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


Zimmerli, Lukas; Steurer, Johann; Kofmehl, Reto; Wertli, Maria M; Held, Ulrike (2014). Validation of a diagnostic probability function for estimating probabilities of acute coronary syndrome. BMC Emergency Medicine, 14:23.

Abstract

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.

Abstract

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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic and Policlinic for Internal Medicine
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2014
Deposited On:27 Nov 2014 12:19
Last Modified:08 Dec 2017 08:25
Publisher:BioMed Central
ISSN:1471-227X
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/1471-227X-14-23
PubMed ID:25403233

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