Related Experiment Video
Updated: Jun 3, 2025
Isolation and Flow Cytometric Analysis of Immune Cells from the Ischemic Mouse Brain
Published on: February 12, 2016
The Role of Complete Blood Count-Derived Inflammatory Biomarkers as Predictors of Infection After Acute Ischemic
Weny Rinawati1,2, Abdulloh Machin3,4,5, Aryati Aryati5,6
1Doctoral Program of Medical Science, Faculty of Medicine, Universitas Airlangga, Surabaya 60132, Indonesia.
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.
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.
More Related Videos
10:03Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
12:42Stereological and Flow Cytometry Characterization of Leukocyte Subpopulations in Models of Transient or Permanent Cerebral Ischemia
Published on: December 28, 2014
Related Concept Videos
01:20Blood Studies for Cardiovascular System I: Cardiac Biomarkers
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
01:19Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...