 cohort studies were included in the systematic review. The meta-analysis on 12 eligible cross-sectional studies revealed no significant association between CAC and CRP [pooled OR: 1.03 (1.00, 1.06)]. Additionally, an insignificant association was found between CAC and CRP through meta-analysis on three eligible cohort studies [pooled OR: 1.05 (0.95, 1.15)] with no considerable heterogeneity across studies. Sensitivity analyses indicated that the meta-analysis models were robust. There was no evidence of publication bias.

CONCLUSION

Based on the meta-analysis findings, elevated levels of CRP did not emerge as a valuable prognostic maker for CAC incidence and progression prediction.

Predictors of long-term absence of coronary artery calcium in individuals with high blood pressure: results from the MESA study

BACKGROUND & AIMS

Individuals with high blood pressure (BP) have varying risks of cardiovascular events due to other coexisting factors. We aimed to identify the predictors of long-term absence of coronary artery calcium (CAC) in individuals with high BP, which is an indicator of healthy arterial aging and can guide preventive strategies.

METHODS

We analyzed data from participants with high BP (≥120/80 mm Hg) in the Multi-Ethnic Study of Atherosclerosis who had baseline CAC = 0 and underwent a second CAC scanning after 10 years. We used multivariable logistic regression to evaluate the association between various risk factors for atherosclerotic cardiovascular disease (ASCVD) and long-term CAC = 0. We also calculated the area under the receiver operating characteristic curve (AUC) to predict the phenotype of healthy arterial aging in this population.

RESULTS

We included 830 participants (37.6% male, mean ± SD age of 59.4 ± 8.7 years). During follow-up, 46.5% of participants (n = 386) had CAC = 0, and they were younger and had fewer metabolic syndrome components. Adding ASCVD risk factors to the demographic model (age, sex, and ethnicity) moderately increased the predictive value for long-term CAC = 0 (AUC: demographic model + ASCVD risk factors vs. demographic model alone, 0.653 vs. 0.597, p < .001; category net reclassification improvement = 0.104, p = .044; integrated discrimination improvement = 0.040, p < .001).

CONCLUSION

In individuals with high BP and initial CAC = 0, over 40% maintained CAC = 0 during a 10-year follow-up, which was associated with fewer ASCVD risk factors. These findings may have implications for preventive strategies in individuals with high BP.Clinical Trial registration number: The MESA was registered at clinical trials. gov as NCT00005487.KEY MESSAGESNearly half (46.5%) of individuals with high blood pressure (BP) maintained a long-term absence of coronary artery calcium (CAC) during a 10-year follow-up, and this was associated with a 66.6% lower risk of atherosclerotic cardiovascular disease (ASCVD) events compared to those who developed incident CAC.Individuals with high BP, who are usually assumed to have an increased risk of ASCVD, exhibit significant heterogeneity in their ASCVD risk; those who maintain CAC = 0 have a lower ASCVD risk.Adding overall ASCVD risk factors to demographic information resulted in a moderate improvement in predicting long-term CAC = 0.

Gender Differences in Subclinical Coronary Atherosclerosis in the Asian Population With a Coronary Artery Calcium Score of Zero

There is little evidence on whether gender difference influences the incidence of subclinical coronary atherosclerosis in Asian populations with a 0 score. In this study, we investigated the influence of age and gender on the extent of subclinical coronary atherosclerotic burden within a healthy Asian population with a 0 coronary artery calcium (CAC) score. A total of 934 participants (320 women and 614 men) from Taiwan's Han Chinese population with an initial CAC score of 0 were included in this study. They underwent 2 consecutive cardiac computed tomography scans over a clinical follow-up period of 4.35 ± 2.37 years. Clinical information and laboratory measurements were collected for analysis. Compared with the female group, the male group demonstrated significantly higher rates of subclinical CAC progression (27.4% vs 13.8%, p <0.001). Across the age group deciles (≤40, 41 to 50, 51 to 60, ≥61 years), the male group had a higher prevalence of subclinical CAC progression than the female group. For the subclinical CAC progression, the logistic regression model demonstrated that age, gender (male gender), cholesterol level, and follow-up period were statistically significant parameters. In conclusion, these findings support that a gender difference impacts the long-term natural course of subclinical coronary calcification conversion in women compared with men, suggesting that the gender-based effect on coronary CAC conversion plays an important role in subclinical coronary atherosclerosis risk stratification in personalized preventive medicine.

