Risultati per: Intervalli di sorveglianza per Aneurisma Aorta Addominale (AAA)

Objectives
Ascending aorta dilatation (AAD) has been suggested as a surrogate marker for vascular organ damage in the hypertensive population. However, limited data are available on AAD in normotensive individuals. This study aims to preliminarily explore the correlation between ascending aorta (AAO) and other established clinically significant target organ damage parameters and to investigate the possible risk factors of AAD in the non-diabetic normotensive individuals.

Design
Our study has a cross-sectional design.

Setting
All participants were recruited from the inpatient and outpatient departments of our hospital.

Participants
We recruited 634 normotensive participants (52.26±16.22 years, 39.43% male) who underwent both ambulatory blood pressure monitoring (ABPM) and echocardiography. The whole study population was divided into AAD and non-AAD groups according to age-gender-specific criteria. The baseline mean blood pressure (BP) of the two groups was 126.92/77.72 and 124.16/77.61 mm Hg, respectively.

Primary and secondary outcome measures
The relationship between AAO and other acknowledged cardiac damage indicators, as well as the associations of AAD with ABPM indexes in the non-diabetic normotensive individuals.

Results
We observed that AAO exhibited a significant correlation with left ventricular mass index (β=1.905, p

Circulation, Volume 150, Issue Suppl_1, Page A4143405-A4143405, November 12, 2024. Background:Pulmonary hypertension (PH) and secondary right ventricle dysfunction is present in 20% of adults with coarctation of aorta (COA) based on echocardiographic studies. There are limited data about invasive hemodynamic characterization of PH in COA. The purpose of this study was to delineate the clinical features, hemodynamics, and outcomes of PH in COA.Method:Retrospective cohort study of adults with repaired COA that underwent right heart catheterization (RHC). PH was defined as pulmonary artery (PA) mean pressure >20 mmHg, and PH was classified as isolated precapillary PH and combined pre/postcapillary PH.Results:Of 99 COA patients that underwent RHC, 57 (58%) had PH. Of the patients with PH, 14 (25%) had isolated precapillary PH while 43 (75%) had postcapillary PH with or without precapillary disease. The correlates of PH were PA compliance (adjusted OR 0.79, 95% CI 0.71-0.86 per 1 ml/mmHg), left atrial reservoir strain (adjusted OR 0.95, 95% CI 0921-0.98 per 1%), and atrial fibrillation (adjusted OR 2.18, 95% CI 1.20-13.5). Higher PA mean pressure was associated with risk of cardiovascular events (adjusted HR 1.04, 95% CI 1.02-1.06 per 1 mmHg) and all-cause mortality (adjusted HR 1.05, 95% CI 1.02-1.08 per 1 mmHg).Conclusions:PH was present in over half of adults with COA referred for RHC, and one-quarter of the patients with PH presented with isolated precapillary PH suggesting an underlying PA vascular dysfunction as a contributing mechanism. Further studies are required to determine optimal therapies and strategies for prevention and treatment of PH in this population.

Circulation, Volume 150, Issue Suppl_1, Page A4144473-A4144473, November 12, 2024. Background:We hypothesized that patients with coarctation of aorta (COA) and obesity would have more advanced cardiovascular remodeling and impaired aerobic capacity compared to COA patients without obesity. The purpose of this study was to assess the relationship between obesity, cardiovascular remodeling, and aerobic capacity in adults with repaired COA.Methods:The study comprised of 3 groups: (1) Obese COA group (n=177) (COA patients with body mass index [BMI] >30 kg/m2); (2) Non-obese COA group (n=572) (COA patients with BMI ≤30 kg/m2); (3) Control group (n=59) (subjects without structural heart disease and BMI ≤30 kg/m2). Cardiovascular remodeling was assessed using the following indices: (1) Arterial stiffness – total arterial compliance index (TACI). (2) Left ventricular hypertrophy – LV mass (LVM) and relative wall thickness (RWT). (3) LV diastolic function – Doppler-derived estimated LV end-diastolic pressure (LVEDP) and Tau. (4) Right ventricular-pulmonary artery coupling – RV free wall strain and right ventricle systolic pressure (RVFW/RVSP). Aerobic capacity was assessed using predicted peak oxygen consumption (VO2).Results:The obese COA group had higher LVM, RWT, LVEDP, and Tau, well as lower RVFWS/RVSP, TACI and peak VO2 compared to non-obese COA group and controls. There was a correlation between BMI and LVM (r=0.39, p

