Intracranial lesion features in moderate-to-severe traumatic brain injury: relation to neurointensive care variables and clinical outcome.

BACKGROUND: The primary aim was to determine the association of intracranial hemorrhage lesion type, size, mass effect, and evolution with the clinical course during neurointensive care and long-term outcome after traumatic brain injury (TBI). METHODS: In this observational, retrospective study, 385 TBI patients treated at the neurointensive care unit at Uppsala University Hospital, Sweden, were included. The lesion type, size, mass effect, and evolution (progression on the follow-up CT) were assessed and analyzed in relation to the percentage of secondary insults with intracranial pressure > 20 mmHg, cerebral perfusion pressure < 60 mmHg, and cerebral pressure autoregulatory status (PRx) and in relation to Glasgow Outcome Scale-Extended. RESULTS: A larger epidural hematoma (p < 0.05) and acute subdural hematoma (p < 0.001) volume, greater midline shift (p < 0.001), and compressed basal cisterns (p < 0.001) correlated with craniotomy surgery. In multiple regressions, presence of traumatic subarachnoid hemorrhage (p < 0.001) and intracranial hemorrhage progression on the follow-up CT (p < 0.01) were associated with more intracranial pressure-insults above 20 mmHg. In similar regressions, obliterated basal cisterns (p < 0.001) were independently associated with higher PRx. In a multiple regression, greater acute subdural hematoma (p < 0.05) and contusion (p < 0.05) volume, presence of traumatic subarachnoid hemorrhage (p < 0.01), and obliterated basal cisterns (p < 0.01) were independently associated with a lower rate of favorable outcome. CONCLUSIONS: The intracranial lesion type, size, mass effect, and evolution were associated with the clinical course, cerebral pathophysiology, and outcome following TBI. Future efforts should integrate such granular data into more sophisticated machine learning models to aid the clinician to better anticipate emerging secondary insults and to predict clinical outcome.