Intracranial pressure trajectories and functional outcomes in pediatric intracranial hemorrhage: a group-based trajectory modeling analysis
摘要
Monitoring the dynamic changes in intracranial pressure (ICP) is crucial for assessing clinical outcomes in pediatric intracranial hemorrhage (ICH). However, the ICP trajectory patterns remain unknown. We aim to identify distinct ICP trajectory patterns in pediatric ICH and assess their impact on clinical outcomes. Pediatric ICH population were enrolled in Jiangsu Pediatric Medical Center. We utilized group-based trajectory modeling (GBTM) to identify distinct hourly ICP trajectories from the initiation of ICP monitoring up to the fourth day. The ΔICP was calculated to capture short-term fluctuations in ICP. Both the ICP trajectory patterns and ΔICP values were analyzed to assess ICP dynamics. Clinical characteristics were compared across the identified trajectory groups to explore potential differences. Multivariable logistic regression analyses were performed to investigate their associations with six-month functional outcomes, with adjustment for potential confounders. A total of 201 eligible patients were included in the study. GBTM identified five distinct ICP trajectories, which differed significantly in terms of mechanical ventilation, vasoactive agent use, pupil reactivity, craniectomy, initial, maximum, and median ICP, as well as ΔICP variability, Glasgow Coma Scale (GCS), and six-month Pediatric Glasgow Outcome Scale-Extended (pGOSE) scores. Compared with the “Low-Stable” group, patients in the “High-Fluctuating” and “Mid-Range Stable with Variability” groups had significantly higher odds of poor six-month outcomes (OR 24.28, 95% CI 2.91–202.90; OR 9.02, 95% CI 1.76–46.35, respectively).
Conclusions: This study reveals substantial heterogeneity in ICP trajectories among children with ICH and identifies three patterns associated with poor neurologic outcomes. Characterizing dynamic ICP trajectory subtypes may assist in early risk stratification and provide insight into ICP regulation patterns.