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2.
Heart Vessels ; 2020 Apr 29.
Artigo em Inglês | MEDLINE | ID: mdl-32350637

RESUMO

Myocardial perfusion imaging (MPI) using Single Photon Emission Computed Tomography has been established as a standard noninvasive tool for risk stratification of coronary artery disease (CAD). We evaluated the diagnostic performance of on-site workstation-based computed tomography-derived fractional flow reserve (CT-FFR) in comparison with MPI using invasive fractional flow reserve (invasive FFR) as a gold standard. We enrolled 97 patients with suspected CAD. Diagnostic performance of CT angiography (CTA), and CT-FFR was compared in 105 lesions of 97 patients. Invasive FFR ≤ 0.8 was detected in 38 (36%) lesions. Diagnostic performance of CT-FFR was improved compared with CTA (AUC 0.83 vs. 0.60, p < 0.0001). The lesions with both CTA and MPI findings (n = 47), invasive FFR ≤ 0.8 was detected in 19 (40.4) lesions. CT-FFR (AUC 0.81, 95% CI 0.72-0.94) significantly improved diagnostic performance compared with CTA-50% (AUC 0.59, p = 0.00019) and MPI (AUC 0.64, p = 0.0082). In lesions with ≥ 50% on CTA (n = 42), diagnostic accuracy of CT-FFR (AUC 0.81) was significantly superior to MPI (AUC 0.64, p = 0.0239). In conclusions, CT-FFR improved diagnostic accuracy to detect invasive FFR ≤ 0.8 compared with luminal stenosis on CTA and ischemia on MPI. Patients with ≥ 50% stenosis on CTA would be the candidates for CT-FFR.

3.
PLoS One ; 15(5): e0232573, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32374784

RESUMO

OBJECTIVES: To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND: Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS: Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS: The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS: An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level.

5.
J Am Coll Cardiol ; 2020 Apr 14.
Artigo em Inglês | MEDLINE | ID: mdl-32305401

RESUMO

SARS-CoV2 host cell infection is mediated by the binding to angiotensin-converting enzyme 2 (ACE2). Systemic dysregulation observed in SARS-CoV was previously postulated to be due to ACE2/Ang1-7/Mas axis downregulation, increased ACE2 activity was shown to mediate disease protection. Since angiotensin II receptor blockers (ARBs), ACE inhibitors, and mineralocorticoid receptor antagonists (MRAs) increase ACE2 receptor expression, it has been tacitly believed that the use of these agents may facilitate viral disease, thus they should not be used in high-risk patients with cardiovascular disease. Based on the anti-inflammatory benefits of the upregulation of the ACE2/Ang1-7/Mas axis and previously demonstrated benefits of lung function improvement in SARS-CoV infections, we hypothesize that the benefits of treatment with renin-angiotensin system inhibitors in SARS-COV2 may outweigh the risks and at the very least should not be withheld.

7.
JACC Cardiovasc Imaging ; 13(5): 1119-1132, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32199835

RESUMO

OBJECTIVES: The authors applied unsupervised machine-learning techniques for integrating echocardiographic features of left ventricular (LV) structure and function into a patient similarity network that predicted major adverse cardiac event(s) (MACE) in an individual patient. BACKGROUND: Patient similarity analysis is an evolving paradigm for precision medicine in which patients are clustered or classified based on their similarities in several clinical features. METHODS: A retrospective cohort of 866 patients was used to develop a network architecture using 9 echocardiographic features of LV structure and function. The data for 468 patients from 2 prospective cohort registries were then added to test the model's generalizability. RESULTS: The map of cross-sectional data in the retrospective cohort resulted in a looped patient network that persisted even after the addition of data from the prospective cohort registries. After subdividing the loop into 4 regions, patients in each region showed unique differences in LV function, with Kaplan-Meier curves demonstrating significant differences in MACE-related rehospitalization and death (both p < 0.001). Addition of network information to clinical risk predictors resulted in significant improvements in net reclassification, integrated discrimination, and median risk scores for predicting MACE (p < 0.05 for all). Furthermore, the network predicted the cardiac disease cycle in each of the 96 patients who had second echocardiographic evaluations. An improvement or remaining in low-risk regions was associated with lower MACE-related rehospitalization rates than worsening or remaining in high-risk regions (3% vs. 37%; p < 0.001). CONCLUSIONS: Patient similarity analysis integrates multiple features of cardiac function to develop a phenotypic network in which patients can be mapped to specific locations associated with specific disease stage and clinical outcomes. The use of patient similarity analysis may have relevance for automated staging of cardiac disease severity, personalized prediction of prognosis, and monitoring progression or response to therapies.

