使用数据挖掘方案调查急性损伤 (AKI) 与COVID-19死亡率的关联
Ayoub Tavakolian1, Mahdieh Farhanji2, Farhang Shapouran3
1Emergency Medicine Department, Deputy of Treatment, Faculty of Medicine, Mashhad University of Medical Science, Mashed, Iran.
Diagnostic microbiology and infectious disease
|August 20, 2023
概括
急性损伤 (AKI) 影响了14.1%的COVID-19患者,是死亡率的重要预测因素. 这项研究强调AKI是COVID-19相关死亡的关键因素.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 数据科学数据科学数据科学
- 流行病学 流行病学
背景情况:
- 在脏研究和患者护理方面,COVID-19带来了巨大的挑战.
- 急性损伤 (AKI) 是严重感染的一种已知的并发症.
研究的目的:
- 为了调查COVID-19患者中AKI的发生率.
- 为了确定与COVID-19患者死亡率相关的风险因素.
- 评估COVID-19死亡率数据挖掘模型的预测性能.
主要方法:
- 采用了数据挖掘技术,包括后勤回归 (LR) 和决策树 (DT) 模型.
- 分析使用SPSS 25和Python 3进行.
- 评估了AKI,年龄,并发症和氧和等关键变量.
主要成果:
- AKI的发病率为14.1%,COVID-19患者的整体死亡风险为13%.
- 后勤回归确定了AKI,年龄,心力衰竭和SPO2水平作为显著的死亡率预测因素.
- 决策树模型显示,AKI是最重要的死亡率预测指标,其次是年龄和白细胞计数.
结论:
- 急性损伤 (AKI) 在COVID-19患者中很普遍,是导致死亡率的关键因素.
- 数据挖掘模型在识别COVID-19死亡率的关键预测因素方面具有实用性.
- 早期识别和管理AKI可能对改善COVID-19患者的治疗结果至关重要.
相关概念视频
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