To describe the evolution patterns of cerebral hemodynamics in acute brain injury (ABI) patients.
Approach:
Data Sources: ABI patients with intracranial pressure (ICP), invasive arterial blood pressure, and heart rate (HR) records were identified from MIMIC-IV, eICU-CRD, and Longquan Hospital.
Modeling Techniques: Group-based multivariate trajectory (GBMT) modeling was used to identify clusters of participants with similar cerebral hemodynamics evolution patterns.
Statistical Analysis: Multivariate logistic regression analyzed the association between GBMT clusters and outcomes, with feature selection via random forest and SHAP values.
Key Findings:
Five clusters with distinct cerebral hemodynamics evolution patterns were identified.
Cluster 5 was associated with unfavorable outcomes compared to Cluster 1.
Sensitivity analysis showed consistent effect size and direction across different subgroups.
Interpretation:
The study identified a unique cerebral hemodynamics evolution pattern in ABI associated with unfavorable outcomes.
Limitations:
The study relies on retrospective data from databases, which may limit generalizability.
Potential confounding factors not accounted for in the analysis.
Conclusion:
Longitudinal analysis of cerebral hemodynamics in ABI patients may enhance understanding of patient outcomes.
For years, chronic stroke patients heard familiar feedback regarding their ability to regain strength and mobility after ischemic strokes caused upper-extremity deficits.
