尿酸与2型糖尿病有关:数据挖掘方法
Amin Mansoori1,2, Davoud Tanbakuchi1, Zahra Fallahi3
1Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
数据挖掘模型确定了2型糖尿病 (T2D) 风险的关键预测因素. 血压高和血脂不良史,尿酸和甘油三水平是显著的指标.
科学领域:
- 生物医学研究的研究.
- 在医疗保健中的数据科学.
- 流行病学 流行病学
背景情况:
- 2型糖尿病 (T2D) 的风险与各种血液生物标志物有关.
- 这些生物标志物的预测价值往往缺乏通过数据挖掘进行评估.
研究的目的:
- 使用数据挖掘算法开发T2D的预测模型.
- 评估血液生物标志物和T2D风险临床因素的预测价值.
主要方法:
- 来自MASHAD研究 (2010-2020) 的9704名参与者 (35-65岁) 的队列研究.
- 评估了血清生物化学因素,脂质概况,BMI,WC,血压和年龄.
- 使用后勤回归 (LR) 和决策树 (DT) 用于T2D预测建模.
主要成果:
- 患有糖尿病的参与者表现出较高的甘油三,LDL,胆固醇,ALT,直接胆红素和尿酸水平 (p<0.05).
- LR模型发现TG,尿酸,hs-CRP,年龄,性别,WC,血压,以及T2D显著的高血压/脂质失调病史.
- DT算法将失脂症史确定为最强的预测因素,其次是年龄,高血压史,尿酸和TG.
结论:
- 在高血压/失脂症史,TG,尿酸,hs-CRP,年龄,WC和血压与T2D发展之间存在显著的关联.
- LR和DT方法有效地确定了T2D风险的关键预测因素.
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