ArticleFrontiers in neurology
A nomogram model to predict cognitive impairment in patients with spontaneous intracerebral hemorrhage.
Article in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: Post-stroke cognitive impairment (PSCI) after spontaneous intracerebral hemorrhage (sICH) is highly prevalent and severely impacts patients' long-term quality of life. However, accurate prediction tools that integrate acute-phase complications with sociodemographic characteristics are currently lacking. This study aimed to identify independent risk factors for PSCI in sICH patients and to construct a visual nomogram prediction model to guide clinical risk stratification prior to hospital discharge. Methods: We retrospectively analyzed clinical data from 264 sICH patients admitted to the Affiliated Hospital of Xuzhou Medical University between July 2023 and July 2025. Patients were classified into cognitive impairment and cognitively normal groups based on the Montreal Cognitive Assessment (MoCA) score (<22). The dataset was randomly split into a training set ( Results: The overall incidence of PSCI in this cohort was 44.3%. Multivariate logistic regression analysis identified pulmonary infection (OR 3.980, 95% CI 2.075-7.635, Conclusion: This study successfully developed a nomogram prediction model incorporating pulmonary infection, hematoma volume, and years of education. The model suggests that cognitive decline after sICH is associated with a combination of systemic inflammation (brain-body axis interaction), primary structural injury, and insufficient cognitive reserve. This user-friendly and accurate scoring tool can assist clinicians in identification of high-risk subgroups for PSCI upon completion of inpatient care, thereby informing intensified clinical monitoring and rehabilitation planning.
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