Comparing the pooled cohort equations and coronary artery calcium scores in a symptomatic mixed Asian cohort

Background

The value of pooled cohort equations (PCE) as a predictor of major adverse cardiovascular events (MACE) is poorly established among symptomatic patients. Coronary artery calcium (CAC) assessment further improves risk prediction, but non-Western studies are lacking. This study aims to compare PCE and CAC scores within a symptomatic mixed Asian cohort, and to evaluate the incremental value of CAC in predicting MACE, as well as in subgroups based on statin use.

Methods

Consecutive patients with stable chest pain who underwent cardiac computed tomography were recruited. Logistic regression was performed to determine the association between risk factors and MACE. Cohort and statin-use subgroup comparisons were done for PCE against Agatston score in predicting MACE.

Results

Of 501 patients included, mean (SD) age was 53.7 (10.8) years, mean follow-up period was 4.64 (0.66) years, 43.5% were female, 48.3% used statins, and 50.0% had no CAC. MI occurred in 8 subjects while 9 subjects underwent revascularization. In the general cohort, age, presence of CAC, and ln(Volume) (OR = 1.05, 7.95, and 1.44, respectively) as well as age and PCE score for the CAC = 0 subgroup (OR = 1.16 and 2.24, respectively), were significantly associated with MACE. None of the risk factors were significantly associated with MACE in the CAC > 0 subgroup. Overall, the PCE, Agatston, and their combination obtained an area under the receiver operating characteristic curve (AUC) of 0.501, 0.662, and 0.661, respectively. Separately, the AUC of PCE, Agatston, and their combination for statin non-users were 0.679, 0.753, and 0.734, while that for statin-users were 0.585, 0.615, and 0.631, respectively. Only the performance of PCE alone was statistically significant (p = 0.025) when compared between statin-users (0.507) and non-users (0.783).

Conclusion

In a symptomatic mixed Asian cohort, age, presence of CAC, and ln(Volume) were independently associated with MACE for the overall subgroup, age and PCE score for the CAC = 0 subgroup, and no risk factor for the CAC > 0 subgroup. Whilst the PCE performance deteriorated in statin versus non-statin users, the Agatston score performed consistently in both groups.

Assessing Agreement When Agreement Is Hard to Assess-The Agatston Score for Coronary Calcification

Method comparison studies comprised simple scatterplots of paired measurements, a 45-degree line as benchmark, and correlation coefficients up to the advent of Bland-Altman analysis in the 1980s. The Agatston score for coronary calcification is based on computed tomography of the heart, and it originated in 1990. A peculiarity of the Agatston score is the often-observed skewed distribution in screening populations. As the Agatston score has manifested itself in preventive cardiology, it is of interest to investigate how reproducibility of the Agatston score has been established. This review is based on literature findings indexed in MEDLINE/PubMed before 20 November 2021. Out of 503 identified articles, 49 papers were included in this review. Sample sizes were highly variable (10-9761), the main focus comprised intra- and interrater as well as intra- and interscanner variability assessments. Simple analysis tools such as scatterplots and correlation coefficients were successively supplemented by first difference, later Bland-Altman plots; however, only very few publications were capable of deriving Limits of Agreement that fit the observed data visually in a convincing way. Moreover, several attempts have been made in the recent past to improve the analysis and reporting of method comparison studies. These warrant increased attention in the future.

