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Introduction <p>Intracerebral hemorrhage (ICH) is the most lethal subtype of stroke, accounting for approximately 20% of all stroke cases, and has a high early mortality rate, largely because effective acute treatments are limited compared with ischemic stroke. Identifying reliable predictors of hospital case-fatality is essential for risk stratification and treatment optimization.</p> Methods <p>This retrospective analytic observational hospital-based study (April 2024 to June 2025, Imam Reza Hospital) included 90 patients with ICH (40 deceased, 50 survivors). We analyzed demographic information, clinical and laboratory parameters, comorbidities, hemorrhage characteristics, and the modified Rankin Scale (mRS) as a measure of functional disability. The primary outcome was hospital case-fatality. All Glasgow Coma Scale (GCS) and mRS assessments were measured by a neurologist at two times (the first and last day of hospitalization).</p> Results <p>Multivariate analysis identified independent and significant predictors of hospital case-fatality: GCS less than 7 at admission (Odds Ratio (OR) = 5.21, 95% Confidence Interval (CI): 4.85–9.41), GCS less than 7 in the last day (OR = 5.96, 95% CI: 3.78–9.05), Hematoma volume &gt; 25 mL (OR = 14.20, 95% CI: 11.52–32.63), intraventricular hemorrhage (OR = 8.23, 95% CI: 5.63–9.96), deep location of hematoma (OR = 5.63, 95% CI: 4.49–8.75); mRS &gt; 3 at discharge (OR = 12.63, 95% CI: 8.41–18.30), mRS &gt; 3 at admission (OR = 8.11, 95% CI: 7.63–11.25), and hypertension (OR = 2.22, 95% CI: 1.41–4.02).</p> Conclusion <p>Hospital case-fatality in ICH patients is independently predicted by hematoma volume, intraventricular hemorrhage extension, deep hematoma location, impaired consciousness, high functional disability scores, and hypertension. Early and systematic assessment of these factors could improve prognostic accuracy and guide personalized clinical decision-making.</p>

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Predictive factors of hospital case-fatality in patients with spontaneous intracerebral haemorrhage

  • 期刊论文

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  • 发表日期：

    2026年8月3日

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  • Asghar Jafari Rouhi,
  • Zahra Khodabakhsh,
  • Haniyeh Ebrahimi Bakhtavar,
  • Elyar Sadeghi Hokmabadi,
  • Arezoo Nejabatian,
  • Farzad Rahmani

摘要

Introduction

Intracerebral hemorrhage (ICH) is the most lethal subtype of stroke, accounting for approximately 20% of all stroke cases, and has a high early mortality rate, largely because effective acute treatments are limited compared with ischemic stroke. Identifying reliable predictors of hospital case-fatality is essential for risk stratification and treatment optimization.

Methods

This retrospective analytic observational hospital-based study (April 2024 to June 2025, Imam Reza Hospital) included 90 patients with ICH (40 deceased, 50 survivors). We analyzed demographic information, clinical and laboratory parameters, comorbidities, hemorrhage characteristics, and the modified Rankin Scale (mRS) as a measure of functional disability. The primary outcome was hospital case-fatality. All Glasgow Coma Scale (GCS) and mRS assessments were measured by a neurologist at two times (the first and last day of hospitalization).

Results

Multivariate analysis identified independent and significant predictors of hospital case-fatality: GCS less than 7 at admission (Odds Ratio (OR) = 5.21, 95% Confidence Interval (CI): 4.85–9.41), GCS less than 7 in the last day (OR = 5.96, 95% CI: 3.78–9.05), Hematoma volume > 25 mL (OR = 14.20, 95% CI: 11.52–32.63), intraventricular hemorrhage (OR = 8.23, 95% CI: 5.63–9.96), deep location of hematoma (OR = 5.63, 95% CI: 4.49–8.75); mRS > 3 at discharge (OR = 12.63, 95% CI: 8.41–18.30), mRS > 3 at admission (OR = 8.11, 95% CI: 7.63–11.25), and hypertension (OR = 2.22, 95% CI: 1.41–4.02).

Conclusion

Hospital case-fatality in ICH patients is independently predicted by hematoma volume, intraventricular hemorrhage extension, deep hematoma location, impaired consciousness, high functional disability scores, and hypertension. Early and systematic assessment of these factors could improve prognostic accuracy and guide personalized clinical decision-making.