Circulation, Volume 150, Issue Suppl_1, Page A4147066-A4147066, November 12, 2024. Atherosclerosis, a complex process involving chronic systemic inflammation, endothelial dysfunction, retention of lipoproteins, plaque formation in large and medium-sized arteries, is one of the most common causes of morbidity and mortality. Octacosanol, a very long chain saturated (C28) aliphatic alcohol is a major active ingredient in the Policosanol, which is extracted from plants like sugar cane and wheat germ. Policosanol has been proposed as dietary supplement for obesity and for lowering serum lipids. Previous animal studies have shown that both Policosanol and Octacosanol can significantly ameliorate formation of atherosclerotic lesions. To further explore the possible mechanism of Octacosanol on the formation of atherosclerosis, we examined the anti-inflammatory effects of Octacosanol on HAEC treated with LPS at 100ng/ml FBS-free cell culture medium. LPS treatment significantly enhanced human monocyte (THP1) adherence to HAEC cells in time-dependent and dose-dependent style, but Octacosanol at 1.25 or 2.5 µM markedly blocked the adhesion of THP1 to HAEC. ELISA showed that LPS can significantly increase the expression of pro-inflammatory cytokines and adhesion molecules by HAEC at 100ng/ml within 4 hours. LPS stimulated more than 3-fold the release of IL-6, IL-8, MCP-1 at 4 hours. By flow cytometry and ELISA, LPS markedly increased the expression of PE-Selectin and VCAM-1. Pretreatment of HAEC with Octacosanol (1.25µM or 2.5µM) significantly reduced the release of inflammatory cytokines, such as MCP-1(p

Circulation, Volume 150, Issue Suppl_1, Page A4141180-A4141180, November 12, 2024. Purpose:Primary prevention of cardiovascular (CV) disease relies on accurate risk estimation. The coronary artery calcium score (CAC) can be measured on routine chest computed tomography (CT); however, it is unclear whether the heart and thoracic aorta regions on CT can provide additional information about future risk beyond calcium and risk factors.Methods:We applied the open-source TotalSegmentator tool to extract heart and thoracic aorta volumes from 27,943 non-contrast non-ECG gated chest CTs from 17,241 National Lung Screening Trial participants. We used the segmented volumes from 10,356 participants as input to train a new 3D Densenet169 deep learning model to predict 12-year CV mortality. Independent testing was performed in 5,165 individuals not used for model training with no history of type 2 diabetes, myocardial infarction, or stroke (eligible for primary prevention). The deep learning score was compared to a regression model using demographics, smoking, BMI, comorbidities, and the radiologist’s findings from the CT. We stratified the CAC and deep learning scores into high vs. low-risk groups using a CAC >100 and deep learning >10% risk threshold, respectively.Results:In the independent testing dataset, (N=5165; median age 60.0±8.0 years; 62.6% male), 3.3% died of CV disease. The deep learning score had higher discrimination for CV mortality than risk factors and CT findings (deep learning AUC 0.72 [0.68,0.76] vs. baseline AUC 0.66 [0.61,0.69], p < 0.001). Similar results were found for secondary outcomes of fatal myocardial infarction and fatal stroke. In a subset of 2,972 testing set individuals with measured CAC, those with high CAC and a high deep learning score had a 10.8% rate of 12-year CV mortality, higher than those with high CAC alone (4.1%, p

