通过使用血液参数的统计和机器学习方法,预测COVID-19患者住院时间概率
Kiomars Motarjem1, Mahin Behzadifard2, Shahin Ramazi3
1Department of Statistics, Faculty of Mathematical Sciences, Tarbiat Modares University.
Annals of medicine and surgery (2012)
|December 9, 2024
概括
预测COVID-19的结果是可以使用入院血液测试. 关键指标包括低,低,小红细胞,低单细胞,高血小板和50岁以上的年龄.
科学领域:
- 医学科学 医学科学 医学科学
- 临床医学 临床医学
- 血液学 血液学 血液学
背景情况:
- 冠状病毒疾病2019 (COVID-19) 可能导致严重的并发症和死亡.
- 早期识别患有严重后果高风险的患者对于及时干预至关重要.
研究的目的:
- 开发一个对COVID-19疾病结果的预测模型,特别是住院时间和死亡率.
- 在入院时确定关键的血液参数和与疾病严重程度相关的临床因素.
主要方法:
- 分析了201名确诊COVID-19感染的患者的数据.
- 考虑了包括年龄,性别,并发症,住院时间和入院时25个血液参数在内的变量.
- 利用加速失效时间模型,特别是日志-正常模型,进行分析.
主要成果:
- 几个因素显著影响住院时间和死亡率 (P<0.05).
- 这些包括低血症,低血症,红细胞微细胞症,单细胞缩,血栓细胞症,特定的并发症 (糖尿病,心血管疾病,高血压) 和50岁以上的年龄.
- 日志-正常加速失效时间模型证明最适合数据.
结论:
- 血栓细胞症,红细胞微细胞症,单细胞减小,低血症,低血症,并发症和50岁以上的年龄被提议作为COVID-19住院时间和死亡率的预测标志物.
- 这些入院时的实验室和临床因素可以帮助估计患者的预后.
- 这些发现强调了这些标记在预测严重的COVID-19结果方面的重要性.
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