Association Between Glasgow Coma Scale Trajectory and In-Hospital Mortality in Traumatic Brain Injury in the ICU: A Retrospective Cohort Study.

Abstract

Background: Glasgow Coma Scale (GCS) is fundamental for neurological assessment in traumatic brain injury (TBI) patients. Traditional single-point GCS measurements fail to capture the dynamic nature of brain injury progression, limiting nurses' ability to identify at-risk patients and implement timely interventions.

Aims: To investigate the dynamic trajectories of the GCS during the first 24 h in ICU and their association with in-hospital mortality in adult TBI patients, providing evidence for nursing neurological assessment and care planning.

Results: Five distinct GCS trajectory groups were identified: stable low level (G1, 3-8 points), stable intermediate level (G2, 9-12 points), stable medium-high level (G3, around 13 points), stable high level (G4, close to 15 points) and increasing (G5, from medium to medium-high level). Compared to G1, in-hospital mortality was significantly reduced in all other groups (G2-G5). Significant interactions were found between GCS trajectories and both age and heart failure status (all interaction p < 0.05), indicating these factors modified the relationship between GCS patterns and mortality.

Conclusion: Dynamic GCS trajectory analysis provides superior prognostic information compared to static assessments. Age and heart failure significantly modify the relationship between GCS patterns and mortality outcomes, requiring careful consideration in nursing assessment of TBI patients.

Relevance to clinical practice: These findings enable nurses to recognise neurological evolution patterns rather than relying on isolated measurements. Trajectory analysis helps identify high-risk patients requiring vigilant monitoring and those showing improvement patterns suitable for rehabilitation consideration. Particularly in elderly and heart failure patients, GCS trajectories should be interpreted with caution, as similar patterns may have different prognostic implications. Incorporating trajectory pattern recognition enhances care planning, resource allocation and team communication across shifts.