Circulation, Volume 150, Issue Suppl_1, Page A4143933-A4143933, November 12, 2024. Background:Organ size and body size relations are often non-linear (allometric). However, allometric relations for thoracic aorta are poorly understood and current practice is based on linear (ratiometric) indexation of aortic dimensions, which can provide misleading information in individual patients. Assessing allometric relationships can have important implications for the detection of aneurysms, particularly at the extremes of body size.Methods:A U-Net convolutional neural network (CNN) segmentation architecture was trained, validated, and used to segment the ascending aorta (AA) and derive its maximum cross-sectional dimensions using MRI scans obtained from 49,193 UK Biobank participants. Sex-adjusted allometric (log-log) models were used to derive allometric exponents describing the relationship of AA size (diameter and cross-sectional area) to body size (height and BSA) in a healthy reference subgroup (n=3,972). Prognostic associations with all-cause mortality and aneurysm complications were then assessed in the entire population over a median follow-up of 66 months.Results:Relationships between AA diameter or area and BSA were highly non-linear (Table 1) and exhibited significant differences between males and females (P for interaction=0.013), precluding the use of a single exponent for both sexes. In contrast, a quasi-linear relationship was found for aortic area and body height (exponent=0.98), making simple ratiometric indexation allometrically adequate. Moreover, no differences in this allometric relation were found between men and women (P for interaction=0.32), indicating its suitability regardless of sex. In contrast, ratiometric diameter/height, diameter/BSA, or area/BSA indexation provided markedly and systematically biased prevalence estimates for aortic dilation, misclassifying many individuals at the extremes of body size (Figure). Finally, the use of the linear area/height ratio was consistently predictive of death and aneurysm complications in the overall population and provided the highest C-index for aneurysm complications regardless of body size (Table 2).Conclusions:In contrast to all other indexation methods, the linear AA area/height ratio is a practical, allometrically correct, and most informative aortic size index, and can be utilized equally in men and women. This should guide strategies for aneurysm detection and decision making in clinical practice and future studies.

Circulation, Volume 150, Issue Suppl_1, Page A4140771-A4140771, November 12, 2024. Introduction:Severe atherosclerosis of the aorta poses a significant risk of embolism to peripheral organs. Non-obstructive general angioscopy (NOGA) offers detailed observation of atherosclerosis in the aorta. Cholesterol crystals (CCs) can disperse into the blood from ruptured plaques (RPs) and cause inflammation. However, the relationship between LDL cholesterol levels and the detection rate of CCs from RPs has not been fully elucidated.Aims:This study aims to evaluate the utility of NOGA in identifying high-risk aortic plaques for CCs detection and to examine the influence of LDL cholesterol levels on this detection rate.Methods:We investigated 105 consecutive patients with coronary artery disease who underwent NOGA between September 2021 and November 2023. Blood samples were taken from a total of 248 NOGA-derived atheromatous plaques in the infrarenal abdominal aorta. The presence of CCs was assessed using polarized light microscopy and the filter paper rinse method. The CCs detection rates were analyzed by stratifying patients based on LDL cholesterol levels (divided at 100 mg/dL) and the presence of RPs.Results:The mean age was 67 years; 82.9% were male, 41.0% had diabetes, 99.1% had dyslipidemia, and 78.1% had hypertension. RPs accounted for 52.8％ of the sampling sites, thrombi for 13.3%, yellow plaque for 21.0%, and ulcer and fissure for 12.9%. The overall CCs detection rate was 22.6% (n = 56/248). The detection rates were 1.7% (n = 2/117) in plaques without RPs and 41.2% (n = 54/131) in plaques with RPs (p < 0.001). Among those with LDL levels < 100 mg/dL, the detection rate was 19.3% (n = 41/213), whereas it was 42.9% (n = 15/35) in those with LDL levels ≥ 100 mg/dL (p = 0.039). Specifically, the detection rates were 1.9% (n = 2/104) in plaques without RPs and LDL < 100 mg/dL, 9.1% (n = 1/11) in plaques without RPs and LDL ≥ 100 mg/dL, 36.8% (n = 39/106) in plaques with RPs and LDL < 100 mg/dL, and 58.3% (n = 14/24) in plaques with RPs and LDL ≥ 100 mg/dL (p < 0.001).Conclusions:Identifying plaque types using NOGA, combined with LDL cholesterol levels, is useful for detecting high-risk aortic plaques prone to CCs. The combination significantly enhances the predictive capability for CCs detection.

