Min Feng, Fanxing Meng, Yuhan Jia, Yanlin Wang, Guozhen Ji, Chong Gao, Jing Luo
{"title":"类风湿关节炎患者心血管疾病风险因素探究:一项回顾性研究","authors":"Min Feng, Fanxing Meng, Yuhan Jia, Yanlin Wang, Guozhen Ji, Chong Gao, Jing Luo","doi":"10.1007/s10753-024-02157-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Patients with rheumatoid arthritis (RA) have increased mortality and morbidity rates owing to cardiovascular diseases (CVD). Timely detection of CVD in RA can greatly improve patient prognosis; however, this technique remains challenging. We aimed to investigate the risk factors for CVD incidence in patients with RA.</p><p><strong>Methods: </strong>This retrospective study included RA patients without CVD risk factors (n = 402), RA with CVD risk factors (n = 394), and RA with CVD (n = 201). Their data on routine examination indicators, vascular endothelial growth factor (VEGF), and immune cells were obtained from medical records. The characteristic variables between each group were screened using univariate analysis, least absolute shrinkage and selection operator (LASSO), random forest (RF), and logistic regression (LR) models, and individualized nomograms were further established to more conveniently observe the likelihood of CVD in RA.</p><p><strong>Results: </strong>Univariate analysis revealed significantly elevated levels of white blood cells (WBC), blood urea nitrogen (BUN), creatinine, creatine kinase (CK), lactate dehydrogenase (LDH), VEGF, serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), apolipoprotein B100 (ApoB100), and apolipoprotein E (ApoE) in RA patients with CVD, whereas apolipoprotein A1 (ApoA1) and high-density lipoprotein/cholesterol (HDL/TC) were decreased. Furthermore, the ratio of regulatory T (Treg) cells exhibiting excellent separation performance in RA patients with CVD was significantly lower than that in other groups, whereas the ratios of Th1/Th2/NK and Treg cells were significantly elevated. The LASSO, RF, and LR models were also used to identify the risk factors for CVD in patients with RA. Through the final selected indicators screened using the three machine learning models and univariate analysis, a convenient nomogram was established to observe the likelihood of CVD in patients with RA.</p><p><strong>Conclusions: </strong>Serum lipids, lipoproteins, and reduction of Treg cells have been identified as risk factors for CVD in patients with RA. Three nomograms combining various risk factors were constructed to predict CVD occurring in patients with RA (RA with/without CVD risk factors).</p>","PeriodicalId":13524,"journal":{"name":"Inflammation","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploration of Risk Factors for Cardiovascular Disease in Patients with Rheumatoid Arthritis: A Retrospective Study.\",\"authors\":\"Min Feng, Fanxing Meng, Yuhan Jia, Yanlin Wang, Guozhen Ji, Chong Gao, Jing Luo\",\"doi\":\"10.1007/s10753-024-02157-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Patients with rheumatoid arthritis (RA) have increased mortality and morbidity rates owing to cardiovascular diseases (CVD). Timely detection of CVD in RA can greatly improve patient prognosis; however, this technique remains challenging. We aimed to investigate the risk factors for CVD incidence in patients with RA.</p><p><strong>Methods: </strong>This retrospective study included RA patients without CVD risk factors (n = 402), RA with CVD risk factors (n = 394), and RA with CVD (n = 201). Their data on routine examination indicators, vascular endothelial growth factor (VEGF), and immune cells were obtained from medical records. The characteristic variables between each group were screened using univariate analysis, least absolute shrinkage and selection operator (LASSO), random forest (RF), and logistic regression (LR) models, and individualized nomograms were further established to more conveniently observe the likelihood of CVD in RA.</p><p><strong>Results: </strong>Univariate analysis revealed significantly elevated levels of white blood cells (WBC), blood urea nitrogen (BUN), creatinine, creatine kinase (CK), lactate dehydrogenase (LDH), VEGF, serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), apolipoprotein B100 (ApoB100), and apolipoprotein E (ApoE) in RA patients with CVD, whereas apolipoprotein A1 (ApoA1) and high-density lipoprotein/cholesterol (HDL/TC) were decreased. Furthermore, the ratio of regulatory T (Treg) cells exhibiting excellent separation performance in RA patients with CVD was significantly lower than that in other groups, whereas the ratios of Th1/Th2/NK and Treg cells were significantly elevated. The LASSO, RF, and LR models were also used to identify the risk factors for CVD in patients with RA. Through the final selected indicators screened using the three machine learning models and univariate analysis, a convenient nomogram was established to observe the likelihood of CVD in patients with RA.