Plasma glucose and not hemoglobin or renal function predicts mortality in patients with STEMI complicated with cardiogenic shock.
OBJECTIVE
To assess the predictive value of three biomarkers for mortality in ST-segment elevation myocardial infarction (STEMI) with cardiogenic shock.


BACKGROUND
STEMI complicated by cardiogenic shock accounts for the majority of STEMI related deaths. Patients with STEMI and hyperglycemia, anemia or kidney dysfunction on admission have a poor prognosis. As data on the combination of those three established predictors of mortality are sparse in STEMI with cardiogenic shock, the objective of the current study was to investigate their predictive value in STEMI patients with cardiogenic shock.


RESULTS
Between 1997 and 2005, a total of 3038 patients presented with STEMI and were treated with percutaneous coronary intervention (PCI). On admission 292 patients presented with cardiogenic shock. Glucose, hemoglobin and creatinine clearance were available in 183 out of 292 patients. Overall 1-year mortality was 34%. In multivariate logistic regression analysis, only glucose remained a strong independent predictor for mortality. The odds for mortality increased by 11% for each 1 mmol/l increase in glucose (OR 1.11, 95% CI 1.02-1.21, P = 0.013).


CONCLUSIONS
Hemoglobin and creatinine clearance bear no prognostic value. Only admission glucose levels strongly and independently predict 1-year mortality in STEMI patients with cardiogenic shock and treated with PCI.
Vis
Marije M
MM
Department of Cardiology, Academic Medical Center, Amsterdam, The Netherlands.
Engström
Annemarie E
AE
Sjauw
Krischan D
KD
Tjong
Fleur V Y
FV
Baan
Jan
J
Koch
Karel T
KT
DeVries
J Hans
JH
Tijssen
Jan G P
JG
de Winter
Robbert J
RJ
Piek
Jan J
JJ
Henriques
José P S
JP
D000368:Aged; D000740:Anemia / Q000097:blood / Q000150:complications / Q000401:mortality*; D015906:Angioplasty, Balloon, Coronary / Q000401:mortality; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism*; D016009:Chi-Square Distribution; D003404:Creatinine / Q000097:blood*; D005260:Female; D006454:Hemoglobins / Q000378:metabolism*; D006801:Humans; D006943:Hyperglycemia / Q000097:blood / Q000150:complications / Q000401:mortality*; D007668:Kidney / Q000378:metabolism / Q000503:physiopathology*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000097:blood / Q000150:complications / Q000401:mortality* / Q000503:physiopathology / Q000628:therapy; D009426:Netherlands; D016017:Odds Ratio; D010343:Patient Admission; D011446:Prospective Studies; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D012770:Shock, Cardiogenic / Q000097:blood / Q000209:etiology / Q000401:mortality* / Q000503:physiopathology; D013997:Time Factors; D016896:Treatment Outcome
D015415:Biomarkers; D001786:Blood Glucose; D006454:Hemoglobins; D003404:Creatinine