在COVID-19患者中的COVID-19肺炎的预测规则:分类和回归树 (CART) 分析模型
Sayato Fukui1, Akihiro Inui1, Takayuki Komatsu2
1Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo, JPN.
这项研究确定了预测COVID-19患者复杂肺炎的关键因素. 通过C反应蛋白,年龄,LDH和血红蛋白水平识别的高风险个体应接受计算机断层扫描 (CT) 扫描.
科学领域:
- 医学成像和诊断 医学成像和诊断
- 传染性疾病 传染性疾病
- 肺部病理学 肺部病理学
背景情况:
- 冠状病毒疾病2019 (COVID-19) 可能导致复杂的肺炎.
- 识别需要计算机断层扫描 (CT) 的患者对于有效管理至关重要.
- 严重的COVID-19肺炎的预测因素尚未完全确定.
研究的目的:
- 为了确定COVID-19患者复杂肺炎的预测因素.
- 用分类和回归树 (CART) 分析确定在COVID-19患者中执行CT扫描的标准.
主要方法:
- 一个大学医院的回顾性横截面研究.
- 分析了2020年诊断的221名COVID-19患者的临床数据.
- 分类和回归树 (CART) 分析以确定肺炎预测因素.
主要成果:
- 在221名患者中,有160名 (72.4%) 患有肺炎.
- 根据C-反应蛋白 (CRP),年龄,乳酸脱酶 (LDH) 和血红蛋白水平,CART分析确定了高风险组.
- 预测模型证明了足够的解释能力,ROC曲线面积为0.860.0.
结论:
- 开发的模型有助于决定是否对COVID-19患者进行CT扫描.
- 通过特定的临床和实验室标志物识别的高风险COVID-19患者,需要进行CT成像.
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