ArticleNeurocritical care2021
Early Determinants of Neurocritical Care Unit Length of Stay in Patients with Spontaneous Intracerebral Hemorrhage.
Article in Neurocritical care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Cerebrospinal Fluid Hemopexin as a Candidate Biomarker for Secondary Sepsis and In-Hospital Outcome After Spontaneous Intracerebral Hemorrhage: An Exploratory Translational Proteomics Study.Neurocritical care · 2026Article
- Early Postoperative Inflammatory Indices Predict Long-Term Neuro-ICU Stay in Patients Requiring Prolonged Care After Supratentorial Brain Tumor Resection: Development and Validation of an Integrated Model.CNS neuroscience & therapeutics · 2026Article
- Modeling the Predictive Performance of the ICH Score: Stepwise Selection and Logistic Modeling of Mortality, Functional Outcomes, Placement Destination, and Length of Stay.Neurosurgery practice · 2026Article
- Early gastrostomy is associated with more efficient healthcare resource utilization in nontraumatic intracerebral hemorrhage patients.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2026Article
- Predictors and outcomes associated with prolonged hospital length of stay in intracerebral hemorrhage: a multicenter prospective cohort study in China.BMC medicine · 2025Article
- Medical complications associated with prolonged length of stay in patients with nontraumatic intracerebral hemorrhage: A nationwide cohort study.Clinical neurology and neurosurgery · 2025Article
- Development of an emergency department length-of-stay prediction model based on machine learning.World journal of emergency medicine · 2025Article
- The Incidence of Takotsubo Cardiomyopathy in Patients with Intracerebral Hemorrhage: A US Nationwide Study.Neurocritical care · 2023Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe present study considers patients with spontaneous intracerebral hemorrhage (ICH) admitted to the neurocritical care unit (NCCU) through the Emergency Department (ED). It aims to identify patient-specific clinical variables that can be assessed on presentation and that are associated with prolonged NCCU length of stay (LOS).
methodsA cross-sectional, single-center, retrospective analysis of ICH patients directly admitted from the ED to the NCCU over an 8-year period was performed. Patients' demographics, clinical exam characteristics, serum laboratory values, intubation status, and neurosurgical procedures at presentation were recorded. Head computed tomography scans obtained on presentation were reviewed. LOS was calculated based on the number of midnights spent in the NCCU. Prolonged LOS was determined using a change point analysis, adopting the method of Taylor which utilizes CUMSUM charts and bootstrap analysis. A decision tree model was trained and validated to identify reliable variables associated with prolonged LOS.
resultsTwo hundred and five patients with ICH were analyzed. Prolonged LOS was calculated to be a stay that exceeds 8 days; 68 patients (33%) had a prolonged LOS in NCCU. Median LOS did not differ between survivors and patients who died in hospital. Clinical variables explored through the decision tree model were intubation status, neurosurgical intervention (EVD, decompression or evacuation within 24 h from presentation), and components of the ICH score: age, GCS, hematoma volume, the presence of intraventricular hemorrhage (IVH), and infratentorial location. The model accuracy was 0.8 and AUC was 0.83 (95% CI 0.78-0.89).
conclusionWe propose an ICH-LOS model based on neurosurgical intervention, intubation status and GCS at presentation to predict prolonged LOS in the NCCU in patients with ICH. This simple clinical tool, if prospectively validated, could help with medical planning, contribute to patient care-directed conversations, assist in optimizing hospital resource utilization, and, more importantly, motivating patient-specific interventions aimed at optimizing outcomes and decreasing LOS.
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