8.
J Nucl Cardiol ; 2020 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-32140993

RESUMO

In the original version of the editorial, a wrong figure was used. The original article has been corrected.

9.
JAMA Netw Open ; 3(3): e201177, 2020 Mar 02.
Artigo em Inglês | MEDLINE | ID: mdl-32181828

RESUMO

Importance: The World Health Organization estimates that the 1 billion individuals who smoke worldwide contribute to the 880 000 secondhand smoke (SHS)-related deaths among individuals who do not smoke each year. A better understanding of the scale of harm of SHS to those who do not smoke could increase awareness of the consequences of smoking and help to design measures to protect individuals who do not smoke, especially children. Objective: To calculate the number of individuals who smoke associated with the death of 1 individual who died of SHS exposure both on a global scale and in various World Bank regions. Design, Setting, and Participants: In this cross-sectional epidemiologic assessment, data from Our World in Data were used to tabulate the number of individuals who smoke in each country and number of premature deaths related to SHS in that country from 1990 to 2016. The mean number of cigarettes consumed in all countries was also included in analyses. Data were collected for the following World Bank regions: North America, Latin America and the Caribbean, Europe and Central Asia, the Middle East and North Africa, sub-Saharan Africa, South Asia, and East Asia and the Pacific from 1990 and 2016. Statistical analysis was conducted in July 2019. Exposure: Secondhand smoke. Main Outcomes and Measures: The pack-year index, calculated as the number of pack-years associated with the death of 1 individual who does not smoke but was exposed to SHS, and the SHS index, calculated as the number of individuals who smoked for 24 years (ie, the mean duration of smoking) associated with the death of 1 individual who does not smoke. Results: Globally, the SHS index changed favorably, from 31.3 (95% CI, 30.6-32.0) individuals who smoked associated with the death of 1 individual who did not smoke in 1990 to 52.3 (95% CI, 51.2-53.5) individuals who smoked in 2016. There was a wide regional variation in the 2016 secondhand smoke index, from 42.6 (95% CI, 41.6-43.5) individuals who smoked in the Middle East and North Africa to 85.7 (95% CI, 83.8-87.7) individuals who smoked in North America. Worldwide, the pack-year index also changed favorably from 751.9 (95% CI, 736.3-770.7) pack-years associated with 1 death in 1990 to 1255.9 (95% CI, 1227.2-1284.4) pack-years in 2016. Conclusions and Relevance: In this study, the substantial disparity among regions in both the SHS index and pack-year index reflected large differences in the scale of the harm of SHS on those who do not smoke. This information may help local policy makers implement measures to better protect those who do not smoke and increase public engagement. Although the number of pack-years and the number of individuals who smoke associated with the death of 1 individual who did not smoke favorably changed over the study period, as of 2016, 52.3 individuals who smoked were associated with the death of 1 individual who did not smoke.

