AI-Facilitated Assessment of Built Environment Using Neighborhood Satellite Imagery and Cardiovascular Risk.

Autor:	Chen Z; Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA., Vieira de Oliveira Salerno PR; Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA., Dazard JE; Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA., Kumar Sirasapalli S; Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA., Makhlouf MHE; Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA., Motairek I; Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA., Moorthy S; Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA., Al-Kindi S; Center for Health and Nature and Department of Cardiology, Houston Methodist, Houston, Texas, USA. Electronic address: sal-kindi@houstonmethodist.org., Rajagopalan S; Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA. Electronic address: sanjay.rajagopalan@uhhospitals.org.
Jazyk:	angličtina
Zdroj:	Journal of the American College of Cardiology [J Am Coll Cardiol] 2024 Oct 29; Vol. 84 (18), pp. 1733-1744.
DOI:	10.1016/j.jacc.2024.08.053
Abstrakt:	Background: Built environment affects cardiovascular health, but comprehensive assessment in a scalable fashion, for population health and resource allocation, is constrained by limitations of current microscale measures. Objectives: The purpose of this study was to investigate the association between satellite image-based environment and risk of major adverse cardiovascular events (MACE). Methods: Using a pretrained deep neural network, features depicting the built environment from Google Satellite Imagery (GSI) around 64,230 patients in Northern Ohio undergoing coronary artery calcium (CAC) scoring were extracted. Elastic net regularized Cox proportional hazards models identified associations of GSI features with MACE risk (defined as myocardial infarction, stroke, heart failure, or death). A composite GSI risk score was constructed using features that demonstrated nonzero coefficients in the elastic net model. We assessed association of this score with MACE risk, after adjusting for CAC scores and the social vulnerability index (SVI). Its interactions with CAC scores were also examined in subgroups. Results: Adjusting for CAC and traditional risk factors, the GSI risk score was significantly associated with higher MACE risk (HR: 2.67; 95% CI: 1.63-4.38; P < 0.001). However, adding SVI reduced this association to nonsignificance (HR: 1.54; 95% CI: 0.91-2.60; P = 0.11). Patients in the highest quartile (Q4) of GSI risk score had a 56% higher observed risk of MACE (HR: 1.56; 95% CI: 1.32-1.86; P < 0.005) compared with the lowest quartile (Q1). The GSI risk score had the strongest association with MACE risk in patients with CAC = 0. This association was attenuated, but remained significant, with higher CAC. Conclusions: AI-enhanced satellite images of the built environment were linked to MACE risk, independently of traditional risk factors and CAC, but this was influenced by social determinants of health, represented by SVI. Satellite image-based assessment of the built environment may provide a rapid scalable integrative approach, warranting further exploration for enhanced risk prediction. Competing Interests: Funding Support and Author Disclosures This work was funded by the National Institute on Minority Health and Health Disparities Award P50MD017351 and 1R35ES031702-01 awarded to Dr Rajagopalan. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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