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Assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the REasons for geographic and racial differences in stroke population

BACKGROUND: Routine electrocardiograms (ECGs) are not recommended for asymptomatic patients because the potential harms are thought to outweigh any benefits. Assessment tools to identify high risk individuals may improve the harm versus benefit profile of screening ECGs. In particular, people with u...

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Autores principales: Levitan, Emily B, Safford, Monika M, Kilgore, Meredith L, Soliman, Elsayed Z, Glasser, Stephen P, Judd, Suzanne E, Muntner, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3617994/
https://www.ncbi.nlm.nih.gov/pubmed/23530553
http://dx.doi.org/10.1186/1471-2261-13-23
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author Levitan, Emily B
Safford, Monika M
Kilgore, Meredith L
Soliman, Elsayed Z
Glasser, Stephen P
Judd, Suzanne E
Muntner, Paul
author_facet Levitan, Emily B
Safford, Monika M
Kilgore, Meredith L
Soliman, Elsayed Z
Glasser, Stephen P
Judd, Suzanne E
Muntner, Paul
author_sort Levitan, Emily B
collection PubMed
description BACKGROUND: Routine electrocardiograms (ECGs) are not recommended for asymptomatic patients because the potential harms are thought to outweigh any benefits. Assessment tools to identify high risk individuals may improve the harm versus benefit profile of screening ECGs. In particular, people with unrecognized myocardial infarction (UMI) have elevated risk for cardiovascular events and death. METHODS: Using logistic regression, we developed a basic assessment tool among 16,653 participants in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study using demographics, self-reported medical history, blood pressure, and body mass index and an expanded assessment tool using information on 51 potential variables. UMI was defined as electrocardiogram evidence of myocardial infarction without a self-reported history (n = 740). RESULTS: The basic assessment tool had a c-statistic of 0.638 (95% confidence interval 0.617 - 0.659) and included age, race, smoking status, body mass index, systolic blood pressure, and self-reported history of transient ischemic attack, deep vein thrombosis, falls, diabetes, and hypertension. A predicted probability of UMI > 3% provided a sensitivity of 80% and a specificity of 30%. The expanded assessment tool had a c-statistic of 0.654 (95% confidence interval 0.634-0.674). Because of the poor performance of these assessment tools, external validation was not pursued. CONCLUSIONS: Despite examining a large number of potential correlates of UMI, the assessment tools did not provide a high level of discrimination. These data suggest defining groups with high prevalence of UMI for targeted screening will be difficult.
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spelling pubmed-36179942013-04-06 Assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the REasons for geographic and racial differences in stroke population Levitan, Emily B Safford, Monika M Kilgore, Meredith L Soliman, Elsayed Z Glasser, Stephen P Judd, Suzanne E Muntner, Paul BMC Cardiovasc Disord Research Article BACKGROUND: Routine electrocardiograms (ECGs) are not recommended for asymptomatic patients because the potential harms are thought to outweigh any benefits. Assessment tools to identify high risk individuals may improve the harm versus benefit profile of screening ECGs. In particular, people with unrecognized myocardial infarction (UMI) have elevated risk for cardiovascular events and death. METHODS: Using logistic regression, we developed a basic assessment tool among 16,653 participants in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study using demographics, self-reported medical history, blood pressure, and body mass index and an expanded assessment tool using information on 51 potential variables. UMI was defined as electrocardiogram evidence of myocardial infarction without a self-reported history (n = 740). RESULTS: The basic assessment tool had a c-statistic of 0.638 (95% confidence interval 0.617 - 0.659) and included age, race, smoking status, body mass index, systolic blood pressure, and self-reported history of transient ischemic attack, deep vein thrombosis, falls, diabetes, and hypertension. A predicted probability of UMI > 3% provided a sensitivity of 80% and a specificity of 30%. The expanded assessment tool had a c-statistic of 0.654 (95% confidence interval 0.634-0.674). Because of the poor performance of these assessment tools, external validation was not pursued. CONCLUSIONS: Despite examining a large number of potential correlates of UMI, the assessment tools did not provide a high level of discrimination. These data suggest defining groups with high prevalence of UMI for targeted screening will be difficult. BioMed Central 2013-03-26 /pmc/articles/PMC3617994/ /pubmed/23530553 http://dx.doi.org/10.1186/1471-2261-13-23 Text en Copyright © 2013 Levitan et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Levitan, Emily B
Safford, Monika M
Kilgore, Meredith L
Soliman, Elsayed Z
Glasser, Stephen P
Judd, Suzanne E
Muntner, Paul
Assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the REasons for geographic and racial differences in stroke population
title Assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the REasons for geographic and racial differences in stroke population
title_full Assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the REasons for geographic and racial differences in stroke population
title_fullStr Assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the REasons for geographic and racial differences in stroke population
title_full_unstemmed Assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the REasons for geographic and racial differences in stroke population
title_short Assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the REasons for geographic and racial differences in stroke population
title_sort assessment tools for unrecognized myocardial infarction: a cross-sectional analysis of the reasons for geographic and racial differences in stroke population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3617994/
https://www.ncbi.nlm.nih.gov/pubmed/23530553
http://dx.doi.org/10.1186/1471-2261-13-23
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