Circulation, Volume 150, Issue Suppl_1, Page A4122612-A4122612, November 12, 2024. Background:Current fetal echocardiographic (F-echo) metrics have inadequate specificity for confident prediction of neonatal critical coarctation of the aorta (CoA). Using single-center data, our machine learning model for the prediction of fetal CoA demonstrated improved accuracy compared to published F-echo metrics for critical CoA assessment. External validation of this model is needed.Aim:Validate a machine learning F-echo predictive model for CoA with an external patient cohort.Methods:Initial model training and testing were performed using retrospective single center data on 9 F-echo measurements for patients with prenatal concern for CoA. A random forest classifier with 80:20 split and 5-fold cross-validation predicted CoA intervention within 30 days of life. A SHapley Additive exPlanations (SHAP) analysis assessed the marginal contribution of each feature. The model was retrained using the 5 most influential F-echo features. External validation for this model was then performed using patients with prenatal concern for CoA retrospectively collected at a partner institution.Results:Inclusion criteria were met by 132 patients in the initial cohort and 64 patients in the external validation cohort, of whom 44% (n=58) and 25% (n=16) respectively had CoA requiring intervention. SHAP analysis for both cohorts demonstrated transverse to descending aorta angle as the most influential feature, followed by ascending to descending aorta angle (Figure 1A). Using internal cross-validation on the initial cohort, the area under the receiver operating characteristic curve (AUC) was 0.93 ± 0.05 (sensitivity 0.97, specificity 1.0) with an F1 score of 0.97 ± 0.03. Validation of the model with the external cohort produced an AUC of 0.87 (sensitivity 0.81, specificity 1.0) and an F1 of 0.90 (Figure 1B).Conclusions:A random forest classifier using F-echo features predicted neonatal critical CoA with higher accuracy than previously published metrics. The model maintained high accuracy when validated with an external patient cohort. Arch angles most significantly impacted the model’s accuracy. Future directions include prospective validation and converting the model to a distributable clinical calculator.

Circulation, Volume 150, Issue Suppl_1, Page AOr108-AOr108, November 12, 2024. Background:Addition of resuscitative endovascular balloon occlusion of the aorta (REBOA) to automated head-up position (AHUP) cardiopulmonary resuscitation (CPR), the combination of active compression decompression CPR, an impedance threshold device, and controlled gradual elevation of the head and thorax, increases cerebral perfusion pressure. Optimal management of REBOA deflation after prolonged AHUP-CPR and ROSC is unknown.Hypothesis:We hypothesized that partial deflation of REBOA, rather than full deflation after ROSC, would result in better hemodynamic parameters.Aims:To compare hemodynamic parameters 1 minute before and 1 minute after complete (100%) versus partial (50%) REBOA deflation after prolonged AHUP-CPR and ROSC.Methods:Yorkshire pigs weighing ∼40 kg were anesthetized and ventilated. After 10 minutes of untreated ventricular fibrillation, AHUP-CPR was started and continued for a median time of 44 minutes. After ROSC, REBOA deflation was initiated in two ways: complete (100%) or partial (50%) deflation over 5 seconds. The following hemodynamic parameters were measured 1 minute before and 1 minute after deflation: mean aortic pressure (MAP), cerebral perfusion pressure (CerPP), and coronary perfusion pressure (CorPP). Data, in mmHg, are presented as mean ± SD, and compared using a paired t-test.Results:13 pigs were included, with 8 pigs in the 100% deflation group and 5 in the 50% deflation group. After ROSC in the 100% deflation group, MAP was 81.5±36.0 before deflation vs. 43.0±14.4 after (p=0.01), whereas in the 50% deflation group, MAP was 90.5±33.0 vs. 83.4±33.3 (p=0.02). CerPP was 72.3±34.4 before deflation vs. 35.9±14.6 (p=0.01) in the 100% deflation group, and 84.6±31.2 vs. 77.6±31.8 (p=0.02) with 50% deflation. Similarly, CorPP was 74.1±37.3 before deflation vs. 36.1±15.8 (p=0.01) after in the 100% deflation group, and 83.0±32.7 vs. 76.1±33.0 (p=0.02) in the 50% deflation group. The differences from before to after deflation were markedly less in the 50% deflation group versus the 100% deflation group: MAP (7.0±4.3 vs. 38.5±25.7, p=0.02), CerPP (7.1±4.4 vs. 36.3±24.4, p=0.02), and CorPP (6.0±4.2 vs. 39.8±25.2, p=0.02), respectively.Conclusion:In this porcine model of prolonged cardiac arrest, partial deflation of the REBOA balloon post ROSC resulted in strikingly higher hemodynamics compared with complete deflation. These findings highlight the need to develop a post-ROSC REBOA deflation strategy when used during AHUP-CPR.

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