Why the study?
Can a risk prediction model using six variables measured in the first week predict death during the first year after acute myocardial infarction in 7-day survivors?
Can a risk prediction model using six variables measured in the first week predict death during the first year after acute myocardial infarction in 7-day survivors?
A multivariate model incorporating six clinical and hemodynamic variables from the first week post-myocardial infarction can predict 1-year mortality with moderate sensitivity and specificity.
May aid early post-MI risk stratification; leaves open prospective validation and outcome impact in contemporary cohorts.
Patients who survived for the first seven days after acute myocardial infarction were followed up for a further 51 weeks. During these 51 weeks there were 123 deaths and 477 eventual survivors. Approximately half of the deaths occurred during the first 3 weeks of follow up. The deaths were predicted with 75% sensitivity and 73% specificity by a discriminant analysis based upon six variables seen during the first 7 days; predictions of death and survival were 55% and 92% accurate respectively. These six variables were, in ascending order of prognostic importance, the occurrence of bundle branch blocks, the administration of a diuretic, the age of the patient, the presence of diabetes mellitus, a previous myocardial infarction, and the ratio of the measured left ventricular pre-ejection and ejection periods. Many other monitored variables, although univariately associated with death, contributed nothing further to the multivariate assessment of mortality risk.
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B. J. Northover (1989) studied this question.
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