Data Sheet 1_Blood–brain barrier vulnerability and microcirculatory dysfunction as predict

202 consecutive acute ischemic stroke patients undergoing endovascular treatment between 2021 and 2024 were analyzed in this retrospective study. The dataset likely contains clinical, laboratory, and CT perfusion-derived parameters to predict hemorrhagic transformation. It was authored by Yuchen Wang and published under a CC-BY-4.0 license.

Use Cases

• Predict hemorrhagic transformation risk based on blood-brain barrier vulnerability and microcirculatory dysfunction markers.
• Build a multimodal risk stratification model integrating collateral status, perfusion parameters, and serum globulin levels.
• Analyze the correlation between hemorrhagic transformation subtypes and patient functional outcomes.
• Validate clinical nomograms using ROC, calibration, and decision curve analysis techniques.

Strengths

• Includes data from 202 consecutive patients, providing a substantial clinical cohort.
• Integrates multiple data types: clinical variables, laboratory results, and CT perfusion imaging parameters.
• The derived prediction model demonstrated excellent discrimination with an AUC of 0.867.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is from a single retrospective study, which may reflect inherent temporal and institutional biases.

Provenance

Source

figshare

Collection Method

Retrospective study of patient records and imaging data.

Time Range

2021-2024

Freshness

Last updated 2026-04-20 05:22:44; freshness should be verified.

Geography

null