Novel nomogram for predicting coronary vulnerable plaque risk in patients with coronary artery disease

Objective: To develop and validate a nomogram for predicting coronary vulnerable plaques (VPs) in coronary artery disease (CAD) patients. Methods: One hundred seventy-seven CAD patients were enrolled in the training group. Another 60 patients were included for validation. Based on the identified independent risk factors, a nomogram model was developed and then validated. Results: Type 2 diabetes, hypertension, neutrophil-to-lymphocyte ratio, low-density lipoprotein cholesterol, MCP-1 and MMP-9 were found to be independent risk factors for coronary VPs. Both internal and external validation showed this nomogram had satisfactory discrimination via receiver operating characteristic curves, calibration via calibration plots and clinical application values via decision curve analysis. Conclusion: The authors established a nomogram model predicting coronary VP risk in CAD patients with promising clinical application value.

Intraindividual evaluation of effects of image filter function on image quality in coronary computed tomography angiography

Objectives

To evaluate whether applying image filters (smooth 3D+ and edge-2) improves image quality in coronary CT angiography (CCTA).

Methods

Ninety patients (routine group) with suspected coronary artery diseases based on 16-cm wide coverage detector CT findings were retrospectively enrolled at a chest pain center from December 2019 to September 2021. Two image filters, smooth 3D+ and edge-2 available on the Advantage Workstation (AW) were subsequently applied to the images to generate the research group (SE group). Quantitative parameters, including CT value, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), image sharpness and image quality score, and diagnostic accuracy were compared between the two groups.

Results

A total of 900 segments from 270 coronary arteries in 90 patients were analyzed. SNR, CNR, and image sharpness for vessels and image quality scores in the SE group were significantly better than those in the routine group (all p < 0.001). The SE group showed a slightly higher negative predictive value (NPV) on the left anterior descending artery and right coronary artery (RCA) stenosis evaluations, as well as total NPV. The SE group also showed slightly higher sensitivity and accuracy than the routine group on RCA stenosis evaluation.

Conclusion

The use of an image filter combining smooth 3D+ and edge-2 on an AW could improve the image quality of CCTA and increase radiologists' diagnostic confidence.

Predicting Patient No-Shows in an Academic Pediatric Neurology Clinic

Background: No-shows can negatively affect patient care. Efforts to predict high-risk patients are needed. Previously, our epilepsy clinic identified patients with 2 or more no-shows or late cancelations in the past 18 months as being at high risk for no-shows. Our objective was to develop a model to accurately predict the risk of no-shows among patients with epilepsy seen at our neurology clinic. Methods: Using electronic health record data, we developed a least absolute shrinkage and selection operator (LASSO)-regularized logistic regression model to predict no-shows and compared its performance with our neurology clinic's above-mentioned ad hoc rule. Results: The ad hoc rule identified 13% of patients seen at our neurology clinic as high-risk patients for no-shows and resulted in a positive predictive value of 38%. In comparison, our LASSO model resulted in a positive predictive value of 48%. Our LASSO model identified that lack of private insurance, inactive Epic MyChart, greater past no-show rates, fewer appointment changes before the appointment date, and follow-up appointments were more likely to result in no-shows. Conclusions: Our LASSO model outperformed the ad hoc rule used by our neurology clinic in predicting patients at high risk for no-shows. Social workers can use the no-show risk scores generated by our LASSO model to prioritize high-risk patients for targeted intervention to reduce no-shows at our neurology clinic.

Fractal Geometry Illustrated Left Atrial Appendage Morphology That Predicted Thrombosis and Stroke in Patients With Atrial Fibrillation

Background

This study aims to correlate the morphological complexity of left atrial appendage (LAA) with thrombosis and stroke in patients with atrial fibrillation (AF).

Methods

The training cohort consisted of 46 patients with AF (age 55.8 ± 7.2 years, 73.9% men) who were referred for radiofrequency catheter ablation. An independent validation cohort consisting of 443 patients with AF was enrolled for further verification. All patients in the training cohort underwent both transesophageal echocardiography (TEE) and enhanced computed tomography (CT). Fractal dimension (FD) analysis was performed to evaluate the morphological complexity of LAAs quantitatively. Clinical and imaging manifestations, FD of LAAs, and diagnostic accuracy were investigated and compared between patients with AF in both training and validation cohorts.

