UNASSIGNED: There are limited data on the feasibility of Impella-assisted percutaneous coronary intervention (PCI) in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR).
UNASSIGNED: To assess the feasibility of the Impella-assisted PCI in patients with severe symptomatic AS, we retrospectively reviewed the medical records to identify patients who were electively admitted for Impella-assisted PCI with a subsequent TAVR at Weill Cornell Medical Center from 2016 to 2021.
UNASSIGNED: During the study period, 15 patients were identified to be eligible for the study, but the Impella failed to cross the aortic valve in 1 patient despite a concomitant balloon aortic valvuloplasty requiring a switch to an intra-aortic balloon pump to assist PCI. A total of 14 patients underwent successful PCI with the Impella CP and were included in the analysis. The median age was 89 years, and women accounted for 43% of the cohort. The median aortic valve area and mean gradient were 0.85 cm2 and 40 mm Hg, respectively, with a median left ventricular ejection fraction of 51%. The median SYNTAX score was 13. The left main stent was placed in 6 patients (43%), with a rotational atherectomy performed in 10 patients (71%). The balloon aortic valvuloplasty was performed in 2 patients before Impella placement. The TAVR was performed in all 14 patients on a median post-Impella-assisted PCI day of 25. No procedural complications were noted post-TAVR with no in-hospital or 30-day death.
UNASSIGNED: In this single-center study of patients with severe AS, the elective Impella-assisted high-risk PCI was feasible and safe before TAVR in selected patients.

BACKGROUND: Metabolic syndrome (MetS) can increase the risk of morbidity and mortality of cardiovascular disease and obstructive coronary artery disease (OCAD), which usually have a poor prognosis. This study aimed to explore the impact of MetS on left ventricular (LV) deformation and function in OCAD patients and investigate the independent factors of impaired LV function and deformation.
METHODS: A total of 121 patients with OCAD and 52 sex- and age-matched controls who underwent cardiac magnetic resonance scanning were enrolled in the study. All OCAD patients were divided into two groups: OCAD with MetS [OCAD(MetS+), n = 83] and OCAD without MetS [OCAD(MetS-), n = 38]. LV functional and global strain parameters were measured and compared among the three groups. Multivariable linear regression analyses were constructed to investigate the independent factors of LV impairment in OCAD patients. Logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to test the prediction efficiency of MetS for LV impairment.
RESULTS: From controls to the OCAD(MetS-) group to the OCAD(MetS+) group, LV mass (LVM) increased, and LV global function index (LVGFI) and LV global longitudinal peak strain (GLPS) decreased (all p < 0.05). Compared with the OCAD(MetS-) group, the LV GLPS declined significantly (p = 0.027), the LVM increased (p = 0.006), and the LVGFI decreased (p = 0.043) in the OCAD(MetS+) group. After adjustment for covariates in OCAD patients, MetS was an independent factor of decreased LV GLPS (β = - 0.211, p = 0.002) and increased LVM (β = 0.221, p = 0.003). The logistic multivariable regression analysis and ROC analysis showed that combined MetS improved the efficiency of predicting LV GLPS reduction (AUC = 0.88) and LVM (AUC = 0.89) increase.
CONCLUSIONS: MetS aggravated the damage of LV deformation and function in OCAD patients and was independently associated with LV deformation and impaired LV strain. Additionally, MetS increased the prediction efficiency of increased LVM and decreased LV GLPS. Early detection and intervention of MetS in patients with OCAD is of great significance.

