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A manifesto for cardiovascular imaging: addressing the human factor(†)
Our use of modern cardiovascular imaging tools has not kept pace with their technological development. Diagnostic errors are common but seldom investigated systematically. Rather than more impressive pictures, our main goal should be more precise tests of function which we select because their appro...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837338/ https://www.ncbi.nlm.nih.gov/pubmed/29029029 http://dx.doi.org/10.1093/ehjci/jex216 |
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author | Fraser, Alan G |
author_facet | Fraser, Alan G |
author_sort | Fraser, Alan G |
collection | PubMed |
description | Our use of modern cardiovascular imaging tools has not kept pace with their technological development. Diagnostic errors are common but seldom investigated systematically. Rather than more impressive pictures, our main goal should be more precise tests of function which we select because their appropriate use has therapeutic implications which in turn have a beneficial impact on morbidity or mortality. We should practise analytical thinking, use checklists to avoid diagnostic pitfalls, and apply strategies that will reduce biases and avoid overdiagnosis. We should develop normative databases, so that we can apply diagnostic algorithms that take account of variations with age and risk factors and that allow us to calculate pre-test probability and report the post-test probability of disease. We should report the imprecision of a test, or its confidence limits, so that reference change values can be considered in daily clinical practice. We should develop decision support tools to improve the quality and interpretation of diagnostic imaging, so that we choose the single best test irrespective of modality. New imaging tools should be evaluated rigorously, so that their diagnostic performance is established before they are widely disseminated; this should be a shared responsibility of manufacturers with clinicians, leading to cost-effective implementation. Trials should evaluate diagnostic strategies against independent reference criteria. We should exploit advances in machine learning to analyse digital data sets and identify those features that best predict prognosis or responses to treatment. Addressing these human factors will reap benefit for patients, while technological advances continue unpredictably. |
format | Online Article Text |
id | pubmed-5837338 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58373382018-03-09 A manifesto for cardiovascular imaging: addressing the human factor(†) Fraser, Alan G Eur Heart J Cardiovasc Imaging Reviews Our use of modern cardiovascular imaging tools has not kept pace with their technological development. Diagnostic errors are common but seldom investigated systematically. Rather than more impressive pictures, our main goal should be more precise tests of function which we select because their appropriate use has therapeutic implications which in turn have a beneficial impact on morbidity or mortality. We should practise analytical thinking, use checklists to avoid diagnostic pitfalls, and apply strategies that will reduce biases and avoid overdiagnosis. We should develop normative databases, so that we can apply diagnostic algorithms that take account of variations with age and risk factors and that allow us to calculate pre-test probability and report the post-test probability of disease. We should report the imprecision of a test, or its confidence limits, so that reference change values can be considered in daily clinical practice. We should develop decision support tools to improve the quality and interpretation of diagnostic imaging, so that we choose the single best test irrespective of modality. New imaging tools should be evaluated rigorously, so that their diagnostic performance is established before they are widely disseminated; this should be a shared responsibility of manufacturers with clinicians, leading to cost-effective implementation. Trials should evaluate diagnostic strategies against independent reference criteria. We should exploit advances in machine learning to analyse digital data sets and identify those features that best predict prognosis or responses to treatment. Addressing these human factors will reap benefit for patients, while technological advances continue unpredictably. Oxford University Press 2017-12 2017-09-28 /pmc/articles/PMC5837338/ /pubmed/29029029 http://dx.doi.org/10.1093/ehjci/jex216 Text en © The Author 2017. Published by Oxford University Press on behalf of the European Society of Cardiology http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Reviews Fraser, Alan G A manifesto for cardiovascular imaging: addressing the human factor(†) |
title | A manifesto for cardiovascular imaging: addressing the human factor(†) |
title_full | A manifesto for cardiovascular imaging: addressing the human factor(†) |
title_fullStr | A manifesto for cardiovascular imaging: addressing the human factor(†) |
title_full_unstemmed | A manifesto for cardiovascular imaging: addressing the human factor(†) |
title_short | A manifesto for cardiovascular imaging: addressing the human factor(†) |
title_sort | manifesto for cardiovascular imaging: addressing the human factor(†) |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837338/ https://www.ncbi.nlm.nih.gov/pubmed/29029029 http://dx.doi.org/10.1093/ehjci/jex216 |
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