B. ó Hartaigh
- Which leukocyte subsets predict cardiovascular mortality? From the LUdwigshafen RIsk and Cardiovascular Health (LURIC) Study
- Volume | Issue number
- 224 | 1
- Pages (from-to)
- Document type
- Faculty of Social and Behavioural Sciences (FMG)
- Psychology Research Institute (PsyRes)
Objective: White blood cells are known to predict cardiovascular mortality, but form a highly heterogeneous population. It is therefore possible that specific subtypes disproportionally contribute to the prediction of cardiovascular outcomes. Therefore, we compared leukocyte subsets alone and in conjunction with an established inflammatory marker, C-reactive protein, for predicting death due to cardiovascular disease in a high-risk population.
Methods: Patients, 3316, (mean [SD] age, 62  years) scheduled for coronary angiography were prospectively followed up. Neutrophil, monocyte and lymphocyte counts were determined. Neutrophil and monocyte subsets were further analysed on the basis of surface expression of CD11b, CD18, CD31, CD40 and CD58. Lymphocytes were further subdivided into CD3, CD4, CD8, and CD19 subsets. The association between each marker and subsequent cardiovascular mortality was assessed using multivariable Cox regression models.
Results: During a median follow-up period of 7.8 years, 745 (22.5%) patients died, of which 484 were due to cardiovascular events. After entering conventional risk factors and removing patients with a current infection, neutrophil count (HR [95% CI] = 1.90 [1.39, 2.60], P < 0.001) and the neutrophil/lymphocyte ratio (HR [95% CI] = 1.68 [1.24, 2.27], P = 0.003) emerged as independent predictors of cardiovascular mortality. After mutual adjustment, neutrophil count (HR [95% CI] = 1.87 [1.35, 2.50], P < 0.001) out-performed C-reactive protein (HR [95% CI] 1.32 [0.99, 1.78], P = 0.06) as a predictor of cardiovascular mortality.
Conclusions: Due to its predictive potential and inexpensive determination, assessment of high neutrophil counts may represent an important marker, possibly improving cardiovascular mortality risk prediction.
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