Predictive value of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in decompensated heart failure

Objective Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), which are new inflammatory markers, inexpensive, widely available, and obtained from routinely used test (complete blood count), have proved to be potential predictors of outcome in many cardiovascular diseases. The aim of this study was to investigate the predictive value of NLR and PLR in detecting HF and their effect on morbidity and mortality of patients with heart failure (HF). Patients and methods This prospective study included 60 patients diagnosed with acute decompensated HF and 40 age-matched and sex-matched healthy controls. Echocardiography was done for all participants to assess cardiac function. All participants were tested for biochemical parameters (urea, creatinine, and liver function tests). Complete blood count with calculation of NLR and PLR was done for all participants. Then all cases were followed up for occurrence of cardiovascular, cerebrovascular complications, history of hospitalization, and death during the period of the study. Results NLR and PLR of patients were significantly higher than controls (P<0.02 and <0.03, respectively). There was an inverse correlation between both PLR and NLR and left ventricular ejection fraction of the study population (P<0.01 and <0.02, respectively). PLR had 70% sensitivity and 47% specificity for prediction of HF with cutoff point more than 186, whereas NLR had 97% sensitivity and 47% specificity for prediction of HF with cutoff point more than 3.56. Moreover, PLR had 83% sensitivity and 58% specificity for prediction of mortality in those patients with decompensated HF with cutoff point more than 175, whereas NLR had 92% sensitivity and 33% specificity for prediction of mortality in those patients with decompensated HF with cutoff point more than 3.56, with average 1-year follow-up. Conclusion NLR and PLR are cheap, widely available inflammatory biomarkers that can be used to predict morbidity and mortality in patients with HF.

Abstract licence: CC BY-NC-ND

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