ArticleFrontiers in medicine2022
A novel risk model based on white blood cell-related biomarkers for acute kidney injury prediction in patients with ischemic stroke admitted to the intensive care unit.
Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Prediction Models for Acute Kidney Injury in Stroke Patients: A Systematic Review.Brain and behavior · 2026Pooled it
- Linear correlation between white blood cell counts and the progression and prognosis of acute kidney injury.The Journal of international medical research · 2025Trial
- Development of a prediction model for acute kidney injury in critically ill patients with advanced colorectal cancer based on white blood cell-related indicators.Frontiers in oncology · 2026Article
- The association between white blood cell-to-hemoglobin ratio and mortality risk in critical traumatic brain injury: insights from MIMIC-IV retrospective analysis.European journal of medical research · 2025Article
- A low preoperative platelet-to-white blood cell ratio is associated with acute kidney injury following cerebral aneurysm treatment in South Korea.Acute and critical care · 2025Article
- A Predictive Model for Acute Kidney Injury Based on Leukocyte-Related Indicators in Hepatocellular Carcinoma Patients Admitted to the Intensive Care Unit.Mediators of inflammation · 2025Article
- Article
- Sex differences in clinical risk factors in obese ischemic stroke patients with a history of smoking.BMC cardiovascular disorders · 2024Article
- Exploring the utility of a latent variable as comprehensive inflammatory prognostic index in critically ill patients with cerebral infarction.Frontiers in neurology · 2024Article
- Prognostic Value of Leukocyte-Based Risk Model for Acute Kidney Injury Prediction in Critically Ill Acute Exacerbation of Chronic Obstructive Pulmonary Disease Patients.International journal of chronic obstructive pulmonary disease · 2024Article
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6 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Conventional systemic inflammatory biomarkers could predict prognosis in patients with ischemic stroke (IS) admitted to the intensive care unit (ICU). Acute kidney injury (AKI) is common in patients with IS admitted to ICU, but few studies have used systemic inflammatory biomarkers to predict AKI in critically ill patients with IS. This study aimed to establish a risk model based on white blood cell (WBC)-related biomarkers to predict AKI in critically ill patients with IS. Methods: Data were extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) for a training cohort, and data were extracted from the Medical Information Mart for eICU Collaborative Research Database (eICU-CRD) for a validation cohort. Logistic regression analysis was used to determine the significant predictors of WBC-related biomarkers on AKI prediction, and a risk model was established based on those significant indicators in multivariate logistic regression. The receiver operating characteristics (ROC) curve was utilized to obtain the best cut-off value of the risk model. The Kaplan-Meier curve was used to evaluate the prognosis-predictive ability of the risk model. Results: The overall incidence of AKI was 28.4% in the training cohort and 33.2% in the validation cohort. WBC to lymphocyte ratio (WLR), WBC to basophils ratio (WBR), WBC to hemoglobin ratio (WHR), and neutrophil to lymphocyte ratio (NLR) could independently predict AKI, and a novel risk model was established based on WLR, WBR, WHR, and NLR. This risk model depicted good prediction performance both in AKI and other clinical outcomes including hemorrhage, persistent AKI, AKI progression, ICU mortality, and in-hospital mortality both in the training set and in the validation set. Conclusion: A risk model based on WBC-related indicators exhibited good AKI prediction performance in critically ill patients with IS which could provide a risk stratification tool for clinicians in the ICU.
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