A Computer-Derived Protocol to Aid in the Diagnosis of Emergency Room Patients with Acute Chest Pain

Lee Goldman, Robert Jarret, Geoffrey Priest, John D'Avella, Mark Millard, Richard Kayne, David Coleman, Stephen Shell, Jeffrey Stem, Daniel Wallace Rahn, Robert Schoen, Carl Schoenberger, James Touloukian, Dana Brock, Vincent DiCola, Mark Cullen, Donald Furman, Lee Katz, Kenneth Dobular, Charles KowalWilliam Levy, Paula McFadden, Eric Conn, Florence Comite, Clifford Berken, Steven Brody, Joseph Craft, Mark Goldgeier, Jeffrey Hymes, Rex Mahnensmith, Richard Maunder, Ronald Vender, Adrienne Bentman, Paula Bockenstadt, James Breeling, John Clark, Marc Colb, Douglas Dawley, Susan Day, Andrew Eisenhauer, David Fox, James Garland, David Ginsburg, Bruce Given, David Golan, James Kirshenbaum, Ronald Koenig, Gordon Kritzer, Theodore Krontiris, Thomas Lee, Dennis Loh, Vincent Picozzi, Martha Radford, Robb Nicholson Celeste, Neal Rosen, Jamie Rosoff, Janet Seltzer, Sandra Skettino, Julia Smith, Julian Solway, Richard Stead, James Stoller, Elizabeth Tarn, Ralph Wallerstein, Ronald White, Richard Wright, Marc Weinberg, Monica Weisberg, Richard Olshen, E. Francis Cook, R. Kent Sargent, G. A. Lamas, Charles Dennis, Clyde Wilson, Lawrence Deckelbaum, Harvey Fineberg, Robert Stiratelli

Research output: Contribution to journalArticle

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Abstract

To determine whether data available to physicians in the emergency room can accurately identify which patients with acute chest pain are having myocardial infarctions, we analyzed 482 patients at one hospital. Using recursive partitioning analysis, we constructed a decision protocol in the format of a simple flow chart to identify infarction on the basis of nine clinical factors. In prospective testing on 468 other patients at a second hospital, the protocol performed as well as the physicians. Moreover, an integration of the protocol with the physicians' judgments resulted in a classification system that preserved sensitivity for detecting infarctions, significantly improved the specificity (from 67 per cent to 77 per cent, P<0.01) and positive predictive value (from 34 per cent to 42 per cent, P = 0.016) of admission to an intensive-care area. The protocol identified a subgroup of 107 patients among whom only 5 per cent had infarctions and for whom admission to non-intensive-care areas might be appropriate. This decision protocol warrants further wide-scale prospective testing but is not ready for routine clinical use. (N Engl J Med. 1982; 307:588–96.) CHEST pain is part of the symptom complex of about two thirds of patients admitted to a hospital with acute myocardial infarctions,1 but the identification of patients whose chest pain represents acute myocardial infarction is among the most difficult problems in clinical medicine. Because of fear of the consequences of missing patients at high risk, emergency room physicians are encouraged to admit patients to “rule out myocardial infarction” if the diagnosis is uncertain. Although this practice increases the number of admissions of patients who do have acute myocardial infarction, it has led to a situation in which as few as.

Original languageEnglish (US)
Pages (from-to)588-596
Number of pages9
JournalNew England Journal of Medicine
Volume307
Issue number10
DOIs
StatePublished - Sep 2 1982

ASJC Scopus subject areas

  • Medicine(all)

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    Goldman, L., Jarret, R., Priest, G., D'Avella, J., Millard, M., Kayne, R., Coleman, D., Shell, S., Stem, J., Rahn, D. W., Schoen, R., Schoenberger, C., Touloukian, J., Brock, D., DiCola, V., Cullen, M., Furman, D., Katz, L., Dobular, K., ... Stiratelli, R. (1982). A Computer-Derived Protocol to Aid in the Diagnosis of Emergency Room Patients with Acute Chest Pain. New England Journal of Medicine, 307(10), 588-596. https://doi.org/10.1056/NEJM198209023071004