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BMC Medical Informatics and Decision Making

, 5:26

First Online: 11 August 2005Received: 04 January 2005Accepted: 11 August 2005


BackgroundPretest 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.

MethodsEight 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.

ResultsIn the validation set, attribute matching produced 267 unique PTP estimates median PTP value 6%, 1–3 quartile 1–10% compared with the LRE, which produced 96 unique PTP estimates median 24%, 1–3 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%.

ConclusionAttribute matching estimated a very low PTP for ACS in a significantly larger proportion of ED patients compared with a validated LRE.

List of abbreviationsACSAcute Coronary Syndrome

CIConfidence Interval

EDEmergency Department

i*trACSInternet Tracking of Acute Coronary Syndrome

LRELogistic Regression Equation

PTPPretest Probability

Electronic supplementary materialThe online version of this article doi:10.1186-1472-6947-5-26 contains supplementary material, which is available to authorized users.

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Autor: Jeffrey A Kline - Charles L Johnson - Charles V PollackJr - Deborah B Diercks - Judd E Hollander - Craig D Newgard - J


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