BACKGROUND: The endothelial nitric oxide synthase (eNOS) gene deficiency is known to cause impaired coronary vasodilating capability in animal models. In the general clinical population, the eNOS gene polymorphisms, able to affect eNOS activity, were associated with cardiometabolic risk features and prevalence of coronary artery disease (CAD).
OBJECTIVE: To investigate the association of eNOS Glu298Asp gene polymorphism, cardiometabolic profile, obstructive CAD and inducible myocardial ischemia in patients with suspected stable CAD.
METHODS: A total of 506 patients (314 males; mean age 62 ± 9 years) referred for suspected CAD was enrolled. Among these, 325 patients underwent stress ECG or cardiac imaging to assess the presence of inducible myocardial ischemia and 436 patients underwent non-invasive computerized tomography or invasive coronary angiography to assess the presence of obstructive CAD. Clinical characteristics and blood samples were collected for each patient.
RESULTS: In the whole population, 49.6% of patients were homozygous for the Glu298 genotype (Glu/Glu), 40.9% heterozygotes (Glu/Asp) and 9.5% homozygous for the 298Asp genotype (Asp/Asp). Obstructive CAD was documented in 178/436 (40.8%) patients undergoing coronary angiography while myocardial ischemia in 160/325 (49.2%) patients undergoing stress testing. Patients with eNOS Asp genotype (Glu/Asp + Asp/Asp) had no significant differences in clinical risk factors and in circulating markers. Independent predictors of obstructive CAD were age, gender, obesity, and low HDL-C. Independent predictors of myocardial ischemia were gender, obesity, low HDL-C and Asp genotype. In the subpopulation in which both stress tests and coronary angiography were performed, the Asp genotype remained associated with increased myocardial ischemia risk after adjustment for obstructive CAD.
CONCLUSIONS: In this population, low-HDL cholesterol was the only cardiometabolic risk determinant of obstructive CAD. The eNOS Glu298Asp gene polymorphism was significantly associated with inducible myocardial ischemia independently of other risk factors and presence of obstructive CAD.

BACKGROUND: Cardiovascular diseases are the leading cause of morbidity and mortality in patients with end-stage renal disease.
OBJECTIVE: This study aimed to assess the prognostic value of high-sensitivity cardiac troponin T (hs-cTnT) in identifying patients with obstructive coronary artery disease (CAD) among patients on hemodialysis listed for kidney transplantation.
METHODS: The study prospectively enrolled consecutive adult hemodialysis patients listed for kidney transplantation. They underwent laboratory tests and a standardized set of imaging and functional tests, including coronary angiography, according to patient characteristics.
RESULTS: The study included 100 consecutive patients (72 men)at a median age of 56.5 years. Ultimately, 48% of the patients were diagnosed with obstructive CAD. Age and plasma hs-cTnT levels predicted the diagnosis of obstructive CAD (OR, 1.13; 95% CI, 1.08-1.20; P < 0.001 and OR, 1.03; 95% CI, 1.01-1.05; P = 0.001, respectively). The calculated cut-off value for age was 53 years, which showed sensitivity of 87.5% and specificity of 76.9% for obstructive CAD diagnosis. The calculated value for hs-cTnT was 0.067 ng/ml, which showed sensitivity of 61.4% and specificity of 82.2% for the detection of obstructive CAD. In patients aged >52 years, 79.2% were diagnosed with obstructive CAD. However, in the group of patients ≤52 years and with hs-cTnT >0.069 ng/ml, the incidence of obstructive CAD was significantly higher than in the group with hs-cTnT level ≤0.069 ng/ml.
CONCLUSIONS: Baseline hs-cTnT level is a useful prognostic biomarker in the diagnosis of obstructive CAD in hemodialysis patients listed for kidney transplantation.

High-sensitivity troponin (hsTn) has a very high diagnostic accuracy for myocardial infarction (MI), and patients who were formerly diagnosed with unstable angina (UA) are being reclassified as having NSTEMI in the era of hsTn. This paradigm shift has changed the clinical features of UA, which remain poorly characterized, specifically the occurrence of obstructive coronary artery disease (CAD) and the need for myocardial revascularization. The main purpose of this study was to clinically characterize contemporary UA patients, assess predictors of obstructive CAD, and develop a risk model to predict significant CAD in this population.
We conducted a retrospective cohort study of 742 patients admitted to the hospital with UA. All patients underwent coronary angiography. The endpoint of the study was the presence of obstructive CAD on angiography. The cohort was divided into two groups: patients with significant coronary artery disease (CAD+) and those without CAD (CAD-). We developed a score (UA CAD Risk) based on the multivariate model and compared it with the GRACE, ESC, and TIMI risk scores using ROC analysis.
Obstructive CAD was observed on angiography in 53% of the patients. Age, dyslipidemia, troponin level, male sex, ST-segment depression, and wall motion abnormalities on echocardiography were independent predictors of obstructive CAD. hsTn levels (undetectable vs. nonsignificant detection) had a negative predictive value of 81% to exclude obstructive CAD. We developed a prediction model with obstructive CAD as the outcome (AUC: 0.60).
In a contemporary UA cohort, approximately 50% of the patients did not have obstructive CAD on angiography. Commonly available cardiac tests at hospital admission show limited discrimination power in identifying patients at risk of obstructive CAD. A revised diagnostic and etiology algorithm for patients with UA is warranted.

