Clinical, electrocardiographic, and biochemical data for immediate risk stratification in acute coronary syndromes

Comparative prognostic value of T-wave inversion and ST-segment depression on the admission electrocardiogram in non-ST-segment elevation acute coronary syndromes

BACKGROUND

ST-segment depression (STD) is predictive of adverse outcomes in non-ST-segment elevation acute coronary syndromes (NSTE-ACS), but there are conflicting data on the incremental prognostic value of T-wave inversions (TWIs) on the admission electrocardiogram.

METHODS

Admission electrocardiograms of 7,343 patients with NSTE-ACS from the Global Registry of Acute Coronary Events (GRACE) and ACS I registry were independently analyzed at a core laboratory and stratified by TWI and STD status. We performed multivariable analyses to determine the independent prognostic significance of TWI and tested for interaction between TWI and STD for adverse outcomes.

RESULTS

Patients with TWI and/or STD had a higher prevalence of cardiovascular risk factors, higher Killip class, and higher GRACE risk scores. Among the 2,708 patients with available angiographic data, rates of 3-vessel or left main disease were similar between patients with TWI and those without TWI/STD. After adjusting for other established prognosticators, TWI did not independently predict in-hospital (adjusted odds ratio 1.03, 95% CI 0.75-1.42, P = .85) or 6-month mortality (adjusted odds ratio 1.02, 95% CI 0.80-1.30, P = .88); STD remained a strong independent predictor. There was no interaction between TWI and STD for these outcomes. No contiguous lead groups or cumulative number of leads with TWI provided independent prognostic information.

CONCLUSIONS

TWI is associated with other high-risk clinical features but is not an independent predictor of adverse short- and long-term mortality in NSTE-ACS. T-wave inversion does not provide additional prognostication beyond the GRACE risk model, and its concomitant presence does not alter the prognostic value of STD.

How can we identify low- and high-risk patients among unselected patients with possible acute coronary syndrome?

OBJECTIVE

Prognosis among patients admitted with possible acute coronary syndrome (ACS) may differ from that of patients with definite ACS. The aim of this study was to identify risk factors for mortality among unselected patients and to use the statistical model to identify patients at low or high mortality risk.

METHODS

From April 1, 2000, to March 31, 2002, we identified all consecutive patients aged 30 to 69 years admitted to the 2 coronary care units covering the municipality of Aarhus, Denmark (population, 138,290). ACS was considered a possible diagnosis if the physician at admission (1) had noted the presence or absence of chest pain, (2) performed a 12-lead electrocardiogram, and (3) measured markers of myocardial necrosis. In 1576 consecutive patients these criteria were fulfilled.

RESULTS

By logistic regression, predictors of mortality were age 60 and older, ST elevation, right bundle-branch block, arrhythmia, elevated markers of myocardial necrosis, and the diagnosis of ACS. The predictive validity of the model, as indicated by receiver operating characteristic curve area, was 85.7%, 87.8%, and 80.1% for 7-, 30-, and 365-day mortality, respectively.

CONCLUSIONS

Mortality may be predicted with high precision based on a statistical model. Identification of survivors by the use of a statistical model was superior as compared to simply ruling out the clinical diagnosis of ACS.

Cardiac markers of acute coronary syndromes: is there a case for point-of-care testing?

OBJECTIVE

Major challenges for physicians include selection of effective tests in the time-sensitive identification and management of patients with acute coronary syndromes (ACS). We review whether cardiac marker testing performed at the point-of-care (POC) has an impact on clinical management and guidance of intervention for ACS patients.

DESIGN AND METHODS

Evidence from recently published studies and meta-analyses supports the efficacy of cardiac markers. Technologies and specifications of all currently available POC tests for monitoring cardiac markers are surveyed. Finally, a series of questions to investigate the utility of cardiac markers, and their measurement by POC tests, for clinical management and guidance of therapy for ACS patients, are addressed.

RESULTS

Cardiac troponins are clearly the best markers for the definitive detection of myocardial infarction. Compelling evidence for the utility of troponins in risk stratification and guidance of intervention for ACS patients has resulted in inclusion of cardiac markers in clinical guidelines. Rapid multi-analyte POC tests, few of which exhibit harmony with central laboratory assays, have facilitated the use of cardiac markers for clinical management and guidance of therapy.

CONCLUSIONS

Given the need to minimize vein-to-brain time, it is expected that point-of-care testing of cardiac markers will take a leading role in management of ACS patients.