Accuracy of a Neural Diagnostic Tree for the Identification of Acute Coronary Syndrome in Patients With Chest Pain and No ST-Segment Elevation

Abstract

Identifying acute coronary syndrome is a difficult task in the emergency department because symptoms may be atypical and the electrocardiogram has low sensitivity. In this prospective cohort study done in a tertiary community emergency hospital, we developed and tested a neural diagnostic tree in 566 consecutive patients with chest pain and no ST-segment elevation for the diagnosis of acute coronary syndrome. Multivariate regression and recursive partitioning analysis allowed the construction of decision rules and of a neural tree for the diagnosis of acute myocardial infarction and acute coronary syndrome. Predictive variables of acute coronary syndrome were: age > or =60 years (odds ratio [OR] = 2.3; P = 0.0016), previous history of coronary artery disease (OR = 2.9; P = 0.0008), diabetes (OR = 2.8; P = 0.0240), definite/probable angina-type chest pain (OR = 17.3; P = 0.0000) and ischemic electrocardiogram (ECG) changes on admission (OR = 3.5; P = 0.0002). The receiver operating characteristic curve of possible diagnostic decision rules of the regression model disclosed a C-index of 0.904 (95% confidence interval = 0.878 to 0.930) for acute coronary syndrome and 0.803 (95% confidence interval 0.757 to 0.849) for acute myocardial infarction. For both disorders, sensitivities of the neural tree were 99% and 93%, respectively, and negative predictive values were both 98%. Negative likelihood ratios were 0.02 and 0.1, respectively. It is concluded that this simple and easy-to-use neural diagnostic tree was very accurate in the identification of non-ST segment elevation chest pain patients without acute coronary syndrome. Patients identified as low probability of disease could receive immediate stress testing and be discharged if the test is negative.

Diagnostic accuracy of clinical prediction rules to exclude acute coronary syndrome in the emergency department setting: a systematic review

“…[16][17][18][19][20][21]25 The reference standard was not reported in 1 study. 15 Of the 8 studies, 6 did not clearly specify that the index test was interpreted without knowledge of results of the reference standard, 15,17,18,20,21,25 nor did it specify that the reference standard was interpreted without knowledge of the results of the index test. Table 2 scores, diagnostic testing and prevalence of disease for each study.…”

“…Three of the prediction rules were derived but not validated (level 4 in hierarchy of evidence). 15,16,21 Bassan and colleagues 15 classified the type of chest pain according to the likelihood of ACS and based subsequent diagnostic testing on this assessment. This increased the risk of verification bias (i.e., failure to use the same gold standard on all patients), potentially overestimating diagnostic performance.…”

“…Review of the full articles in phase II identified 8 that met inclusion criteria (κ = 0.85). [15][16][17][18][19][20][21] Two additional articles were selected for further review from the bibliographies of selected articles. 22,23 On full text review these were excluded because one retrospectively analyzed data that was originally collected from 2 large clinical trials 22 and the other required the use of a computer to generate diagnostic probabilities.…”

Development and validation of a prediction rule for early discharge of low-risk emergency department patients with potential ischemic chest pain

“…11 Few studies have attempted to derive a clinical prediction rule to identify patients who can be safely discharged without further investigations, such as provocative testing or imaging. Bassan and colleagues developed a decision rule incorporating the clinical likelihood of ACS-patients selectively received investigations to confirm or refute the presence of disease, ensuring a varying ''gold standard'' for ACS diagnosis, 12 whereas Fernandez Portales and colleagues had cardiologists enrol patients with a high clinical suspicion of ACS 13 ; hence, the resulting rule may have limited generalizability in an ED setting.…”

Incorporation of Biomarkers with the Renal Angina Index for Prediction of Severe AKI in Critically Ill Children

“…Repeated evidence highlights the erosion of troponin performance when measured in patients without chest pain or at low clinical risk of myocardial infarction from coronary disease (10)(11)(12)(13)(14)(15)(16). In addition, independent of troponin, the absence of cardiac angina carries high negative predictive value for the diagnosis of a heart attack (17,18). Capricious, undirected use of any biomarker degrades its effectiveness.…”