Clinical, Laboratory, and CT Morphological Factors Associated with 3-Month Functional Outcomes in Spontaneous

Mustafa Harun Şahin1, Özhan Özcan2, Oğuzhan Kurşun3

  • 1Department of Neurology, Balikesir Ataturk City Hospital, 10100 Balikesir, Türkiye.

Brain Sciences
|July 28, 2026
PubMed

Insights

Predicting outcomes for spontaneous intracerebral hemorrhage (ICH) is crucial. This study found that neurological severity, hematoma volume, and CT scan findings like hypodensities predict poor functional outcomes.

Area of Science:

  • Neurology
  • Radiology
  • Biomedical Engineering

Background:

  • Spontaneous intracerebral hemorrhage (ICH) leads to significant mortality and disability.
  • Accurate prediction of functional outcomes is essential for patient management.

Purpose of the Study:

  • To identify independent clinical, laboratory, and imaging predictors of 3-month functional outcome in spontaneous ICH patients.
  • To evaluate the predictive performance of these factors compared to existing prognostic scores.

Main Methods:

  • Retrospective cohort study of 337 spontaneous ICH patients.
  • Analysis included clinical data, laboratory parameters, non-contrast CT (NCCT) morphological markers, hematoma volume, and prognostic scores (ICH, FUNC).
  • Firth penalized logistic regression was used to identify independent predictors of poor functional outcome (modified Rankin Scale 3-6 at 3 months).

Main Results:

  • Poor functional outcome was observed in 60.2% of patients; 3-month mortality was 36.8%.
  • Independent predictors of poor outcome included lower Glasgow Coma Scale, larger hematoma volume, NCCT hypodensities, hypertension history, and lower LDL cholesterol.
  • The developed model demonstrated good discrimination (AUC 0.872) and outperformed ICH and FUNC scores.

Conclusions:

  • Neurological severity, hematoma volume, NCCT hypodensities, and specific clinical/laboratory factors independently predict poor 3-month functional outcome in ICH.
  • Integrating clinical, volumetric, and CT morphological data improves prognostic discrimination.
  • Findings require prospective validation for clinical implementation.
Abstract

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