Routinely analyzed leukocyte characteristics improve prediction of mortality after coronary angiography

Abstract

Background: Inflammation and leukocyte infiltration are hallmarks of atherosclerosis. Clinically routine hematology analyzers mostly perform an entire differential blood count by default, irrespective of the requested parameter. We hypothesize that these normally unreported leukocyte characteristics associate with coronary artery disease (CAD) severity and can improve prediction of mortality in coronary angiography patients.

Methods: We studied coronary angiography patients suspected of CAD (n = 1015) from the Utrecht Coronary Biobank cohort. Leukocyte characteristics were routinely assessed in blood drawn directly prior to angiography using an automated hematology analyzer and extracted from the Utrecht patient oriented database (UPOD) database. Patients were followed up for a median duration of 805 days, during which 65 patients died. We evaluated the association of leukocyte characteristics with synergy between PCI with taxus and cardiac surgery (SYNTAX) score as a measure of CAD severity, all-cause and cardiovascular mortality and major adverse cardiovascular events (MACEs). In order to determine the improvement of risk prediction, we calculated continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI).

Results: Monocyte percentage showed strong independent predictive value for all-cause mortality (hazard ratio (HR) 1.44 (1.19-1.74), p < 0.001), and the monocyte-to-lymphocyte ratio performed best for cardiovascular mortality (HR 1.42 (1.11-1.81), p = 0.005). The cNRIs and IDIs of leukocyte characteristics for all-cause mortality confirmed the improvement in mortality risk prediction. No significantly predictive leukocyte characteristics were found for MACEs.

Conclusion: Readily available yet unreported leukocyte characteristics from routine hematology analyzers significantly improved prediction of mortality in coronary angiography patients on top of clinical characteristics.

Keywords: Prediction; coronary angiography; leukocytes.