Results

In the training cohort, LAAs (n = 22) with thrombi had significantly higher FD than those without thrombi (n = 24) h 0.44 ± 0.07 vs. 2.35 ± 0.11, p = 0.003). Receiver-operating characteristic (ROC) analysis suggested that the diagnostic accuracy of FD combined with a CHA₂DS₂-VaSc score was significantly higher than that of the CHA₂DS₂-VaSc score alone in low- to moderate-risk patients with AF (area under the curve 0.8479 vs. 0.6958, p = 0.009). The results were also validated in an independent external validation cohort and demonstrated that increased FD was associated with stroke. Hemodynamic analysis revealed that LAAs with thrombi and high FD were prone to blood stasis and lower blood flow rate.

Conclusion

LAA morphological complexity is closely associated with thrombosis and stroke in patients with paroxysmal AF. A new risk assessment system combining CHA₂DS₂-VaSc score and FD has a higher diagnostic accuracy in predicting LAA thrombosis.

Coronary Computed Tomography Angiography Analysis of Calcium Content to Identify Non-culprit Vulnerable Plaques in Patients With Acute Coronary Syndrome

Background

Aside from the culprit plaque, the presence of vulnerable plaques in patients with acute coronary syndrome (ACS) may be associated with future cardiac events. A link between calcification and plaque rupture has been previously described.

Aim

To assess whether analysis of the calcium component of coronary plaques using CT angiography, coronary computed tomographic angiography (CCTA) can help to detect additional vulnerable plaques in patients with non-ST elevation myocardial infarction (NSTEMI).

Materials And Methods

Cross sectional study of consecutive patients referred for NSTEMI from 30 July to 30 August 2018 with CCTA performed before coronary angiography with systematic optical coherence tomography (OCT) analysis of all coronary arteries within 24 h of clinical onset of NSTEMI. Three types of plaques were defined: culprit plaques defined by angiography (vulnerable culprit plaques–VCP) – plaques with a fibrous cap thickness < 65 microns or thrombus in OCT (vulnerable non-culprit plaque–VNCP) – plaques with a fibrous cap thickness ≥ 65 microns in OCT (stable plaque–SP).

Results

A total of 134 calcified plaques were identified in 29 patients (73% male, 59 ± 14 years) with 29(22%) VCP, 28(21%) VNCP and 77(57%) SP. Using CCTA analysis of the calcium component, factors associated with vulnerable plaques were longer calcification length, larger calcification volume, lower calcium mass, higher Agatston score plaque-specific (ASp), presence of spotty calcifications and an intimal position in the wall. In multivariate analysis, ASp, calcification length and spotty calcifications were independently associated to vulnerable plaques. There was no difference between VCP and VNCP.

Conclusions

CCTA analysis of calcium component of the plaque could help to identify additional vulnerable plaques in NSTEMI patients.

Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification

Coronary artery calcium (CAC), which can be measured in various types of computed tomography (CT) examinations, is a hallmark of coronary artery atherosclerosis. However, despite the clinical value of CAC scores in predicting cardiovascular events, routine measurement of CAC scores is limited due to high cost, radiation exposure, and lack of widespread availability. It would be of great clinical significance if CAC could be predicted by electrocardiograms (ECGs), which are cost-effective and routinely performed during various medical checkups. We aimed to develop binary classification artificial intelligence (AI) models that predict CAC using only ECGs as input. Moreover, we aimed to address the generalizability of our model in different environments by externally validating our model on a dataset from a different institution. Among adult patients, standard 12-lead ECGs were extracted if measured within 60 days before or after the CAC scores, and labeled with the corresponding CAC scores. We constructed deep convolutional neural network models based on residual networks using only the raw waveforms of the ECGs as input, predicting CAC at different levels, namely CAC score ≥100, ≥400 and ≥1,000. Our AI models performed well in predicting CAC in the training and internal validation dataset [area under the receiver operating characteristics curve (AUROC) 0.753 ± 0.009, 0.802 ± 0.027, and 0.835 ± 0.024 for the CAC score ≥100, ≥400, and ≥1,000 model, respectively]. Our models also performed well in the external validation dataset (AUROC 0.718, 0.777 and 0.803 for the CAC score ≥100, ≥400, and ≥1,000 model, respectively), indicating that our model can generalize well to different but plausibly related populations. Model performance in terms of AUROC increased in the order of CAC score ≥100, ≥400, and ≥1,000 model, indicating that higher CAC scores might be associated with more prominent structural changes of the heart detected by the model. With our AI models, a substantial proportion of previously unrecognized CAC can be afforded with a risk stratification of CAC, enabling initiation of prophylactic therapy, and reducing the adverse consequences related to ischemic heart disease.

