免疫微环境相关标志物的预测模型在患有败血症伴随心肌功能障碍的患者中及其在诊断中的作用
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1Department of Intensive Care Unit, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.
Frontiers in cardiovascular medicine
|January 1, 2026
概括
这项研究确定了关键的免疫标记物和预测败血症诱导心肌功能障碍 (SIMD) 的临床因素. 使用这些因素的预测模型可以有效地识别高风险患者,以便进行早期干预.
科学领域:
- 心脏病学 心脏病学
- 免疫学 免疫学 免疫学
- 关键护理医学 关键护理医学
背景情况:
- 败血症引起的心肌功能障碍 (SIMD) 是败血症的严重并发症.
- 早期识别有SIMD风险的患者对于及时干预和改善结果至关重要.
研究的目的:
- 评估免疫微环境标记物来预测SIMD.
- 开发和比较名图,决策树和梯度增强机 (GBM) 模型的有效性,以评估SIMD风险.
主要方法:
- 对165名败血症患者的回顾性分析.
- 使用后勤回归对风险因素的选.
- 使用AUC.构建和评估名录图,决策树和GBM预测模型.
主要成果:
- 较高的APACHE II评分,NT-proBNP,sTREM-1和HMGB1水平被确定为SIMD的危险因素.
- 这三种模型 (nomogram,决策树,GBM) 均显示出优异的预测性能 (AUC从0.815到0.885不等).
结论:
- 免疫标志物sTREM-1和HMGB1,以及临床因素,与SIMD相关.
- 开发的预测模型有效地识别高风险个体,支持早期临床干预.
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