对复发性Clostridioides difficile感染的临床风险工具的验证
Rachel H Boone1, Emmanuel Lee2, William A Petri1,3
1Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, VA, USA.
预测复发性Clostridioides difficile感染 (CDI) 仍然具有挑战性,因为经过验证的工具表现不佳. 需要新的生物标志物和先进模型来提高CDI复发的预测准确性.
科学领域:
- 传染性疾病 传染性疾病
- 临床流行病学临床流行病学
- 医疗信息学 医疗信息学
背景情况:
- 困难菌感染 (CDI) 造成了严重的医疗负担.
- 复发性CDI是常见的,并与增加的发病率和死亡率有关.
- 准确预测CDI复发对于及时干预至关重要.
研究的目的:
- 验证现有的工具来预测反复发生的CDI.
- 为了比较各种风险评分,指南和生物标志物的表现.
- 评估电子医疗记录在验证这些预测工具中的有用性.
主要方法:
- 对1519名患有CDI的住院成年患者进行了回顾性队列研究.
- 经过验证的多重复发风险得分,共识指南,ATLAS得分和PCR周期值.
- 使用接收器操作特征曲线 (AUROC) 下面的面积来比较工具性能.
主要成果:
- 所有经过验证的工具在预测复发性CDI方面表现不佳 (AUROC范围:0.488-0.564).
- 揭示者等人. 其他. 工具显示了最高的AUROC (0.523),但性能并不比其他方法更好.
- 预测准确性特别低,在患者有CDI病史.
结论:
- 目前的工具不足以可靠地预测反复发生的CDI.
- 需要新的生物标志物和更复杂的预测模型.
- 未来的研究应该专注于开发改进的策略来识别患有CDI复发高风险的患者.
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