</p><p><strong>Conclusions: </strong>Serum lipids, lipoproteins, and reduction of Treg cells have been identified as risk factors for CVD in patients with RA. Three nomograms combining various risk factors were constructed to predict CVD occurring in patients with RA (RA with/without CVD risk factors).</p>\",\"PeriodicalId\":13524,\"journal\":{\"name\":\"Inflammation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Inflammation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10753-024-02157-5\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Inflammation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10753-024-02157-5","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
目的:类风湿性关节炎(RA)患者因心血管疾病(CVD)导致的死亡率和发病率增加。及时发现类风湿关节炎患者的心血管疾病可大大改善患者的预后;然而,这项技术仍具有挑战性。我们旨在研究 RA 患者心血管疾病发病率的风险因素:这项回顾性研究包括无心血管疾病危险因素的 RA 患者(402 人)、有心血管疾病危险因素的 RA 患者(394 人)和有心血管疾病的 RA 患者(201 人)。他们的常规检查指标、血管内皮生长因子(VEGF)和免疫细胞数据均来自病历。采用单变量分析、最小绝对收缩和选择算子(LASSO)、随机森林(RF)和逻辑回归(LR)模型筛选各组间的特征变量,并进一步建立个体化提名图,以更方便地观察RA患者发生心血管疾病的可能性:在患有心血管疾病的 RA 患者中,血清总胆固醇(TC)、甘油三酯(TG)、低密度脂蛋白(LDL)、载脂蛋白 B100(ApoB100)和载脂蛋白 E(ApoE)均有所下降,而载脂蛋白 A1(ApoA1)和高密度脂蛋白/胆固醇(HDL/TC)则有所下降。此外,患有心血管疾病的 RA 患者中具有良好分离性能的调节性 T(Treg)细胞比例明显低于其他组别,而 Th1/Th2/NK 和 Treg 细胞的比例则明显升高。LASSO、RF和LR模型也被用于识别RA患者心血管疾病的危险因素。通过使用三种机器学习模型和单变量分析筛选出的最终选定指标,建立了一个方便的提名图,用于观察RA患者发生心血管疾病的可能性:结论:血清脂质、脂蛋白和Treg细胞的减少已被确定为RA患者心血管疾病的风险因素。结论:血清脂质、脂蛋白和 Treg 细胞减少已被确定为 RA 患者心血管疾病的风险因素,结合各种风险因素构建了三个提名图,以预测 RA 患者(有/无心血管疾病风险因素的 RA 患者)发生心血管疾病的可能性。
Exploration of Risk Factors for Cardiovascular Disease in Patients with Rheumatoid Arthritis: A Retrospective Study.
Objective: Patients with rheumatoid arthritis (RA) have increased mortality and morbidity rates owing to cardiovascular diseases (CVD). Timely detection of CVD in RA can greatly improve patient prognosis; however, this technique remains challenging. We aimed to investigate the risk factors for CVD incidence in patients with RA.
Methods: This retrospective study included RA patients without CVD risk factors (n = 402), RA with CVD risk factors (n = 394), and RA with CVD (n = 201). Their data on routine examination indicators, vascular endothelial growth factor (VEGF), and immune cells were obtained from medical records. The characteristic variables between each group were screened using univariate analysis, least absolute shrinkage and selection operator (LASSO), random forest (RF), and logistic regression (LR) models, and individualized nomograms were further established to more conveniently observe the likelihood of CVD in RA.
Results: Univariate analysis revealed significantly elevated levels of white blood cells (WBC), blood urea nitrogen (BUN), creatinine, creatine kinase (CK), lactate dehydrogenase (LDH), VEGF, serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), apolipoprotein B100 (ApoB100), and apolipoprotein E (ApoE) in RA patients with CVD, whereas apolipoprotein A1 (ApoA1) and high-density lipoprotein/cholesterol (HDL/TC) were decreased. Furthermore, the ratio of regulatory T (Treg) cells exhibiting excellent separation performance in RA patients with CVD was significantly lower than that in other groups, whereas the ratios of Th1/Th2/NK and Treg cells were significantly elevated. The LASSO, RF, and LR models were also used to identify the risk factors for CVD in patients with RA. Through the final selected indicators screened using the three machine learning models and univariate analysis, a convenient nomogram was established to observe the likelihood of CVD in patients with RA.
Conclusions: Serum lipids, lipoproteins, and reduction of Treg cells have been identified as risk factors for CVD in patients with RA. Three nomograms combining various risk factors were constructed to predict CVD occurring in patients with RA (RA with/without CVD risk factors).
期刊介绍:
Inflammation publishes the latest international advances in experimental and clinical research on the physiology, biochemistry, cell biology, and pharmacology of inflammation. Contributions include full-length scientific reports, short definitive articles, and papers from meetings and symposia proceedings. The journal''s coverage includes acute and chronic inflammation; mediators of inflammation; mechanisms of tissue injury and cytotoxicity; pharmacology of inflammation; and clinical studies of inflammation and its modification.