Impact of dynamic blood glucose trajectories on mortality in critically ill non-traumatic intracranial hemorrhage patients: a retrospective cohort study.

Authors

Mingkun Yang, Yanwen Lu, Yijing Liu, Yifeng Chen, Xindian Pan, Xiaofeng Zhang, Weihang Hu, Jing Yan

Published in

BMC neurology. Volume 26. Issue 1. Sep 07, 2026. Epub Sep 07, 2026.

Abstract

Dysglycemia is frequently observed in patients with non-traumatic intracranial hemorrhage (ICH) and has been linked to adverse clinical outcomes. However, the prognostic impact of longitudinal blood glucose trajectories in critically ill non-traumatic intracranial hemorrhage remains incompletely understood.
We conducted a retrospective cohort study using the MIMIC-IV database (United States, 2008-2019), including 2,260 critically ill non-traumatic ICH patients. Latent class mixed modeling (LCMM) was employed to identify distinct longitudinal blood glucose trajectory subtypes, utilizing blood glucose data collected during the initial 72 h of ICU admission. Associations between trajectory groups and mortality were assessed using multivariable Cox proportional hazards regression.
Four glucose trajectories were identified: Trajectory 1 (persistent low), Trajectory 2 (moderate stable), Trajectory 3 (progressive decline), and Trajectory 4 (progressive increase). Significant differences in baseline characteristics were observed across trajectories. Even after adjusting for baseline blood glucose and other potential confounders, the 28-day mortality risk remained significantly elevated in Trajectories 2-4 compared to Trajectory 1, with hazard ratios of 1.71 (95% CI: 1.33-2.20), 1.87 (95% CI: 1.25-2.80), and 2.41 (95% CI: 1.64-3.54), respectively. Consistent findings were observed for 180-day and 1-year mortality.
Four distinct blood glucose trajectories observed during the first 72 h of ICU admission among critically ill patients with non-traumatic ICH were independently associated with 28-day and longer-term mortality. These findings may support early risk stratification and inform future prospective studies.

PMID:
42733111
Bibliographic data and abstract were imported from PubMed on 14 Sep 2026.

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