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Pretest probability assessment derived from attribute matching

BACKGROUND: 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). METHODS: Eight clinical varia...

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Autores principales: Kline, Jeffrey A, Johnson, Charles L, Pollack, Charles V, Diercks, Deborah B, Hollander, Judd E, Newgard, Craig D, Garvey, J Lee
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1201143/
https://www.ncbi.nlm.nih.gov/pubmed/16095534
http://dx.doi.org/10.1186/1472-6947-5-26
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author Kline, Jeffrey A
Johnson, Charles L
Pollack, Charles V
Diercks, Deborah B
Hollander, Judd E
Newgard, Craig D
Garvey, J Lee
author_facet Kline, Jeffrey A
Johnson, Charles L
Pollack, Charles V
Diercks, Deborah B
Hollander, Judd E
Newgard, Craig D
Garvey, J Lee
author_sort Kline, Jeffrey A
collection PubMed
description BACKGROUND: 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). METHODS: 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). RESULTS: In the validation set, attribute matching produced 267 unique PTP estimates [median PTP value 6%, 1(st)–3(rd )quartile 1–10%] compared with the LRE, which produced 96 unique PTP estimates [median 24%, 1(st)–3(rd )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. 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%). CONCLUSION: Attribute matching estimated a very low PTP for ACS in a significantly larger proportion of ED patients compared with a validated LRE.
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spelling pubmed-12011432005-09-10 Pretest probability assessment derived from attribute matching Kline, Jeffrey A Johnson, Charles L Pollack, Charles V Diercks, Deborah B Hollander, Judd E Newgard, Craig D Garvey, J Lee BMC Med Inform Decis Mak Research Article BACKGROUND: 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). METHODS: 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). RESULTS: In the validation set, attribute matching produced 267 unique PTP estimates [median PTP value 6%, 1(st)–3(rd )quartile 1–10%] compared with the LRE, which produced 96 unique PTP estimates [median 24%, 1(st)–3(rd )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. 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%). CONCLUSION: Attribute matching estimated a very low PTP for ACS in a significantly larger proportion of ED patients compared with a validated LRE. BioMed Central 2005-08-11 /pmc/articles/PMC1201143/ /pubmed/16095534 http://dx.doi.org/10.1186/1472-6947-5-26 Text en Copyright © 2005 Kline 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
Kline, Jeffrey A
Johnson, Charles L
Pollack, Charles V
Diercks, Deborah B
Hollander, Judd E
Newgard, Craig D
Garvey, J Lee
Pretest probability assessment derived from attribute matching
title 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_short Pretest probability assessment derived from attribute matching
title_sort pretest probability assessment derived from attribute matching
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1201143/
https://www.ncbi.nlm.nih.gov/pubmed/16095534
http://dx.doi.org/10.1186/1472-6947-5-26
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