使用数据挖掘方法来探索2型糖尿病与SARS-CoV-2之间的关联
Hamideh Ghazizadeh1,2, Neda Shakour3, Sahar Ghoflchi2
1The Hospital for Sick Children, CALIPER Program, Division of Clinical Biochemistry, Pediatric Laboratory Medicine, Toronto, ON, Canada.
BMC pulmonary medicine
|June 12, 2023
概括
2型糖尿病 (T2DM) 和特定的生物化学和血液学因素,如肌酸化酶 (CPK),血尿素 (BUN) 和平均血小板体积 (MPV) 与COVID-19感染风险有显著关联. 这些发现突出了T2DM.
科学领域:
- 传染性疾病 传染性疾病
- 内分泌学 在内分泌学.
- 生物化学 生物化学
- 血液学 血液学 血液学
背景情况:
- 严重急性呼吸系统综合征冠状病毒2 (SARS-CoV-2) 在2019年底出现,导致广泛的呼吸系统疾病.
- 了解风险因素和疾病关联对于管理COVID-19大流行至关重要.
- 2型糖尿病 (T2DM) 是一种普遍的代谢障碍,对传染病有潜在的影响.
研究的目的:
- 为了调查2型糖尿病 (T2DM) 和COVID-19感染之间的关系.
- 在T2DM患者中确定与COVID-19严重程度相关的生物化学和血液学因素.
- 改进糖尿病人群中COVID-19的治疗和管理策略.
主要方法:
- 这是一项大型队列研究,涉及13,170名35-65岁的参与者 (5,780名COVID-19阳性,7,390名阴性).
- 生物化学因素 (例如,肌酸酶,血液尿素) 和血液学因素 (例如,平均血小板体积) 的分析.
- 应用数据挖掘技术,包括后勤回归 (LR) 和决策树 (DT) 算法,以评估与COVID-19感染的关联,调整混因素.
主要成果:
- 后勤回归确定了肌酸素酶 (CPK),血尿素 (BUN) 和平均血小板体积 (MPV) 作为与COVID-19感染相关的显著生物化学和血液学因素.
- 决策树分析证实CPK,BUN和MPV是关键的预测变量.
- 经过对混杂变量进行调整后,T2DM患者的COVID-19感染风险增加.
结论:
- 在COVID-19感染的背景下,CPK,BUN,MPV和T2DM之间存在显著的关联.
- T2DM似乎在COVID-19的发展和进展中发挥着关键作用.
- 这些发现强调了在流行病期间对糖尿病患者监测这些因素的重要性.
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