JACC. Cardiovascular imaging · 2025
Prevalence and Prognostic Value of Incidentally Detected Coronary Artery Calcium Using Artificial Intelligence Among Individuals With Immune-Mediated Inflammatory Diseases.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Weber Brittany N, Biery David W, Petranovic Milena, Besser Stephanie A, Huck Daniel M, Shiyovich Arthur, Cardoso Rhanderson, Berman Adam N, Blair Camila V, Trivedi Nayruti, Garshick Micheal S, Merola Joseph, Costenbader Karen, Shaw Leslee J, Nasir Khurram, Liao Katherine P, Di Carli Marcelo F, Blankstein Ron
Аннотация
BACKGROUND: Coronary artery calcium (CAC) scoring is strongly associated with cardiovascular (CV) events among the general population; however, its prognostic value among individuals with immune-mediated inflammatory diseases (IMIDs) is not well characterized.
OBJECTIVES: This study aims to assess the prevalence of CAC derived from routine chest computed tomography (CT) using a validated artificial intelligence (AI) algorithm and its association with adverse CV events among those with IMIDs.
METHODS: The authors studied a retrospective cohort of all patients 40 to 70 years of age with a diagnosis of systemic lupus erythematosus, rheumatoid arthritis, or psoriatic disease, and no prior atherosclerotic cardiovascular disease who underwent chest CT at 2 medical centers in Boston, Massachusetts, USA, from 2000 to 2023 as part of routine care. The presence and severity of CAC was determined using a validated AI methodology. Cox proportional hazards modeling was used to assess the association of CAC-AI categories (CAC-AI = 0, CAC-AI = 1-99, and CAC-AI ≥100) with all-cause mortality and major adverse cardiovascular events (MACE) (nonfatal myocardial infarction, coronary revascularization, nonfatal stroke, or CV mortality). All models were adjusted for age, sex, and traditional CV risk factors.
RESULTS: In total, 2,546 individuals with IMIDs (median age: 59 years [Q1-Q3: 53-65 years]; 1,694 [66.5%] women) were included with a median follow-up of 8.1 years. Among this cohort, 53% had CAC-AI >0 while only 6.0% were on a statin. A low burden of CAC (CAC-AI = 1-99) was associated with an increased risk of all-cause mortality (adjusted HR: 1.41; P = 0.010) and MACE (adjusted HR: 2.05; P < 0.001) with even greater risk observed among individuals with CAC-AI ≥100 (adjusted HR: 2.45; P < 0.001) and MACE (adjusted HR: 3.24; P < 0.001).
CONCLUSIONS: Among those with IMIDs, incidental CAC-AI was highly prevalent and significantly associated with both all-cause mortality and MACE. These findings suggest that CAC-AI may provide important prognostic information, allowing for improved risk stratification and treatment within an already high-risk and undertreated population.
OBJECTIVES: This study aims to assess the prevalence of CAC derived from routine chest computed tomography (CT) using a validated artificial intelligence (AI) algorithm and its association with adverse CV events among those with IMIDs.
METHODS: The authors studied a retrospective cohort of all patients 40 to 70 years of age with a diagnosis of systemic lupus erythematosus, rheumatoid arthritis, or psoriatic disease, and no prior atherosclerotic cardiovascular disease who underwent chest CT at 2 medical centers in Boston, Massachusetts, USA, from 2000 to 2023 as part of routine care. The presence and severity of CAC was determined using a validated AI methodology. Cox proportional hazards modeling was used to assess the association of CAC-AI categories (CAC-AI = 0, CAC-AI = 1-99, and CAC-AI ≥100) with all-cause mortality and major adverse cardiovascular events (MACE) (nonfatal myocardial infarction, coronary revascularization, nonfatal stroke, or CV mortality). All models were adjusted for age, sex, and traditional CV risk factors.
RESULTS: In total, 2,546 individuals with IMIDs (median age: 59 years [Q1-Q3: 53-65 years]; 1,694 [66.5%] women) were included with a median follow-up of 8.1 years. Among this cohort, 53% had CAC-AI >0 while only 6.0% were on a statin. A low burden of CAC (CAC-AI = 1-99) was associated with an increased risk of all-cause mortality (adjusted HR: 1.41; P = 0.010) and MACE (adjusted HR: 2.05; P < 0.001) with even greater risk observed among individuals with CAC-AI ≥100 (adjusted HR: 2.45; P < 0.001) and MACE (adjusted HR: 3.24; P < 0.001).
CONCLUSIONS: Among those with IMIDs, incidental CAC-AI was highly prevalent and significantly associated with both all-cause mortality and MACE. These findings suggest that CAC-AI may provide important prognostic information, allowing for improved risk stratification and treatment within an already high-risk and undertreated population.
Предметные рубрики MeSH
AdultAgedFemaleHumansMaleMiddle AgedArthritis, PsoriaticArthritis, RheumatoidArtificial IntelligenceBostonComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseIncidental FindingsLupus Erythematosus, SystemicPredictive Value of TestsPrevalencePrognosisRetrospective StudiesRisk AssessmentRisk FactorsTime FactorsVascular Calcification