Subphenotyping aneurysmal subarachnoid Hemorrhage using clinical and biological data clustering

Santafé, M; Quintana, M; Sánchez, A; Gràcia, RM; Campos-Fernandez, D; Abraira, L; Santamarina, E

doi:10.1016/j.jcrc.2025.155365

Neuroanesthesia & neurocritical care

Subphenotyping aneurysmal subarachnoid Hemorrhage using clinical and biological data clustering

J Crit CarePublished 28 Nov 2025Retrospective cohort study

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Authors' conclusion

Clustering analysis revealed two aSAH subphenotypes associated with DCI, mortality and functional.

Study context

Population: Adults with aneurysmal SAH admitted to the ICU, 2010–2021
Participants: 511 adults

Exposure: High-Risk vs Low-Risk Cluster
High-Risk Clustern = 301
Low-Risk Clustern = 210reference
Outcome: Distinct clinical subphenotypes of aneurysmal subarachnoid hemorrhage (aSAH) identified by clustering of clinical, radiological and laboratory data

Methodological detailsK-means clustering, principal component analysis

K-means clustering
Principal component analysis

Main finding

As reported in the abstract

Subphenotypes identified

High-Risk Cluster58.9 %301

Low-Risk Cluster41.1 %210

Observational data: associations, not effects.

Further findings

Serum S100B (subset of patients) · significantly elevated in the High-Risk Cluster · moderate discriminatory power

P = 0.008

High-Risk Cluster0.077 μg/Lrange 0.056–0.179

Low-Risk Cluster0.055 μg/Lrange 0.040–0.079

Serum serum biomarkers (S100B) (subset of patients) — S100B discriminatory power (AUC): 0.72

Original publication

Subphenotyping aneurysmal subarachnoid Hemorrhage using clinical and biological data clustering. J Crit Care. Published 28 November 2025. doi:10.1016/j.jcrc.2025.155365

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