The Role of Complete Blood Count-Derived Inflammatory Biomarkers as Predictors of Infection After Acute Ischemic Stroke: A Single-Center Retrospective Study

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.

Keywords: biomarker; blood count; infection; inflammation; ischemic stroke; lymphocyte; monocyte; neutrophil; platelet; post-stroke infection.

Figure 1

Flowchart of study participants.

Figure 2

The median leukocyte count (p < 0.001) and platelet count (p = 0.592).

Figure 3

The medians of leukocyte and platelet indices between the infection and non-infection AIS groups. ABC: absolute basophil count, AEC: absolute eosinophil count, ANC: absolute neutrophil count, ALC: absolute lymphocyte count, AMC: absolute monocyte count, BLR: basophil to lymphocyte ratio, ELR: eosinophil to lymphocyte ratio, NLR: neutrophil to lymphocyte ratio, dNLR: derivative NLR, MLR: monocyte to lymphocyte ratio, MGLR: monocyte–granulocyte to lymphocyte ratio, BMR: basophil to monocyte ratio, EMR: eosinophil to monocyte ratio, NMR: neutrophil to monocyte ratio, LMR: lymphocyte to monocyte ratio, BPR: basophil to platelet ratio, MPR: monocyte to platelet ratio, PNR: platelet to neutrophil ratio, PLR: platelet to lymphocyte ratio, SIRI: systemic inflammatory response index, SII: systemic immune inflammation index.

Figure 4

Receiver operating characteristic (ROC) curves of complete blood count-derived inflammatory biomarkers: (A) Leukocyte and platelet count, (B) Absolute leukocyte differential count, (C) Ratio to lymphocytes, (D) Ratio to monocytes, (E) Ratio to platelets, (F) Ratio of platelets to neutrophils and lymphocytes, and (G) Systemic inflammatory index.