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Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome

BACKGROUND: We recently reported about the derivation of a diagnostic probability function for acute coronary syndrome (ACS). The present study aims to validate the probability function as a rule-out criterion in a new sample of patients. METHODS: 186 patients presenting with chest pain and/or dyspn...

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Autores principales: Zimmerli, Lukas, Steurer, Johann, Kofmehl, Reto, Wertli, Maria M, Held, Ulrike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4289321/
https://www.ncbi.nlm.nih.gov/pubmed/25403233
http://dx.doi.org/10.1186/1471-227X-14-23
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author Zimmerli, Lukas
Steurer, Johann
Kofmehl, Reto
Wertli, Maria M
Held, Ulrike
author_facet Zimmerli, Lukas
Steurer, Johann
Kofmehl, Reto
Wertli, Maria M
Held, Ulrike
author_sort Zimmerli, Lukas
collection PubMed
description BACKGROUND: We recently reported about the derivation of a diagnostic probability function for acute coronary syndrome (ACS). The present study aims to validate the probability function as a rule-out criterion in a new sample of patients. METHODS: 186 patients presenting with chest pain and/or dyspnea at one of the three participating hospitals’ emergency rooms in Switzerland were included in the study. In these patients, information on a set of pre-specified variables was collected and a predicted probability of ACS was calculated for each patient. Approximately two weeks after the initial visit in the emergency room, patients were contacted by phone to assess whether a diagnosis of ACS was established. RESULTS: Of the 186 patients included in the study, 31 (17%) had an acute coronary syndrome. A risk probability for ACS below 2% was considered a rule-out criterion for ACS, leading to a sensitivity of 87% and a specificity of 17% of the rule. The characteristics of the study patients were compared to the cases from which the probability function was derived, and considerable deviations were found in some of the variables. CONCLUSIONS: The proposed probability function, with a 2% cut-off for ruling out ACS works quite well if the patient data lie within the ranges of values of the original vignettes. If the observations deviate too much from these ranges, the predicted probabilities for ACS should be seen with caution. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-227X-14-23) contains supplementary material, which is available to authorized users.
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spelling pubmed-42893212015-01-11 Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome Zimmerli, Lukas Steurer, Johann Kofmehl, Reto Wertli, Maria M Held, Ulrike BMC Emerg Med Research Article BACKGROUND: We recently reported about the derivation of a diagnostic probability function for acute coronary syndrome (ACS). The present study aims to validate the probability function as a rule-out criterion in a new sample of patients. METHODS: 186 patients presenting with chest pain and/or dyspnea at one of the three participating hospitals’ emergency rooms in Switzerland were included in the study. In these patients, information on a set of pre-specified variables was collected and a predicted probability of ACS was calculated for each patient. Approximately two weeks after the initial visit in the emergency room, patients were contacted by phone to assess whether a diagnosis of ACS was established. RESULTS: Of the 186 patients included in the study, 31 (17%) had an acute coronary syndrome. A risk probability for ACS below 2% was considered a rule-out criterion for ACS, leading to a sensitivity of 87% and a specificity of 17% of the rule. The characteristics of the study patients were compared to the cases from which the probability function was derived, and considerable deviations were found in some of the variables. CONCLUSIONS: The proposed probability function, with a 2% cut-off for ruling out ACS works quite well if the patient data lie within the ranges of values of the original vignettes. If the observations deviate too much from these ranges, the predicted probabilities for ACS should be seen with caution. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-227X-14-23) contains supplementary material, which is available to authorized users. BioMed Central 2014-11-18 /pmc/articles/PMC4289321/ /pubmed/25403233 http://dx.doi.org/10.1186/1471-227X-14-23 Text en © Zimmerli et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. 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 credited. 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 Article
Zimmerli, Lukas
Steurer, Johann
Kofmehl, Reto
Wertli, Maria M
Held, Ulrike
Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome
title Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome
title_full Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome
title_fullStr Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome
title_full_unstemmed Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome
title_short Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome
title_sort validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4289321/
https://www.ncbi.nlm.nih.gov/pubmed/25403233
http://dx.doi.org/10.1186/1471-227X-14-23
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