Improved survival after acute myocardial infarction in patients with advanced Killip class.
BACKGROUND
The continuing applicability of the Killip classification system to the effective stratification of long-term and short-term outcome in patients with acute myocardial infarction (MI) and its influence on treatment strategy calls for reanalysis in the setting of today's primary reperfusion treatments.


OBJECTIVE
Our study sought to test the hypothesis that Killip classification, established on admission in patients with acute MI, is an effective tool for early prediction of in-hospital mortality and long-term survival.


METHODS
A series of 909 consecutive Olmsted County patients admitted with acute MI to St. Marys Hospital, Mayo Clinic, between January 1988 and March 1998 was analyzed. Killip classification was the primary variable. Endpoints were in-hospital death, major in-hospital complications, and post-hospital death.


RESULTS
Patients analyzed included 714 classified as Killip I, 170 classified as Killip II/III, and 25 classified as Killip IV. Increases in in-hospital mortality and prevalence of in-hospital complications correspond significantly with advanced Killip class (p < 0.01), with in-hospital mortality 7% in class I, 17.6% in classes II/III, and 36% in class IV patients (p < 0.001). Killip classification was strongly associated with mode of therapy administered within 24 h of admission (p < 0.01). Killip IV patients underwent primary angioplasty most commonly and were less likely to receive medical therapy.


CONCLUSIONS
Killip classification remains a strong independent predictor of in-hospital mortality and complications, and of long-term survival. Early primary angioplasty has contributed to a decrease in mortality in Killip IV patients, but effective adjunctive medical therapy is underutilized.
Miller
W L
WL
Division of Cardiovascular Diseases, Mayo Clinic and Foundation, Rochester, MN 55905, USA.
Wright
R S
RS
Grill
J P
JP
Kopecky
S L
SL
D000368:Aged; D016009:Chi-Square Distribution; D003710:Demography; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008910:Minnesota / Q000453:epidemiology; D009203:Myocardial Infarction / Q000145:classification* / Q000401:mortality*; D011379:Prognosis; D016016:Proportional Hazards Models; D012008:Recurrence; D018570:Risk Assessment; D016019:Survival Analysis