Hierarchical Cluster Analysis Identifies Distinct Physiological States After Acute Brain Injury.

ABSTRACT:

Background

Analysis of intracranial multimodality monitoring data is challenging, and quantitative methods may help identify unique physiological signatures that inform therapeutic strategies and outcome prediction. The aim of this study was to test the hypothesis that data-driven approaches can identify distinct physiological states from intracranial multimodality monitoring data.

Methods

This was a single-center retrospective observational study of patients with either severe traumatic brain injury or high-grade subarachnoid hemorrhage who underwent invasive multimodality neuromonitoring. We used hierarchical cluster analysis to group hourly values for heart rate, mean arterial pressure, intracranial pressure, brain tissue oxygen, and cerebral microdialysis across all incl

SUBMITTER: Rajagopalan S 

PROVIDER: S-EPMC11346511 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature