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Neutrophilia predicts death and heart failure after myocardial infarction: a community-based study
Adelaide M Arruda-Olson1, Guy S Reeder, Malcolm R Bell
1Division of Cardiovascular Diseases and Internal Medicine and the Department of Health Sciences Research, Mayo Clinic and Mayo Foundation, Rochester, MN 55905, USA.
Background:
The relationship between neutrophils and outcomes post-myocardial infarction (MI) is not completely characterized. We examined the associations of neutrophil count with mortality and post-MI heart failure (HF) and their incremental value for risk discrimination in the community.
Methods And Results:
MI was diagnosed with cardiac pain, biomarkers, and Minnesota coding of the ECG. Neutrophil count at presentation, reported as counts x10(9)/L, was categorized by tertiles (lower tertile, <5.7; middle tertile, 5.7 to 8.5; upper tertile, >8.5). From 1979 to 2002, 2047 incident MIs occurred in Olmsted County, Minn (mean age, 68+/-14 years; 44% women). Median (25th to 75th percentile) neutrophil count was 7.0 (5.1 to 9.5). Within 3 years post-MI, 577 patients died, and 770 developed HF. Overall survival and survival free of HF decreased with increased neutrophil tertile (P<0.001). Compared with the lower tertile, the age and sex adjusted hazard ratio for death was 1.44 (95% CI, 1.14 to 1.81) for the middle tertile and 2.60 (95% CI, 2.10 to 3.22) for the upper tertile (P<0.001). Similarly, for HF, the hazard ratio was 1.32 (95% CI, 1.09 to 1.59) for the middle and 2.12 (95% CI, 1.77 to 2.53) for the upper tertile (P<0.001). These associations persisted after adjustment for risk factors, comorbidities, Killip class, revascularization, and ejection fraction. Neutrophil count improved risk discrimination as indicated by increases in the area under the receiver operating characteristic curves (all P<0.05) and by the integrated discrimination improvement analysis (all P<0.001).
Conclusions:
In the community, the neutrophil count was strongly and independently associated with death and HF post-MI and improved risk discrimination over traditional predictors.
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