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Association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial Bayesian model

BACKGROUND: Coronary computed tomography angiography (CTA) has demonstrated high diagnostic accuracy for detection of coronary artery stenosis, and healthcare providers can detect coronary artery disease in earlier stages before it develops into more serious clinical conditions such as acute myocard...

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Autores principales: Kawaguchi, Hideaki, Koike, Soichi, Sakurai, Ryota, Ohe, Kazuhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5963166/
https://www.ncbi.nlm.nih.gov/pubmed/29784002
http://dx.doi.org/10.1186/s12942-018-0133-0
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author Kawaguchi, Hideaki
Koike, Soichi
Sakurai, Ryota
Ohe, Kazuhiko
author_facet Kawaguchi, Hideaki
Koike, Soichi
Sakurai, Ryota
Ohe, Kazuhiko
author_sort Kawaguchi, Hideaki
collection PubMed
description BACKGROUND: Coronary computed tomography angiography (CTA) has demonstrated high diagnostic accuracy for detection of coronary artery stenosis, and healthcare providers can detect coronary artery disease in earlier stages before it develops into more serious clinical conditions such as acute myocardial infarction (AMI). We hypothesized that the mortality ratio of AMI in regions with a higher density of coronary CTA is lower than that in regions with a lower density of coronary CTA. METHODS: This ecological and cross-sectional study using secondary data targeted all secondary medical service areas (SMSAs) in Japan (n = 349). We obtained the numbers of cardiologists, institutions with coronary CTA, and institutions with a cardiac catheterization laboratory (CCL) as medical resources, socioeconomic factors, lifestyle factors, exercise habit factors, and AMI mortality data from a Japanese national database. We evaluated the association between the number of these medical resources and the standardized mortality ratio (SMR) of AMI in each SMSA using a hierarchical Bayesian model accounting for spatial autocorrelation (i.e., a conditional autoregressive model). We assumed a Poisson distribution for the observed number of AMI-related deaths and set the expected number of AMI-related deaths as the offset variable. RESULTS: The number of institutions with coronary CTA was negatively and significantly associated with the SMR of AMI (relative risk [RR] 0.900; 95% credible interval [CI] 0.848–0.953), while the SMR in each SMSA was not significantly associated with the number of either cardiologists (RR 0.997; 95% CI 0.988–1.004) or institutions with a CCL (RR 1.026; 95% CI 0.963–1.096). CONCLUSIONS: We observed a significant association between the number of institutions with coronary CTA and the SMR of AMI. Effective allocation of coronary CTA in each region is recommended, and it would be important to clarify the standing position of coronary CTA in regional networking for AMI treatment in the future. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12942-018-0133-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-59631662018-05-24 Association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial Bayesian model Kawaguchi, Hideaki Koike, Soichi Sakurai, Ryota Ohe, Kazuhiko Int J Health Geogr Research BACKGROUND: Coronary computed tomography angiography (CTA) has demonstrated high diagnostic accuracy for detection of coronary artery stenosis, and healthcare providers can detect coronary artery disease in earlier stages before it develops into more serious clinical conditions such as acute myocardial infarction (AMI). We hypothesized that the mortality ratio of AMI in regions with a higher density of coronary CTA is lower than that in regions with a lower density of coronary CTA. METHODS: This ecological and cross-sectional study using secondary data targeted all secondary medical service areas (SMSAs) in Japan (n = 349). We obtained the numbers of cardiologists, institutions with coronary CTA, and institutions with a cardiac catheterization laboratory (CCL) as medical resources, socioeconomic factors, lifestyle factors, exercise habit factors, and AMI mortality data from a Japanese national database. We evaluated the association between the number of these medical resources and the standardized mortality ratio (SMR) of AMI in each SMSA using a hierarchical Bayesian model accounting for spatial autocorrelation (i.e., a conditional autoregressive model). We assumed a Poisson distribution for the observed number of AMI-related deaths and set the expected number of AMI-related deaths as the offset variable. RESULTS: The number of institutions with coronary CTA was negatively and significantly associated with the SMR of AMI (relative risk [RR] 0.900; 95% credible interval [CI] 0.848–0.953), while the SMR in each SMSA was not significantly associated with the number of either cardiologists (RR 0.997; 95% CI 0.988–1.004) or institutions with a CCL (RR 1.026; 95% CI 0.963–1.096). CONCLUSIONS: We observed a significant association between the number of institutions with coronary CTA and the SMR of AMI. Effective allocation of coronary CTA in each region is recommended, and it would be important to clarify the standing position of coronary CTA in regional networking for AMI treatment in the future. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12942-018-0133-0) contains supplementary material, which is available to authorized users. BioMed Central 2018-05-21 /pmc/articles/PMC5963166/ /pubmed/29784002 http://dx.doi.org/10.1186/s12942-018-0133-0 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Kawaguchi, Hideaki
Koike, Soichi
Sakurai, Ryota
Ohe, Kazuhiko
Association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial Bayesian model
title Association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial Bayesian model
title_full Association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial Bayesian model
title_fullStr Association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial Bayesian model
title_full_unstemmed Association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial Bayesian model
title_short Association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial Bayesian model
title_sort association between number of institutions with coronary computed tomography angiography and regional mortality ratio of acute myocardial infarction: a nationwide ecological study using a spatial bayesian model
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5963166/
https://www.ncbi.nlm.nih.gov/pubmed/29784002
http://dx.doi.org/10.1186/s12942-018-0133-0
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