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Updated: Jun 19, 2026
A Low Mortality Rat Model to Assess Delayed Cerebral Vasospasm After Experimental Subarachnoid Hemorrhage
Published on: January 17, 2013
Interrelationships Between Inflammatory Score, Delayed Cerebral Ischemia and Unfavorable Outcome in Patients with
Peng Zhang1,2, Haiyang Zhu1,2, Xinbo Li1,2
1Department of Neurosurgery, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
Insights
A new inflammatory score, using lymphocyte, PIV, RDW, and LDH, accurately predicts delayed cerebral ischemia (DCI) and poor outcomes in aneurysmal subarachnoid hemorrhage (aSAH) patients. This score improves risk prediction, highlighting DCI
Area of Science:
- Neuroscience
- Biomarkers
- Inflammation
Background:
- Aneurysmal subarachnoid hemorrhage (aSAH) poses significant risks, including delayed cerebral ischemia (DCI) and poor patient outcomes.
- Effective risk stratification is crucial for managing aSAH patients and improving clinical decision-making.
Purpose of the Study:
- To develop and validate an integrated inflammatory score for enhanced prediction of DCI and poor outcomes in aSAH.
- To investigate the mediating and interacting roles of DCI in the relationship between inflammation and poor outcomes using four-way effect decomposition.
Main Methods:
- Machine learning algorithms were utilized for biomarker selection and the construction of an inflammatory score.
- Multivariate logistic regression analyzed the association between the inflammatory score and DCI/poor outcomes.
- Four-way decomposition assessed mediation and interaction effects of DCI on the inflammation-outcome relationship.
Main Results:
- The inflammatory score, combining lymphocyte, pan-immune-inflammation value (PIV), red blood cell distribution width (RDW), and lactate dehydrogenase (LDH), was calculated for 368 aSAH patients.
- The inflammatory score was independently associated with DCI and poor outcomes.
- DCI partially mediated the effect of high inflammatory score on poor outcomes, with significant mediation and interaction components (3.60% mediation only, 38.89% mediated interaction).
- Adding the inflammatory score to predictive models significantly improved discrimination (AUC increased from 0.772 to 0.822, NRI 5.3%, IDI 6.9%).
Conclusions:
- The developed inflammatory score is a significant predictor of DCI and poor outcomes in aSAH patients.
- DCI plays a crucial role as a mediator and interacts synergistically with the inflammatory score in determining poor outcomes.
- The inflammatory score offers additive value for risk prediction in aSAH, aiding clinical management.
Background:
To identify biomarkers and develop an inflammatory score based on proper integration to improve risk prediction of delayed cerebral ischemia (DCI) and poor outcome in patients with aneurysmal subarachnoid hemorrhage (aSAH). We also further explore the mediation and interaction of DCI within the chain of events using the four-way effect decomposition.
Methods:
Machine learning algorithms are used for biomarker selection and constructed the inflammatory score. Multivariate logistic regression was performed to identify the association of inflammatory score with DCI and poor outcome. Next, we employed a four-way decomposition to assess the extent to which the inflammation effect on the risk of poor outcome is mediated by or interacts with DCI. Finally, the additive value of inflammatory score was measured using the area under the curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI).
Results:
In total, 368 aSAH patients were included. The inflammatory score was calculated with the combination of lymphocyte, pan-immune-inflammation value (PIV), red blood cell distribution width (RDW), and lactate dehydrogenase (LDH). Multivariate analysis identified that inflammatory score was independently associated with DCI and poor outcome. The effect of high inflammatory score on poor outcome may be partly explained by DCI, where there is both pure mediation and mediated interaction. With DCI as a potential mediator, the excess relative risk could be decomposed into 30.86% controlled direct effect, 3.60% mediation only, 26.64% interaction only, and 38.89% mediated interaction. Adding the inflammatory score to the predictive model improved the AUC from 0.772 to 0.822, with an NRI of 5.3% and IDI of 6.9%.
Conclusion:
The inflammatory score was significantly associated with DCI and poor outcome in patients with aSAH. Not only may be a potential synergistic interaction between high inflammatory score and DCI on the risk of poor outcome but also where DCI is an important mediating mechanism.
