在COVID-19患者中输管和死亡率的预测因素:一项回顾性研究
Tiziana Cena1, Gianmaria Cammarota2, Danila Azzolina3
1Anestesia e Terapia Intensiva, Azienda Ospedaliero Universitaria "Maggiore della Carità", Novara, Italy. titti.cena@gmail.com.
Journal of anesthesia, analgesia and critical care
|June 29, 2023
概括
这项研究确定了COVID-19患有低血量急性呼吸衰竭 (ARF) 患者输管和死亡的关键风险因素. 随机森林模型准确地预测了不良结果,有助于临床选和资源分配.
科学领域:
- 关键护理医学 关键护理医学
- 传染性疾病 传染性疾病
- 肺部病理学 肺部病理学
背景情况:
- 患有缺血性急性呼吸衰竭 (ARF) 的COVID-19患者需要对输管和死亡率进行有效的风险分层.
- 有效地分配重症监护资源需要准确预测患者病情的恶化.
研究的目的:
- 为了确定ARF的COVID-19患者的输管和医院内死亡的风险因素.
- 开发患者结果的预测模型.
主要方法:
- 对187名进入重症监护室的COVID-19患者进行了回顾性分析.
- 使用人口,临床,实验室和定量胸部CT数据开发两个随机森林 (RF) 模型.
- 确定输管和死亡率的独立预测因素.
主要成果:
- 与输管相关的变量包括C反应蛋白,乳酸脱酶和白细胞计数.
- 与死亡率相关的因素包括年龄,心血管疾病,C反应蛋白,乳酸脱酶和侵入性机械通风.
- 在CT扫描中,地面玻璃的不透明度,巩固和纤维化与输管治疗和死亡率有显著的关联.
结论:
- 证实了COVID-19 ARF患者不良结果的先前确定的人口,临床,血液化学和放射学预测因素.
- 开发的射频模型在预测输管和医院内死亡率方面表现出很好的准确性.
- 这些模型可以改善高风险患者的识别和资源管理.
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