PREDICTORS OF 30-DAY MORTALITY IN THE ERA OF REPERFUSION FOR ACUTE MYOCARDIAL-INFARCTION - RESULTS FROM AN INTERNATIONAL TRIAL OF 41 021 PATIENTS

Background Despite remarkable advances in the treatment of acute myoca rdial infarction, substantial early patient mortality remains. Appropr iate choices among alternative therapies and the use of clinical resou rces depend on an estimate of the patient's risk. Individual patients reflect a combination of clinical features that influence prognosis, a nd these factors must be appropriately weighted to produce an accurate assessment of risk. Prior studies to define prognosis either were per formed before widespread use of thrombolysis or were limited in sample size or spectrum of data. Using the large population of the GUSTO-I t rial, we performed a comprehensive analysis of relations between basel ine clinical data and 30-day mortality and developed a multivariable s tatistical model for risk assessment in candidates for thrombolytic th erapy. Methods and Results For the 41 021 patients enrolled in GUSTO-I , a randomized trial of four thrombolytic strategies, relations betwee n clinical descriptors routinely collected at initial presentation, an d death within 30 days (which occurred in 7% of the population) were e xamined with both univariable and multivariable analyses. Variables st udied included demographics, history and risk factors, presenting char acteristics, and treatment assignment. Risk modeling was performed wit h logistic multiple regression and validated with bootstrapping techni ques. Multivariable analysis identified age as the most significant fa ctor influencing 30-day mortality, with rates of 1.1% in the youngest decile (<45 years) and 20.5% in patients >75 (adjusted chi(2)=717, P<. 0001). Other factors most significantly associated with increased mort ality were lower systolic blood pressure (chi(2)=550, P<.0001), higher Killip class (chi(2)=350, P<.0001), elevated heart rate (chi(2)=275, P<.0001), and anterior infarction (chi(2)=143, P<.0001). Together, the se five characteristics contained 90% of the prognostic information in the baseline clinical data. Other significant though less important f actors included previous myocardial infarction, height, time to treatm ent, diabetes, weight, smoking status, type of thrombolytic, previous bypass surgery, hypertension, and prior cerebrovascular disease. Combi ning prognostic variables through logistic regression, we produced a v alidated model that stratified patient risk and accurately estimated t he likelihood of death. Conclusions The clinical determinants of morta lity in patients treated with thrombolytic therapy within 6 hours of s ymptom onset are multifactorial and the relations complex. Although a few variables contain most of the prognostic information, many others contribute additional independent prognostic information. Through cons ideration of multiple characteristics, including age, medical history, physiological significance of the infarction, and medical treatment, the prognosis of an individual patient can be accurately estimated.