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Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model

BACKGROUND: Cardio-cerebrovascular diseases (CVDs) result in 17.5 million deaths annually worldwide, accounting for 46.2% of noncommunicable causes of death, and are the leading cause of death, followed by cancer, respiratory disease, and diabetes mellitus. Coronary artery computed tomography angiog...

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Autores principales: Bae, Woo Kyung, Cho, Jihoon, Kim, Seok, Kim, Borham, Baek, Hyunyoung, Song, Wongeun, Yoo, Sooyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614618/
https://www.ncbi.nlm.nih.gov/pubmed/36227638
http://dx.doi.org/10.2196/41503
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author Bae, Woo Kyung
Cho, Jihoon
Kim, Seok
Kim, Borham
Baek, Hyunyoung
Song, Wongeun
Yoo, Sooyoung
author_facet Bae, Woo Kyung
Cho, Jihoon
Kim, Seok
Kim, Borham
Baek, Hyunyoung
Song, Wongeun
Yoo, Sooyoung
author_sort Bae, Woo Kyung
collection PubMed
description BACKGROUND: Cardio-cerebrovascular diseases (CVDs) result in 17.5 million deaths annually worldwide, accounting for 46.2% of noncommunicable causes of death, and are the leading cause of death, followed by cancer, respiratory disease, and diabetes mellitus. Coronary artery computed tomography angiography (CCTA), which detects calcification in the coronary arteries, can be used to detect asymptomatic but serious vascular disease. It allows for noninvasive and quick testing despite involving radiation exposure. OBJECTIVE: The objective of our study was to investigate the effectiveness of CCTA screening on CVD outcomes by using the Observational Health Data Sciences and Informatics’ Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) data and the population-level estimation method. METHODS: Using electronic health record–based OMOP-CDM data, including health questionnaire responses, adults (aged 30-74 years) without a history of CVD were selected, and 5-year CVD outcomes were compared between patients undergoing CCTA (target group) and a comparison group via 1:1 propensity score matching. Participants were stratified into low-risk and high-risk groups based on the American College of Cardiology/American Heart Association atherosclerotic cardiovascular disease (ASCVD) risk score and Framingham risk score (FRS) for subgroup analyses. RESULTS: The 2-year and 5-year risk scores were compared as secondary outcomes between the two groups. In total, 8787 participants were included in both the target group and comparison group. No significant differences (calibration P=.37) were found between the hazard ratios of the groups at 5 years. The subgroup analysis also revealed no significant differences between the ASCVD risk scores and FRSs of the groups at 5 years (ASCVD risk score: P=.97; FRS: P=.85). However, the CCTA group showed a significantly lower increase in risk scores at 2 years (ASCVD risk score: P=.03; FRS: P=.02). CONCLUSIONS: Although we could not confirm a significant difference in the preventive effects of CCTA screening for CVDs over a long period of 5 years, it may have a beneficial effect on risk score management over 2 years.
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spelling pubmed-96146182022-10-29 Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model Bae, Woo Kyung Cho, Jihoon Kim, Seok Kim, Borham Baek, Hyunyoung Song, Wongeun Yoo, Sooyoung JMIR Med Inform Original Paper BACKGROUND: Cardio-cerebrovascular diseases (CVDs) result in 17.5 million deaths annually worldwide, accounting for 46.2% of noncommunicable causes of death, and are the leading cause of death, followed by cancer, respiratory disease, and diabetes mellitus. Coronary artery computed tomography angiography (CCTA), which detects calcification in the coronary arteries, can be used to detect asymptomatic but serious vascular disease. It allows for noninvasive and quick testing despite involving radiation exposure. OBJECTIVE: The objective of our study was to investigate the effectiveness of CCTA screening on CVD outcomes by using the Observational Health Data Sciences and Informatics’ Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) data and the population-level estimation method. METHODS: Using electronic health record–based OMOP-CDM data, including health questionnaire responses, adults (aged 30-74 years) without a history of CVD were selected, and 5-year CVD outcomes were compared between patients undergoing CCTA (target group) and a comparison group via 1:1 propensity score matching. Participants were stratified into low-risk and high-risk groups based on the American College of Cardiology/American Heart Association atherosclerotic cardiovascular disease (ASCVD) risk score and Framingham risk score (FRS) for subgroup analyses. RESULTS: The 2-year and 5-year risk scores were compared as secondary outcomes between the two groups. In total, 8787 participants were included in both the target group and comparison group. No significant differences (calibration P=.37) were found between the hazard ratios of the groups at 5 years. The subgroup analysis also revealed no significant differences between the ASCVD risk scores and FRSs of the groups at 5 years (ASCVD risk score: P=.97; FRS: P=.85). However, the CCTA group showed a significantly lower increase in risk scores at 2 years (ASCVD risk score: P=.03; FRS: P=.02). CONCLUSIONS: Although we could not confirm a significant difference in the preventive effects of CCTA screening for CVDs over a long period of 5 years, it may have a beneficial effect on risk score management over 2 years. JMIR Publications 2022-10-13 /pmc/articles/PMC9614618/ /pubmed/36227638 http://dx.doi.org/10.2196/41503 Text en ©Woo Kyung Bae, Jihoon Cho, Seok Kim, Borham Kim, Hyunyoung Baek, Wongeun Song, Sooyoung Yoo. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 13.10.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Bae, Woo Kyung
Cho, Jihoon
Kim, Seok
Kim, Borham
Baek, Hyunyoung
Song, Wongeun
Yoo, Sooyoung
Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model
title Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model
title_full Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model
title_fullStr Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model
title_full_unstemmed Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model
title_short Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model
title_sort coronary artery computed tomography angiography for preventing cardio-cerebrovascular disease: observational cohort study using the observational health data sciences and informatics’ common data model
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614618/
https://www.ncbi.nlm.nih.gov/pubmed/36227638
http://dx.doi.org/10.2196/41503
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