Trajectory clustering of immune cells and its association with clinical outcomes after aneurysmal subarachnoid hemorrhage.

Abstract

Background and purpose: The immune response following aneurysmal subarachnoid hemorrhage (aSAH) can exacerbate secondary brain injury and impact clinical outcomes. As the immune response after aSAH is a dynamic process, we aim to track and characterize immune cell trajectories over time to identify patterns associated with various clinical outcomes.

Methods: In this retrospective single-center study of patients with aSAH, we analyzed immune cell count trajectories, including neutrophil, monocyte, and lymphocyte counts, collected from day 1 to day 14. These trajectories were classified into four distinct clusters utilizing the k-means longitudinal clustering method. A comprehensive multivariable analysis was performed to explore the associations of these immune cell clusters with various clinical outcomes. These outcomes included a Modified Rankin Scale score (mRS) of 3 to 6, indicative of poor functional outcomes, along with complications including shunt dependency, vasospasm, and secondary cerebral infarction.

Results: In this study, 304 patients with aSAH were analyzed. The trajectories of immune cell counts, including neutrophils, monocytes, and lymphocytes, were successfully categorized into four distinct clusters for each immune cell type. Within neutrophil clusters, both persistent neutrophilia and progressive neutrophilia were associated with poor functional outcomes, shunt dependency, and vasospasm, with resolving neutrophilia showing a lesser degree of these associations. Within monocyte clusters, early monocytosis was associated with vasospasm, whereas delayed monocytosis was associated with shunt dependency. Within lymphocyte clusters, both early transient lymphopenia and early prolonged lymphopenia were associated with poor functional outcomes.

Conclusion: Our study demonstrates that distinct immune cell trajectories post-aSAH, identified through unsupervised clustering, are significantly associated with specific clinical outcomes. Understanding these dynamic immune responses may provide key insights with potential for future therapeutic strategies.