12.
Artigo em Inglês | MEDLINE | ID: mdl-32063545

RESUMO

BACKGROUND AND AIMS: Different methodologies to report whole-heart atherosclerotic plaque on coronary computed tomography angiography (CCTA) have been utilized. We examined which of the three commonly used plaque burden definitions was least affected by differences in body surface area (BSA) and sex. METHODS: The PARADIGM study includes symptomatic patients with suspected coronary atherosclerosis who underwent serial CCTA >2 years apart. Coronary lumen, vessel, and plaque were quantified from the coronary tree on a 0.5 mm cross-sectional basis by a core-lab, and summed to per-patient. Three quantitative methods of plaque burden were employed: (1) total plaque volume (PV) in mm3, (2) percent atheroma volume (PAV) in % [which equaled: PV/vessel volume * 100%], and (3) normalized total atheroma volume (TAVnorm) in mm3 [which equaled: PV/vessel length * mean population vessel length]. Only data from the baseline CCTA were used. PV, PAV, and TAVnorm were compared between patients in the top quartile of BSA vs the remaining, and between sexes. Associations between vessel volume, BSA, and the three plaque burden methodologies were assessed. RESULTS: The study population comprised 1479 patients (age 60.7 ± 9.3 years, 58.4% male) who underwent CCTA. A total of 17,649 coronary artery segments were evaluated with a median of 12 (IQR 11-13) segments per-patient (from a 16-segment coronary tree). Patients with a large BSA (top quartile), compared with the remaining patients, had a larger PV and TAVnorm, but similar PAV. The relation between larger BSA and larger absolute plaque volume (PV and TAVnorm) was mediated by the coronary vessel volume. Independent from the atherosclerotic cardiovascular disease risk (ASCVD) score, vessel volume correlated with PV (P < 0.001), and TAVnorm (P = 0.003), but not with PAV (P = 0.201). The three plaque burden methods were equally affected by sex. CONCLUSIONS: PAV was less affected by patient's body surface area then PV and TAVnorm and may be the preferred method to report coronary atherosclerotic burden.

13.
J Am Coll Cardiol ; 75(7): 750-758, 2020 Feb 25.
Artigo em Inglês | MEDLINE | ID: mdl-32081284

RESUMO

BACKGROUND: Left ventricular (LV) systolic function may be overestimated in patients with secondary mitral regurgitation (MR) when using LV ejection fraction (EF). LV global longitudinal strain (GLS) is a less load-dependent measure of LV function. However, the prognostic value of LV GLS in secondary MR has not been evaluated. OBJECTIVES: This study sought to demonstrate the prognostic value of LV GLS over LVEF in patients with secondary MR. METHODS: A total of 650 patients (mean 66 ± 11 years of age, 68% men) with significant secondary MR were included. The study population was subdivided based on the LV GLS value at which the hazard ratio (HR) for all-cause mortality was >1 using a spline curve analysis (LV GLS <7.0%, impaired LV systolic function vs. LV GLS ≥7.0%, preserved LV systolic function). The primary endpoint was all-cause mortality. RESULTS: During a median follow-up of 56 (interquartile range: 28 to 106 months) months, 334 (51%) patients died. Patients with a more impaired LV GLS showed significantly higher mortality rates at 1-, 2-, and 5-year follow-up (13%, 23%, and 44%, respectively) when compared with patients with more preserved LV systolic function (5%, 14%, and 31%, respectively). On multivariable analysis, LV GLS <7.0% was associated with increased mortality (HR: 1.337; 95% confidence interval: 1.038 to 1.722; p = 0.024), whereas LVEF ≤30% was not (HR: 1.055; 95% confidence interval: 0.794 to 1.403; p = 0.711). CONCLUSIONS: In patients with secondary MR, impaired LV GLS was independently associated with an increased risk for all-cause mortality, whereas LVEF was not. LV GLS may therefore be useful in the risk stratification of patients with secondary MR.

15.
J Am Heart Assoc ; 9(5): e013958, 2020 Mar 03.
Artigo em Inglês | MEDLINE | ID: mdl-32089046

RESUMO

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP.

