Table 1_Risk factors and development of a prediction model for hematoma expansion in elder

194 elderly patients with spontaneous intracerebral hemorrhage were analyzed to identify predictors of hematoma expansion. The study, authored by Xian-Xing Yu and posted in 2026, developed a model with an optimism-corrected AUC of 0.891. Independent risk factors included age, NIHSS score, neutrophil count, INR, baseline hematoma volume, black hole sign, and irregular shape.

Use Cases

• Developing a risk stratification tool based on clinical, laboratory, and imaging variables.
• Training a binary classification model to predict hematoma expansion based on patient age and NIHSS score.
• Analyzing the association between inflammatory markers like neutrophil count and neurological deterioration.
• Validating imaging biomarkers such as the black hole sign and irregular hematoma shape for prognosis.

Strengths

• Model performance is quantified with an optimism-corrected AUC of 0.891 from 1000 bootstrap resamples.
• The dataset includes 194 patient records with 56 observed hematoma expansion events, providing a clear outcome variable.
• Analysis identifies seven independent predictors with specific adjusted odds ratios and confidence intervals.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 18.1 KB, indicating limited scope.

Provenance

Source

figshare

Collection Method

Retrospective observational study of patients consecutively enrolled between May 2023 and May 2024.

Time Range

Patient admissions between May 2023 and May 2024.

Freshness

Last updated 2026-05-28 06:20:32; freshness should be verified.