Development of an optimized multimarker strategy for early risk assessment of patients with acute coronary syndromes
Introduction
The evaluation of patients who present to the emergency department (ED) with chest pain suggestive of an acute coronary syndrome (ACS) is challenging. Many patients present with chest pain but only a minority have definite ACS and many, especially those who are older may have ACS without chest pain [1]. The diagnostic and prognostic value of cardiac troponin I (cTnI) in this situation is well established but its optimal use requires serial samples over time [2]. A multi-marker approach to risk stratification applied at the time of presentation might provide similar information in a more timely fashion and also identify those at risk, who do not manifest troponin elevations.
Increases in biomarkers upstream from biomarkers of necrosis, such as markers of inflammation, coagulation/fibrinolysis and markers of cardiac function, may be capable of fulfilling this role [3] and multiple studies have used this approach [4]. For example, increased concentrations of high sensitivity C-reactive protein (hsCRP) and N terminal-pro B-type natriuretic peptide (NT-proBNP) predict major adverse cardiac events independent of elevations in cardiac troponin [5]. D-dimer, a marker of fibrinolysis used to help diagnose pulmonary embolism has been shown to be helpful in the triage of patients with ACS [6]. Similarly, whole blood choline (WBCHO) predicts cardiac death, life-threatening cardiac arrhythmias, heart failure and the need for coronary intervention when measured at the time of presentation [7]. Lipoprotein-associated phospholipase A2 (Lp-PLA2), an inflammatory marker related to oxidized lipids, predicts cardiovascular endpoints in initially healthy subjects [8], [9], [10], [11] and in patients with atherosclerosis [12]. Another new marker, placental growth factor (PlGF), is thought to be a marker of plaque rupture [3] and may identify patients at risk for mortality independent of cardiac troponin and inflammatory markers [13] in patients with suspected ACS [4].
Although the ability to provide rapid measurements of multiple biomarkers with multiplex technology is near, the optimal method to define multimarker strategies is controversial. Thus, we employed both logistic regression methods and the use of a novel method called classification and regression tree (CART) analysis. The latter method allows probing of optimal cut-offs and the sequencing of marker determinations to optimally add information in a low to moderate risk population of the emergency department.
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Patients
Patients presenting to the ED at the Charité tertiary university clinic between May 22, 2002 and March 25, 2003 with suspected ACS were enrolled. The inclusion was based on the judgement of the attending physician to consider cardiac ischemia as cause of the acute symptoms and therefore a real life ED situation was investigated. Therefore, all patients with chest discomfort could be included. The sample consisted of 432 consecutive patients enrolled within a median of 6.6 h of onset of chest
Results
The characteristics of the overall study group of 432 are displayed in Table 1 along with the risk groups achieved by CART analysis (Fig. 2) with the 2 most predictive analytes, NT-proBNP and WBCHO. Significantly fewer patients in the low risk group underwent coronary angiography (30.8% vs 60.5% in the high risk group and 37.7% in the whole group). In patients with the final diagnosis NSTE-ACS 82.2% were scheduled for early invasive procedures. Patients with high risk were more likely male,
Discussion
The multifactorial pathophysiology of acute coronary syndromes and its potential complications is an important rationale for measurements of multiple biomarkers related to different underlying pathophysiological aspects in order to optimize early biochemical risk assessment. In addition, there are likely some patients at risk with non cardiovascular diseases who are part of this group as well and different markers may be more sensitive to this group as well [4]. However, the methods on how to
Conclusions
Our data demonstrate that the use of multiple markers can define groups at very low and very high risks with the use of the admission blood sample only. Logistic regression was augmented by CART analysis to select those cardiac biomarkers useful for optimal risk prediction and to define a sequence for their use. In this low-medium risk patients with ACS the combination of a marker of left ventricular dysfunction (NT-pro BNP), one of ischemia and plaque instability (WBCHO) and one of plaque
Acknowledgements
We thank Dr. Klaus Köhler, DadeBehring, Marburg, Germany and Robert Doss, Abbott, Chicago IL, for unrestricted research grants. We also acknowledge editorial assistance by Anne M. Gale, Editor in the Life Sciences. Dr. M. Möckel has full and unrestricted access to all data and takes responsibility for the integrity of the data and the accuracy of the data analysis. There are no financial disclosures to be made related to this work.
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