高密度脂蛋白胆固醇相关炎症指数与慢性阻塞性肺病之间的关联:采用机器学习分析的横截面研究
Xingshi Hua1,2, Yu Gan3, Xiaodong Lv4
1Liaoning University of Traditional Chinese Medicine, Shenyang, China.
单细胞与HDL (MHR) 和中性粒细胞与HDL (NHR) 的比率与更高的慢性阻塞性肺病 (COPD) 风险有关. 这些炎症标志物显示出早期COPD检测和干预的潜力.
科学领域:
- 肺部医学 肺部医学
- 免疫学 免疫学 免疫学
- 生物统计学 生物统计学
背景情况:
- 慢性阻塞性肺病 (COPD) 是一种复杂的炎症和代谢障碍.
- 免疫细胞与高密度脂蛋白胆固醇 (HDL-C) 的比例是新兴的炎症标志物.
- 与HDL-C相关的炎症指数和COPD患病率之间的联系需要进一步调查.
研究的目的:
- 调查基于HDL-C的炎症指数与COPD患病率之间的关联.
- 探索这些指数在COPD中的潜在因果关系和预测价值.
- 开发COPD风险分层的预测模型.
主要方法:
- 对9,998名参与者的NHANES数据 (2007-2012) 的分析,其中有1,619人患有COPD.
- 对四种炎症指数的检查:淋巴细胞/高血压 (LHR),单细胞/高血压 (MHR),中性细胞/高血压 (NHR) 和血小板/高血压 (PHR).
- 机器学习,多变量逻辑回归,调解分析和门德尔随机化 (MR) 的应用.
主要成果:
- MHR和NHR与COPD的几率增加显著相关 (分别为28%和37%).
- 观察到一致的剂量反应关系,主要是直接的关联.
- 门德尔随机化表明中性粒细胞计数在COPD风险中的潜在因果作用;机器学习将MHR和NHR确定为关键预测因素.
结论:
- 单细胞与高血压 (MHR) 和中性粒细胞与高血压 (NHR) 的比率是COPD患病率的有希望的生物标志物.
- 来自多种分析方法的强有力的证据支持它们的临床实用性.
- 这些指数可以帮助COPD风险分层和早期干预策略.
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