» Articles » PMID: 27183255

Utility of the Diamond-Forrester Classification in Stratifying Acute Chest Pain in an Academic Chest Pain Center

Overview
Date 2016 May 17
PMID 27183255
Citations 1
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Because the Diamond-Forrester (DF) model is predictive of obstructive coronary artery disease (CAD), it is often used to risk stratify acute chest pain patients. We sought to further evaluate the clinical utility of the DF model within a chest pain evaluation center.

Methods: Consecutive patients with chest pain and no known CAD or evidence of active ischemia were asked to participate in a prospective registry. Patients were classified based on cardiovascular risk factors, age, and DF classification. We compared data from the emergency department course, Duke Activity Status Index (DASI) and Seattle Angina Questionnaire (SAQ), hospitalization rates, and results of testing between patients with typical angina and all others. Multivariate logistic regression was also used to assess for predictors of CAD by computed tomography coronary angiography (CTCA) or positive exercise treadmill testing (ETT).

Results: Among 209 patients, 163 had atypical/noncardiac and 46 had typical chest pain. The SAQ and DASI scores were lower in the typical chest pain group (indicating more severe impairment), which were not statistically significantly different. There were no significant differences in risk factors or the results of CTCA, ETT, or cardiac catheterization. In the regression analysis, SAQ score, DASI score, and DF classification were not predictive of CAD by CTCA. Worsening angina frequency scores on the SAQ were marginally associated with positive ETT (OR, 1.04; P=0.04).

Conclusion: In a contemporary low-risk acute chest pain population, typical angina, as defined by the DF classification, was not predictive of CAD or useful for identifying patients with higher symptom burden.

Citing Articles

Computed tomography coronary angiography after excluding myocardial infarction: high-sensitivity troponin versus risk score-guided approach.

Yoo W, Ahn S, Chae B, Kim W World J Emerg Med. 2023; 14(6):428-433.

PMID: 37969225 PMC: 10632764. DOI: 10.5847/wjem.j.1920-8642.2023.094.

References
1.
Pryor D, Harrell Jr F, Lee K, Califf R, Rosati R . Estimating the likelihood of significant coronary artery disease. Am J Med. 1983; 75(5):771-80. DOI: 10.1016/0002-9343(83)90406-0. View

2.
Harris P, Taylor R, Thielke R, Payne J, Gonzalez N, Conde J . Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2008; 42(2):377-81. PMC: 2700030. DOI: 10.1016/j.jbi.2008.08.010. View

3.
Pryor D, Shaw L, McCants C, Lee K, Mark D, Harrell Jr F . Value of the history and physical in identifying patients at increased risk for coronary artery disease. Ann Intern Med. 1993; 118(2):81-90. DOI: 10.7326/0003-4819-118-2-199301150-00001. View

4.
Mark D, Shaw L, Harrell Jr F, Hlatky M, Lee K, Bengtson J . Prognostic value of a treadmill exercise score in outpatients with suspected coronary artery disease. N Engl J Med. 1991; 325(12):849-53. DOI: 10.1056/NEJM199109193251204. View

5.
Diamond G, Forrester J . Analysis of probability as an aid in the clinical diagnosis of coronary-artery disease. N Engl J Med. 1979; 300(24):1350-8. DOI: 10.1056/NEJM197906143002402. View