UNASSIGNED: Due to the limitations of current methods for detecting obstructive coronary artery disease (CAD), many individuals are mistakenly or unnecessarily referred for coronary angiography (CAG).
UNASSIGNED: Our goal is to create a comprehensive database of heart sounds in CAD and develop accurate deep learning algorithms to efficiently detect obstructive CAD based on heart sound signals. This will enable effective screening before undergoing CAG.
UNASSIGNED: We included 320 subjects suspected of CAD who underwent CAG. We employed advanced filtering techniques and state-of-the-art deep learning models (VGG-16, 1D CNN, and ResNet18) to analyze the heart sound signals and identify obstructive CAD (defined as at least one ≥50 % stenosis). To assess the performance of our models, we prospectively recruited an additional 80 subjects for testing.
UNASSIGNED: In the test set, VGG-16 exhibited the highest performance with an area under the ROC curve (AUC) of 0.834 (95 % CI, 0.736-0.930), while ResNet-18 and CNN-7 achieved AUCs of only 0.755 (95 % CI, 0.614-0.819) and 0.652 (95 % CI, 0.554-0.770) respectively. VGG-16 demonstrated a sensitivity of 80.4 % and specificity of 86.2 % in the test set. The combined diagnostic model of VGG and DF scores achieved an AUC of 0.915 (95 % CI: 0.855-0.974), and the AUC for VGG combined with PTP scores was 0.908 (95 % CI: 0.845-0.971). The sensitivity and specificity of VGG-16 exceeded 0.85 in patients with coronary artery occlusion and those with 3 vascular lesions.
UNASSIGNED: Our deep learning model, based on heart sounds, offers a non-invasive and efficient screening method for obstructive CAD. It is expected to significantly reduce the number of unnecessary referrals for downstream screening.

The addition of coronary artery calcium score (CACS) to prediction models has been verified to improve performance. Machine learning (ML) algorithms become important medical tools in an era of precision medicine, However, combined utility by CACS and ML algorithms in hypertensive patients to forecast obstructive coronary artery disease (CAD) on coronary computed tomography angiography (CCTA) is rare.
This retrospective study was composed of 1,273 individuals with hypertension and without a history of CAD, who underwent dual-source computed tomography evaluation. We applied five ML algorithms, coupled with clinical factors, imaging parameters, and CACS to construct predictive models. Moreover, 80% individuals were randomly taken as a training set on which 5-fold cross-validation was done and the remaining 20% were regarded as a validation set.
16.7% (212 out of 1,273) of hypertensive patients had obstructive CAD. Extreme Gradient Boosting (XGBoost) posted the biggest area under the receiver operator characteristic curve (AUC) of 0.83 in five ML algorithms. Continuous net reclassification improvement (NRI) was 0.55 (95% CI (0.39-0.71), p < 0.001), and integrated discrimination improvement (IDI) was 0.04 (95% CI (0.01-0. 07), p = 0.0048) when the XGBoost model was compared with traditional Models. In the subgroup analysis stratified by hypertension levels, XGBoost still had excellent performance.
The ML model incorporating clinical features and CACS may accurately forecast the presence of obstructive CAD on CCTA among hypertensive patients. XGBoost is superior to other ML algorithms.

