使用人工智能预测老年患者的COVID-19住院死亡率:一个多中心研究
Massimiliano Fedecostante1, Jacopo Sabbatinelli2,3, Giuseppina Dell'Aquila1
1Geriatria, Accettazione Geriatrica e Centro di ricerca per l'invecchiamento, IRCCS INRCA, Ancona, Italy.
Frontiers in aging
|November 1, 2024
概括
患有COVID-19的老年人具有显著的死亡风险. 预先存在的移动性和疾病严重程度是住院死亡的关键预测因素,突出了功能状态在预测结果中的重要性.
科学领域:
- 老年学是一门学科.
- 传染性疾病 传染性疾病
- 人工智能在医学中的应用
背景情况:
- 严重急性呼吸系统综合征冠状病毒2 (SARS-CoV-2) 已成为流行病,造成持续的临床风险,特别是对有多种健康问题和脆弱的老年人来说.
- 尽管疫情结束了,但COVID-19继续对老年人群产生重大影响.
研究的目的:
- 通过使用例行收集的入院数据,确定与老年COVID-19患者住院死亡率相关的关键特征.
- 开发一种预测模型,用于识别COVID-19死亡风险较高的老年患者.
主要方法:
- 一项多中心观察性研究 (Gerocovid-急性病房) 包括COVID-19大流行期间60岁以上的患者.
- 用机器学习平台 (Just Add Data Bio) 分析了71个常规收集的变量,以确定预后相关性.
- 人工智能被用来减轻偏见,测试众多模型,并执行内部验证.
主要成果:
- 使用12个关键变量开发了一个预测模型,通过三种不同的算法的融合确定了这些变量.
- 这些变量包括COVID-19前的移动性,世卫组织疾病严重程度,年龄,生命体征,血液气体,血清,血糖,肝酶和中性粒细胞与淋巴细胞的比例.
- 该模型通过内部验证证明了高预后准确性.
结论:
- 疾病前的流动性水平成为与住院死亡率相关的最重要因素,这突显了老年人功能状况.
- 中性粒细胞与淋巴细胞比率与死亡率的关联证实了中性粒细胞在SARS-CoV-2病变发生过程中的关键作用.
- 这些发现有助于分层风险和管理COVID-19的老年患者.
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