18.
JAMA Cardiol ; 2020 Jan 22.
Artigo em Inglês | MEDLINE | ID: mdl-31968065

RESUMO

Importance: Plaque morphologic measures on coronary computed tomography angiography (CCTA) have been associated with future acute coronary syndrome (ACS). However, the evolution of calcified coronary plaques by noninvasive imaging is not known. Objective: To ascertain whether the increasing density in calcified coronary plaque is associated with risk for ACS. Design, Setting, and Participants: This multicenter case-control cohort study included individuals enrolled in ICONIC (Incident Coronary Syndromes Identified by Computed Tomography), a nested case-control study of patients drawn from the CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter) registry, which included 13 study sites in 8 countries. Patients who experienced core laboratory-verified ACS after baseline CCTA (n = 189) and control individuals who did not experience ACS after baseline CCTA (n = 189) were included. Patients and controls were matched 1:1 by propensity scores for age; male sex; presence of hypertension, hyperlipidemia, and diabetes; family history of premature coronary artery disease (CAD); current smoking status; and CAD severity. Data were analyzed from November 2018 to March 2019. Exposures: Whole-heart atherosclerotic plaque volume was quantitated from all coronary vessels and their branches. For patients who underwent invasive angiography at the time of ACS, culprit lesions were coregistered to baseline CCTA lesions by a blinded independent reader. Low-density plaque was defined as having less than 130 Hounsfield units (HU); calcified plaque, as having more than 350 HU and subcategorized on a voxel-level basis into 3 strata: 351 to 700 HU, 701 to 1000 HU, and more than 1000 HU (termed 1K plaque). Main Outcomes and Measures: Association between calcium density and future ACS risk. Results: A total of 189 patients and 189 matched controls (mean [SD] age of 59.9 [9.8] years; 247 [65.3%] were male) were included in the analysis and were monitored during a mean (SD) follow-up period of 3.9 (2.5) years. The overall mean (SD) calcified plaque volume (>350 HU) was similar between patients and controls (76.4 [101.6] mm3 vs 99.0 [156.1] mm3; P = .32), but patients who experienced ACS exhibited less 1K plaque (>1000 HU) compared with controls (3.9 [8.3] mm3 vs 9.4 [23.2] mm3; P = .02). Individuals within the highest quartile of 1K plaque exhibited less low-density plaque, as a percentage of total plaque, when compared with patients within the lower 3 quartiles (12.6% [10.4%] vs 24.9% [20.6%]; P < .001). For 93 culprit precursor lesions detected by CCTA, the volume of 1K plaque was lower compared with the maximally stenotic lesion in controls (2.6 [7.2] mm3 vs 7.6 [20.3] mm3; P = .01). The per-patient and per-lesion results were similar between the 2 groups when restricted to myocardial infarction cases. Conclusions and Relevance: Results of this study suggest that, on a per-patient and per-lesion basis, 1K plaque was associated with a lower risk for future ACS and that measurement of 1K plaque may improve risk stratification beyond plaque burden.

19.
Mayo Clin Proc ; 95(1): 136-156, 2020 01.
Artigo em Inglês | MEDLINE | ID: mdl-31902409

RESUMO

Globally, cardiovascular disease remains a major cause of adverse outcomes in young individuals, unlike its decline in other age groups. This group is not well studied and has a unique risk profile with less traditional cardiovascular risk factors compared with older populations. Plaque rupture still remains the most common etiology of myocardial infarction, but unique syndromes such as plaque erosion, coronary microvascular dysfunction, spontaneous coronary artery dissection, and coronary spasm related to drug use are more prevalent in this age group. Such diversity of diagnosis and presentation, along with therapeutic implications, underscore the need to study the profile of myocardial infarction in young persons. We searched PubMed for articles published from 1980 to 218 using the terms acute myocardial infarction, young, plaque rupture, plaque erosion, spontaneous coronary artery dissection (SCAD), coronary vasospasm, variant or Prinzmetal angina, drug-induced myocardial infarction, myocarditis, coronary embolism, microvascular dysfunction, MINOCA, and myocardial infarction in pregnancy and reviewed all the published studies. With the data from this search, we aim to inform readers of the prevalence, risk factors, presentation, and management of acute myocardial infarction in young patients and elaborate on special subgroups with diagnostic and therapeutic challenges. We also outline a parsimonious method designed to simplify management of these complex patients.


Assuntos
Infarto do Miocárdio , Administração dos Cuidados ao Paciente/métodos , Adulto , Idade de Início , Causalidade , Humanos , Infarto do Miocárdio/epidemiologia , Infarto do Miocárdio/etiologia , Infarto do Miocárdio/terapia , Prognóstico , Fatores de Risco
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