Comparison between statistical and machine learning methods to detect the hematological indices with the greatest influence on elevated serum levels of low-density lipoprotein cholesterol

IF 3.4 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Somayeh Ghiasi Hafezi , Bahareh Behkamal , Mohammad Rashidmayvan , Marzieh Hosseini , Mehran Yadegari , Sahar Ghoflchi , Amin Mansoori , Mark Ghamsary , Gordon Ferns , Mohammad Reza Saberi , Habibollah Esmaily , Majid Ghayour-Mobarhan
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Abstract

Introduction

Elevated levels of low-density lipoprotein-cholesterol (LDL-C) is a significant risk factor for the development of cardiovascular diseases (CVD)s. Furthermore, studies have revealed an association between indices of the complete blood count (CBC) and dyslipidemia. We aimed to investigate the relationship between CBC parameters and serum levels of LDL.

Method

In a prospective study involving 9704 participants aged 35–65 years, comprehensive screening was conducted to estimate LDL-C levels and CBC indicators. The association between these biomarkers and high LDL-C (LDL-C≥130 mg/dL (3.25 mmol/L)) was investigated using various analytical methods, including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) methodologies.

Result

The present study found that age, hemoglobin (HGB), hematocrit (HCT), platelet count (PLT), lymphocyte (LYM), PLT-LYM ratio (PLR), PLT-High-Density Lipoprotein (HDL) ratio (PHR), HGB-LYM ratio (HLR), red blood cell count (RBC), Neutrophil-HDL ratio (NHR), and PLT-RBC ratio (PRR) were all statistically significant between the two groups (p<0.05). Another important finding was that red cell distribution width (RDW) was a significant predictor for higher LDL levels in women. Furthermore, in men, RDW-PLT ratio (RPR) and PHR were the most important indicators for assessing the elevated LDL levels.

Conclusion

The study found that sex increases LDL-C odds in females by 52.9 %, while age and HCT increase it by 4.1 % and 5.5 %, respectively. RPR and PHR were the most influential variables for both genders. Elevated RPR and PHR were negatively correlated with increased LDL levels in men, and RDW levels was a statistically significant factor for women. Moreover, RDW was a significant factor in women for high levels of HDL-C.
The study revealed that females have higher LDL-C levels (16 % compared to 14 % of males), with significant differences across variables like age, HGB, HCT, PLT, RLR, PHR, RBC, LYM, NHR, RPR, and key factors like RDW and SII.
比较统计方法和机器学习方法,以检测对低密度脂蛋白胆固醇血清水平升高影响最大的血液学指标。
导言:低密度脂蛋白胆固醇(LDL-C)水平升高是心血管疾病(CVD)发病的重要风险因素。此外,研究还发现全血细胞计数(CBC)指标与血脂异常之间存在关联。我们旨在研究全血细胞计数参数与血清低密度脂蛋白水平之间的关系:在一项涉及 9704 名 35 至 65 岁参与者的前瞻性研究中,我们进行了全面筛查,以估算低密度脂蛋白胆固醇水平和全血细胞计数指标。采用多种分析方法,包括逻辑回归(LR)、决策树(DT)、随机森林(RF)、神经网络(NN)和支持向量机(SVM)方法,研究了这些生物标志物与高 LDL-C(LDL-C≥130mg/dL (3.25mmol/L))之间的关联:本研究发现,年龄、血红蛋白 (HGB)、血细胞比容 (HCT)、血小板计数 (PLT)、淋巴细胞 (LYM)、PLT-LYM 比值 (PLR)、PLT-高密度脂蛋白 (HDL) 比值 (PHR)、HGB-LYM 比值 (HLR)、红细胞计数 (RBC)、中性粒细胞-HDL 比值 (NHR) 和 PLT-RBC 比值 (PRR) 在两组间均有统计学意义(p 结论:本研究发现,性别会增加低密度脂蛋白血症的发病率:研究发现,性别会使女性的低密度脂蛋白胆固醇几率增加 52.9%,而年龄和 HCT 则分别增加 4.1% 和 5.5%。RPR和PHR是对男女影响最大的变量。男性的 RPR 和 PHR 升高与低密度脂蛋白水平升高呈负相关,而 RDW 水平对女性来说是一个具有统计学意义的因素。此外,RDW 是女性高密度脂蛋白胆固醇水平的一个重要因素。研究显示,女性的低密度脂蛋白胆固醇水平较高(16%,而男性为 14%),在年龄、HGB、HCT、PLT、RLR、PHR、RBC、LYM、NHR、RPR 等变量以及 RDW 和 SII 等关键因素之间存在显著差异。
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来源期刊
Chemistry and Physics of Lipids
Chemistry and Physics of Lipids 生物-生化与分子生物学
CiteScore
7.60
自引率
2.90%
发文量
50
审稿时长
40 days
期刊介绍: Chemistry and Physics of Lipids publishes research papers and review articles on chemical and physical aspects of lipids with primary emphasis on the relationship of these properties to biological functions and to biomedical applications. Accordingly, the journal covers: advances in synthetic and analytical lipid methodology; mass-spectrometry of lipids; chemical and physical characterisation of isolated structures; thermodynamics, phase behaviour, topology and dynamics of lipid assemblies; physicochemical studies into lipid-lipid and lipid-protein interactions in lipoproteins and in natural and model membranes; movement of lipids within, across and between membranes; intracellular lipid transfer; structure-function relationships and the nature of lipid-derived second messengers; chemical, physical and functional alterations of lipids induced by free radicals; enzymatic and non-enzymatic mechanisms of lipid peroxidation in cells, tissues, biofluids; oxidative lipidomics; and the role of lipids in the regulation of membrane-dependent biological processes.
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