Artificial Intelligence Advancements in the Cardiovascular Imaging of Coronary Atherosclerosis

Coronary artery disease is a leading cause of death worldwide. There has been a myriad of advancements in the field of cardiovascular imaging to aid in diagnosis, treatment, and prevention of coronary artery disease. The application of artificial intelligence in medicine, particularly in cardiovascular medicine has erupted in the past decade. This article serves to highlight the highest yield articles within cardiovascular imaging with an emphasis on coronary CT angiography methods for % stenosis evaluation and atherosclerosis quantification for the general cardiologist. The paper finally discusses the evolving paradigm of implementation of artificial intelligence in real world practice.

Use of Coronary Computed Tomography Angiography to Screen Hospital Employees with Cardiovascular Risk Factors

The objective of this study was to determine how coronary computed tomography angiography (CCTA) can be employed to detect coronary artery disease in hospital employees, enabling early treatment and minimizing damage. All employees of our hospital were assessed using the Framingham Risk Score. Those with a 10-year risk of myocardial infarction or death of >10% were offered CCTA; the Coronary Artery Disease Reporting and Data System (CAD-RADS) score was the outcome. A total of 3923 hospital employees were included, and the number who had received CCTA was 309. Among these 309, 31 (10.0%) had a CAD-RADS score of 3-5, with 10 of the 31 (32.3%) requiring further cardiac catheterization; 161 (52.1%) had a score of 1-2; and 117 (37.9%) had a score of 0. In the multivariate logistic regression, only age of ≥ 55 years (p < 0.05), hypertension (p < 0.05), and hyperlipidemia (p < 0.05) were discovered to be significant risk factors for a CAD-RADS score of 3-5. Thus, regular and adequate control of chronic diseases is critical for patients, and more studies are required to be confirmed if there are more significant risk factors.

Severe, but not mild to moderate, non-alcoholic fatty liver disease associated with increased risk of subclinical coronary atherosclerosis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is associated with high risk of cardiovascular disease. The prevalence is increasing to 45-65% in the general population with routine health check-up, and most subjects have the mild degree NAFLD in recent years. Moreover, there are no studies on the association between NAFLD severity and coronary atherosclerosis in the real-world setting by ultrasonography.

METHODS

The aim of this study was to determine the relationship between the severity of NAFLD and subclinical coronary atherosclerosis. Overall, 817 subjects meet criteria for NAFLD were enrolled in the retrospective cohort study (155 subjects were excluded). The severity of NAFLD was divided into the normal, mild, moderate and severe degree based on the finding of abdominal ultrasonography. The assessment of coronary atherosclerosis was based on CAC scan/coronary CT angiography finding in terms of CAC score ≧ 100, CAC score ≧ 400, CAD-RADS ≧ 3 and presence of vulnerable plaque(s).

RESULTS

A significant linear trend was observed between the severity of NAFLD and subclinical coronary atherosclerosis. Compared with the reference group (including normal, mild, and moderate NAFLD), severe degree NAFLD was the independently associated risk of subclinical coronary atherosclerosis in term of CAC score ≧ 100, CAC score ≧ 400, CAD-RADS ≧ 3 and presence of vulnerable plaque(s) based on binary logistic regression after adjustment for FRS score and body fat percentage.

CONCLUSIONS

Severe degree, but not mild to moderate, was associated with high risk of subclinical coronary atherosclerosis, independently of FRS score and body-fat percentage.