Abstract
Background and Objectives: Although a wide range of hematological parameters are used as blood-based inflammatory biomarkers, the role of complete blood count-derived inflammatory biomarkers in infection after acute ischemic stroke (AIS) is modest. Therefore, this study aimed to explore complete blood count-derived inflammatory biomarkers as predictors of infection after AIS. Materials and Methods: A single-center retrospective cross-sectional study was carried out at the National Brain Center Hospital Prof. Dr. dr. Mahar Mardjono, Jakarta, Indonesia, between 1 October 2023, and 31 March 2024, using medical records of hospitalized first-ever ischemic stroke patients who underwent a complete blood count within 24 h of admission. Based on complete blood count-derived inflammatory biomarkers, this study included absolute numbers and related ratios or indices. Results: In total, 163 patients met the study criteria. The diagnosis of infection after AIS was established using reliable clinical symptoms and/or guidelines of the disease. According to the status of infection after AIS, the subjects were categorized into two groups, including 24 patients in the infection group and 139 patients in the non-infection group. Biomarkers that had significant accuracy (higher sensitivity and specificity, respectively) in predicting infection were the leukocyte count (LC; 70.8%, 74.1%, p < 0.001), absolute neutrophil count (ANC; 66.7%, 79.9%, p < 0.001), absolute monocyte count (AMC; 75.0%, 63.3%, p = 0.001), neutrophil to lymphocyte ratio (NLR; 62.5%, 71.9%, p = 0.003), derivative NLR (dNLR; 50.0%, 78.4%, p = 0.003), monocyte-granulocyte to lymphocyte ratio (MGLR; 62.5%, 73.0%, p = 0.003), systemic inflammatory response index (SIRI; 62.5%, 79.0%, p = 0.001), and systemic immune inflammation index (SII; 87.5%, 44.0%, p = 0.012) with chances of 74.4%, 75.4%, 71.0%, 69.0%, 68.7%, 69.3%, 73.4%, and 66.2%, respectively. Conclusions: Considering the overall ROC curve used to evaluate the complete blood count-derived inflammatory biomarkers, ANC has a better ability to predict infection in AIS patients, as denoted by the highest AUC, suggesting a 75.4% chance of correctly discriminating patients with infection after stroke.