The clinical value of inflammation index in predicting ICU mortality of critically ill patients with intracerebral hemorrhage

Bibliographic Data

ID22077827
AuthorsGuang Zhao (0000-0002-2048-6461, Jiangsu University, corresponding author), Yuting Gu (0009-0003-2431-1030, Jiangsu University), Zhaoxiang Wang (0000-0001-6577-0565, Jiangsu University), Yuyang Chen (0000-0002-5220-0501, Jiangsu University), Xiaohua Xia (0000-0001-5357-0048, Jiangsu University)
Year2024
Volume12
Pages1373585-1373585
Publication date2024-08-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1373585
PMID39157528
OpenAlexW4401277397
LanguageEN
References cited49

Background: The inflammatory response holds paramount significance in the context of intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates. Biological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) play crucial roles in influencing the systemic inflammatory response following ICH. This study aims to compare the predictive efficacy of NLR, PLR, LMR, SII, and SIRI concerning the risk of mortality in the intensive care unit (ICU) among critically ill patients with ICH. Such a comparison seeks to elucidate their early warning capabilities in the management and treatment of ICH. Methods: Patients with severe ICH requiring admission to the ICU were screened from the Medical Information Marketplace for Intensive Care (MIMIC-IV) database. The outcomes studied included ICU mortality and 30 day ICU hospitalization rates, based on tertiles of the NLR index level. To explore the relationship between the NLR index and clinical outcomes in critically ill patients with ICH, we utilized receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and multivariate logistic regression analysis. Results: A total of 869 patients (51.9% male) were included in the study, with an ICU mortality rate of 22.9% and a 30 day ICU hospitalization rate of 98.4%. Among the five indicators examined, both the ROC curve and DCA indicated that NLR (AUC: 0.660, 95%CI: 0.617-0.703) had the highest predictive ability for ICU mortality. Moreover, this association remained significant even after adjusting for other confounding factors during multivariate analysis (HR: 3.520, 95%CI: 2.039-6.077). Based on the results of the multivariate analysis, incorporating age, albumin, lactic acid, NLR, and GCS score as variables, we developed a nomogram to predict ICU mortality in critically ill patients with ICH. Conclusion: NLR emerges as the most effective predictor of ICU mortality risk among critically ill patients grappling with ICH when compared to the other four indicators. Furthermore, the integration of albumin and lactic acid indicators into the NLR nomogram enhances the ability to promptly identify ICU mortality in individuals facing severe ICH

Critically ill · Inflammation · Intensive care medicine · Intracerebral hemorrhage · Subarachnoid hemorrhage · Inflammation biomarkers and pathways · Inflammatory Biomarkers in Disease Prognosis · Intracerebral and Subarachnoid Hemorrhage Research · Medicine · Internal Medicine

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