使用机器学习技术预测移植后通过早期唾液微生物群的术后感染
Xuyu Xiang1,2, Hong Liu1,2, Tianyin Wang1,2
1The Transplantation Center of the Third Xiangya Hospital, Central South University, Changsha, China.
Renal failure
|July 3, 2025
概括
唾液微生物组分析可以预测移植后的感染. 口腔细菌和淋巴细胞水平的变化提供了早期预警信号,改善了患者的结果并减少了医疗保健负担.
科学领域:
- 微生物学 微生物学
- 免疫学 免疫学 免疫学
- 移植科学 移植科学
背景情况:
- 移植 (KT) 对末期病至关重要,但免疫抑制会增加感染风险.
- 对于后KT感染的预测生物标志物对于临床管理和经济原因至关重要.
- 目前的监测依赖于周围血液淋巴细胞亚种群 (PBLS) 计数,这些计数有局限性.
研究的目的:
- 研究唾液微生物群作为移植后感染的预测生物标志物.
- 将唾液微生物群的预测性能与PBLS计数进行比较.
主要方法:
- 16S rRNA测序了来自39名KT接受者的122个唾液样本.
- 分析唾液微生物群的组成和多样性.
- 使用随机森林和物流回归进行预测模型的开发,整合临床数据,PBLS和微生物组信息.
主要成果:
- 感染者和对照者之间唾液微生物群的显著差异.
- 唾液微生物群分析在预测感染方面表现优于PBLS计数 (AUC为85.97%对67.03%).
- 鉴定出Mogibacterium作为一个显著的预测因子,与淋巴细胞复合动态相关.
结论:
- 早期的唾液微生物群概况是1年内后KT感染的有效预测因素.
- 唾液微生物组分析为KT患者感染风险分层提供了一个有希望的,非侵入性的工具.
- 这种方法可以增强个性化的免疫抑制管理,并改善长期的移植结果.
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