Pretest probability assessment derived from attribute matching

<p>Abstract</p> <p>Background</p> <p>Pretest probability (PTP) assessment plays a central role in diagnosis. This report compares a novel attribute-matching method to generate a PTP for acute coronary syndrome (ACS). We compare the new method with a validated logistic r...

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Main Authors: Hollander Judd E, Diercks Deborah B, Pollack Charles V, Johnson Charles L, Kline Jeffrey A, Newgard Craig D, Garvey J Lee
Format: Article
Language:English
Published: BMC 2005-08-01
Series:BMC Medical Informatics and Decision Making
Online Access:http://www.biomedcentral.com/1472-6947/5/26
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spelling doaj-9a73b5fe7fce48a7b61e5d58b94698002020-11-24T21:52:07ZengBMCBMC Medical Informatics and Decision Making1472-69472005-08-01512610.1186/1472-6947-5-26Pretest probability assessment derived from attribute matchingHollander Judd EDiercks Deborah BPollack Charles VJohnson Charles LKline Jeffrey ANewgard Craig DGarvey J Lee<p>Abstract</p> <p>Background</p> <p>Pretest probability (PTP) assessment plays a central role in diagnosis. This report compares a novel attribute-matching method to generate a PTP for acute coronary syndrome (ACS). We compare the new method with a validated logistic regression equation (LRE).</p> <p>Methods</p> <p>Eight clinical variables (attributes) were chosen by classification and regression tree analysis of a prospectively collected reference database of 14,796 emergency department (ED) patients evaluated for possible ACS. For attribute matching, a computer program identifies patients within the database who have the exact profile defined by clinician input of the eight attributes. The novel method was compared with the LRE for ability to produce PTP estimation <2% in a validation set of 8,120 patients evaluated for possible ACS and did not have ST segment elevation on ECG. 1,061 patients were excluded prior to validation analysis because of ST-segment elevation (713), missing data (77) or being lost to follow-up (271).</p> <p>Results</p> <p>In the validation set, attribute matching produced 267 unique PTP estimates [median PTP value 6%, 1<sup>st</sup>–3<sup>rd </sup>quartile 1–10%] compared with the LRE, which produced 96 unique PTP estimates [median 24%, 1<sup>st</sup>–3<sup>rd </sup>quartile 10–30%]. The areas under the receiver operating characteristic curves were 0.74 (95% CI 0.65 to 0.82) for the attribute matching curve and 0.68 (95% CI 0.62 to 0.77) for LRE.</p> <p>The attribute matching system categorized 1,670 (24%, 95% CI = 23–25%) patients as having a PTP < 2.0%; 28 developed ACS (1.7% 95% CI = 1.1–2.4%). The LRE categorized 244 (4%, 95% CI = 3–4%) with PTP < 2.0%; four developed ACS (1.6%, 95% CI = 0.4–4.1%).</p> <p>Conclusion</p> <p>Attribute matching estimated a very low PTP for ACS in a significantly larger proportion of ED patients compared with a validated LRE.</p> http://www.biomedcentral.com/1472-6947/5/26
collection DOAJ
language English
format Article
sources DOAJ
author Hollander Judd E
Diercks Deborah B
Pollack Charles V
Johnson Charles L
Kline Jeffrey A
Newgard Craig D
Garvey J Lee
spellingShingle Hollander Judd E
Diercks Deborah B
Pollack Charles V
Johnson Charles L
Kline Jeffrey A
Newgard Craig D
Garvey J Lee
Pretest probability assessment derived from attribute matching
BMC Medical Informatics and Decision Making
author_facet Hollander Judd E
Diercks Deborah B
Pollack Charles V
Johnson Charles L
Kline Jeffrey A
Newgard Craig D
Garvey J Lee
author_sort Hollander Judd E
title Pretest probability assessment derived from attribute matching
title_short Pretest probability assessment derived from attribute matching
title_full Pretest probability assessment derived from attribute matching
title_fullStr Pretest probability assessment derived from attribute matching
title_full_unstemmed Pretest probability assessment derived from attribute matching
title_sort pretest probability assessment derived from attribute matching
publisher BMC
series BMC Medical Informatics and Decision Making
issn 1472-6947
publishDate 2005-08-01
description <p>Abstract</p> <p>Background</p> <p>Pretest probability (PTP) assessment plays a central role in diagnosis. This report compares a novel attribute-matching method to generate a PTP for acute coronary syndrome (ACS). We compare the new method with a validated logistic regression equation (LRE).</p> <p>Methods</p> <p>Eight clinical variables (attributes) were chosen by classification and regression tree analysis of a prospectively collected reference database of 14,796 emergency department (ED) patients evaluated for possible ACS. For attribute matching, a computer program identifies patients within the database who have the exact profile defined by clinician input of the eight attributes. The novel method was compared with the LRE for ability to produce PTP estimation <2% in a validation set of 8,120 patients evaluated for possible ACS and did not have ST segment elevation on ECG. 1,061 patients were excluded prior to validation analysis because of ST-segment elevation (713), missing data (77) or being lost to follow-up (271).</p> <p>Results</p> <p>In the validation set, attribute matching produced 267 unique PTP estimates [median PTP value 6%, 1<sup>st</sup>–3<sup>rd </sup>quartile 1–10%] compared with the LRE, which produced 96 unique PTP estimates [median 24%, 1<sup>st</sup>–3<sup>rd </sup>quartile 10–30%]. The areas under the receiver operating characteristic curves were 0.74 (95% CI 0.65 to 0.82) for the attribute matching curve and 0.68 (95% CI 0.62 to 0.77) for LRE.</p> <p>The attribute matching system categorized 1,670 (24%, 95% CI = 23–25%) patients as having a PTP < 2.0%; 28 developed ACS (1.7% 95% CI = 1.1–2.4%). The LRE categorized 244 (4%, 95% CI = 3–4%) with PTP < 2.0%; four developed ACS (1.6%, 95% CI = 0.4–4.1%).</p> <p>Conclusion</p> <p>Attribute matching estimated a very low PTP for ACS in a significantly larger proportion of ED patients compared with a validated LRE.</p>
url http://www.biomedcentral.com/1472-6947/5/26
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