Scholarlink

Background <p>Spontaneous intracerebral hemorrhage (sICH) is a devastating form of stroke with high mortality and disability rates. Hematoma expansion (HE) occurs in over 30% of sICH patients and serves as a critical predictor of poor outcomes. This review aims to synthesize current evidence on clinical factors predicting HE in sICH patients.</p> Methods <p>We conducted a comprehensive literature search of major databases from inception to December 2024. Included studies examined clinical, radiological, and biochemical factors associated with HE in sICH.</p> Results <p>Multiple factors demonstrate predictive value for HE, including hematoma volume, irregular shape, ultra-early growth rate, coagulation status, blood pressure parameters, and specific imaging markers. Emerging technologies including advanced MRI and biomarker assays show promise for improved prediction. Multimodal prediction models incorporating clinical and imaging data demonstrate superior predictive accuracy compared to single parameters.</p> Conclusion <p>Early identification of HE risks factors enables targeted intervention and may improve clinical outcomes. Future research should focus on validating multimodal prediction tools and developing targeted therapies for high-risk patients.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Advancements in predicting clinical factors for hematoma enlargement in primary cerebral hemorrhage patients: a review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月28日

查看全文
  • Fa Wu,
  • Yulin Yang,
  • Tingting Wu,
  • Rui Jiang,
  • Jie Wu,
  • Jinping Sheng,
  • Hongmei Yu,
  • Jialin Wu,
  • Peng Wang

摘要

Background

Spontaneous intracerebral hemorrhage (sICH) is a devastating form of stroke with high mortality and disability rates. Hematoma expansion (HE) occurs in over 30% of sICH patients and serves as a critical predictor of poor outcomes. This review aims to synthesize current evidence on clinical factors predicting HE in sICH patients.

Methods

We conducted a comprehensive literature search of major databases from inception to December 2024. Included studies examined clinical, radiological, and biochemical factors associated with HE in sICH.

Results

Multiple factors demonstrate predictive value for HE, including hematoma volume, irregular shape, ultra-early growth rate, coagulation status, blood pressure parameters, and specific imaging markers. Emerging technologies including advanced MRI and biomarker assays show promise for improved prediction. Multimodal prediction models incorporating clinical and imaging data demonstrate superior predictive accuracy compared to single parameters.

Conclusion

Early identification of HE risks factors enables targeted intervention and may improve clinical outcomes. Future research should focus on validating multimodal prediction tools and developing targeted therapies for high-risk patients.