UNASSIGNED: We assessed differences in risk profile and 3-year outcome between patients undergoing percutaneous coronary intervention (PCI) for premature and non-premature coronary artery disease (CAD).
UNASSIGNED: The prevalence of CAD increases with age, yet some individuals develop obstructive CAD at younger age.
UNASSIGNED: Among participants in four randomized all-comers PCI trials, without previous coronary revascularization or myocardial infarction (MI), we compared patients with premature (men <50 years; women <55 years) and non-premature CAD. Various clinical endpoints were assessed, including multivariate analyses.
UNASSIGNED: Of 6,171 patients, 887 (14.4%) suffered from premature CAD. These patients had fewer risk factors than patients with non-premature CAD, but were more often smokers (60.7% vs. 26.4%) and overweight (76.2% vs. 69.8%). In addition, premature CAD patients presented more often with ST-segment elevation MI and underwent less often treatment of multiple vessels, and calcified or bifurcated lesions. Furthermore, premature CAD patients had a lower all-cause mortality risk (adj.HR: 0.23, 95%-CI: 0.10-0.52; p < 0.001), but target vessel revascularization (adj.HR: 1.63, 95%-CI: 1.18-2.26; p = 0.003) and definite stent thrombosis risks (adj.HR: 2.24, 95%-CI: 1.06-4.72; p = 0.034) were higher. MACE rates showed no statistically significant difference (6.6% vs. 9.4%; adj.HR: 0.86, 95%-CI: 0.65-1.16; p = 0.33).
UNASSIGNED: About one out of seven PCI patients was treated for premature CAD. These patients had less complex risk profiles than patients with non-premature CAD; yet, their risk of repeated revascularization and stent thrombosis was higher. As lifetime event risk of patients with premature CAD is known to be particularly high, further efforts should be made to improve modifiable risk factors such as smoking and overweight.
UNASSIGNED: (TWENTE I, clinicaltrials.gov: NCT01066650), DUTCH PEERS (TWENTE II, NCT01331707), BIO-RESORT (TWENTE III, NCT01674803), and BIONYX (TWENTE IV, NCT02508714).

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with a markedly increased prevalence of coronary artery disease (CAD). Radiomics features of pericoronary adipose tissue (PCAT) were correlated with inflammation, which may have potential value in the prediction of CAD.
OBJECTIVE: To determine whether radiomics analysis of PCAT captured by plain computed tomography (CT) could predict obstructive CAD in patients with T2DM.
METHODS: The study included 155 patients with T2DM with suspected CAD between January 2020 and December 2021. Volumes of right coronary artery of 10-50 mm were delineated in the plain CT to extract radiomics features and PCAT CT attenuation (PCATa). Least absolute shrinkage and selection operator was used to select the useful radiomics features to calculate the radiomics score (Rad-score). Univariate and multivariable logistic regression were applied to select independent predictors. The predictive performance was evaluated by the area under the receiver operating characteristics curve (AUC).
RESULTS: Rad-score (per 0.1 increments: odds ratio [OR] = 1.297; P < 0.001), coronary artery calcium score (CACS) (OR = 1.003; P = 0.037), and sex (OR = 3.245; P = 0.026) were identified as independent predictors for obstructive CAD. Rad-score (AUC = 0.835) outperformed CACS (AUC = 0.780), sex (AUC = 0.665), and PCATa (AUC = 0.550) in predicting obstructive CAD (P = 0.017 and 0.003 for Rad-score vs. sex and PCATa, respectively); however, the improvement between Rad-score and CACS had no statistical significance (P = 0.490).
CONCLUSIONS: Plain CT-derived Rad-score may be used as a preliminary screening tool for obstructive CAD in patients with T2DM.

UNASSIGNED: The early diagnosis of coronary artery disease (CAD) enables early intervention for the modifiable risk factors of the disease. Coronary artery calcification (CAC) detected incidentally on standard noncontrast chest computed tomography (CT) provides an opportunity for the early diagnosis of CAD. The purpose of this study was to demonstrate that CAC should be routinely reported when evaluating thoracic CT examinations. Routine reporting of CAC will contribute to the early diagnosis of CAD.
UNASSIGNED: The present study included 279 patients who underwent conventional coronary angiography (CAG) and CT within one month before undergoing CAG. The CAG and CT images of the patients were evaluated retrospectively. The levels of coronary artery stenosis were determined in reference to the CAG images. The CAC scores of the patients were calculated using the Weston method based on their chest CT images.
UNASSIGNED: The mean age of the patients was 63.2 ± 11.5 (range, 41-93) years, and 172 (61.6%) of them were men. The Weston score (WS) was 0 in 18.9% of the patients with obstructive CAD (OCAD), whereas it was ≥ 7 in 27.9% of patients. All patients with a WS of ≥ 7 had OCAD. All patients without luminal stenosis or < 50% stenosis had a WS of < 7.
UNASSIGNED: The CAC score is useful for the diagnosis of CAD and OCAD. If CAC is identified on standard noncontrast chest CT, it should be scored and reported accordingly. The WS can be used for CAC scoring.