Systemic Immune-Inflammation Index Predicts the Prognosis of Traumatic Brain Injury.

World Neurosurg

Department of Neurosurgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, China; Department of Neurosurgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China; Neurosurgical Institute of Nan

Published: March 2024


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Objective: Systemic inflammation following traumatic brain injury (TBI) has been extensively studied over the past decades, as it contributes significantly to the pathophysiological injury mechanisms and subsequent poor outcomes. Systemic immune-inflammation (SII) index is a novel biomarker of systemic inflammatory response. However, its predictive value regarding TBI prognosis in clinical practice remains insufficiently investigated.

Methods: A total of 102 TBI patients admitted to Nanjing Drum Tower Hospital from July 2019 to February 2022 were enrolled. We employed various statistical analyses to evaluate the correlation between inflammatory indicators upon admission and patient prognosis, compared the predictive accuracy of these indicators, and generated receiver operating curve analysis to test their prognostic performance.

Results: The SII index, platelet count, absolute lymphocyte count, and neutrophil/lymphocyte ratio (NLR) were capable of distinguishing TBI prognosis according to univariate logistic regression models (P < 0.05). Multivariate logistic regression models revealed that increased SII index, platelet count, and NLR upon admission were independent predictors of poor TBI prognosis (P < 0.05). Receiver operating curve analysis further demonstrated that the SII index (area under the curve = 0.845, 95% confidence interval 0.769-0.921, P = 0.000) exhibited higher predictive ability than the NLR (area under the curve = 0.694, 95% confidence interval 0.591-0.796, P = 0.001).

Conclusions: Our findings suggested that increased SII index during the early stages of TBI was an independent risk factor for poor prognosis with satisfactory predictive value. The SII index provides a reliable, convenient, and cost-effective prognostic model to evaluate systemic inflammation after TBI and identify patients at risk of poor outcomes, thereby offering valuable guidance for clinical practice.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.wneu.2023.10.081DOI Listing

Publication Analysis

Top Keywords

tbi prognosis
12
systemic immune-inflammation
8
traumatic brain
8
brain injury
8
systemic inflammation
8
poor outcomes
8
clinical practice
8
receiver operating
8
operating curve
8
curve analysis
8

Similar Publications

Traumatic brain injuries (TBI) represent a leading cause of morbidity and mortality globally. Whilst clinical care has significantly improved in recent years, there is still significant scope to improve patient outcomes, particularly in relation to quality of life. However, there is a window of opportunity for clinical intervention, since most of the mortality and morbidity is associated with secondary injury processes that arise after the initial trauma.

View Article and Find Full Text PDF

Diffuse axonal injury (DAI) is one of the most severe consequences of traumatic brain injury (TBI), characterized by widespread axonal damage in the cerebral white matter. DAI plays a crucial role in determining clinical outcomes, significantly contributing to long-term disability and mortality in severe cases. Despite advancements in neuroscience and clinical management, the diagnosis and prognosis of DAI remain challenging due to its complex pathophysiology and the difficulty of detecting axonal damage in its early stages.

View Article and Find Full Text PDF

Predictors of functional recovery in the first year after severe traumatic brain injury.

Braz J Phys Ther

August 2025

Laboratory of Neurorehabilitation and Neuromodulation, Universidade Federal do Espírito Santo, Espírito Santo, Brazil; Baylor Scott & White Research Institute, Dallas, TX, , United States; Baylor Scott & White Institute for Rehabilitation, Dallas, TX, United States. Electronic address: fernandozan

Introduction: Traumatic Brain Injury (TBI) survivors often experience long-term impairments that might decrease their quality of life and functional independence.

Objective: This study aimed to identify predictors of functional recovery after severe TBI in Brazil.

Methods: A prospective observational cohort study was conducted at a trauma referral hospital between May 2021 and May 2022.

View Article and Find Full Text PDF

Traumatic brain injury (TBI) is one of the most prevalent health conditions, with severity assessment serving as an initial step for management, prognosis, and targeted therapy. Existing studies on automated outcome prediction using machine learning (ML) often overlook the importance of TBI features in decision-making and the challenges posed by limited and imbalanced training data. Furthermore, many attempts have focused on quantitatively evaluating ML algorithms without explaining the decisions, making the outcomes difficult to interpret and apply for less-experienced doctors.

View Article and Find Full Text PDF

Management of traumatic brain injury (TBI) patients on pre-TBI antithrombotic medications poses a clinical challenge in everyday practice. However, the safety profiles of antiplatelets (APs) have not been systematically studied and compared to anticoagulants (ACs) in this patient population. In this PRISMA-compliant systematic review the EMBASE and MEDLINE databases were systematically queried to identify comparative studies in patients with TBI and pre-injury AP and AC medications.

View Article and Find Full Text PDF