Chen Pengfei, Zhu Meilin, Guo Ming, Shi Dazhuo, Chen Zhuhong, Du Jianpeng
Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Cardiovascular Diseases Center, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Sci Rep. 2024 Dec 3;14(1):30082. doi: 10.1038/s41598-024-81637-y.
This study aims to investigate the association between the platelet-to-high-density lipoprotein cholesterol ratio (PHR) and diabetes/prediabetes in US adults. Data from the 2005-2018 National Health and Nutrition Examination Survey (NHANES) were analyzed in this study. The PHR was calculated by dividing platelet count by HDL-C concentration. Diabetes and prediabetes were classified according to established clinical criteria. Multivariate logistic regression analyses were employed to estimate odds ratios (ORs) and 95% CIs. We used a two-stage logistic regression model with restricted cubic splines (RCS) to evaluate potential non-linear relationships and to identify inflection points. The discriminative ability of the model was evaluated using receiver operating characteristic (ROC) curves, with the area under the curve (AUC) used to measure model performance. Sensitivity and specificity at the optimal threshold were also reported. Furthermore, subgroup and interaction analyses were conducted to determine variations across different population groups. The study included 20,229 eligible participants, with a mean age of 47.84 years, and 51.80% being female. Among the participants, 14.29% were diagnosed with diabetes, and 44.36% with prediabetes. A positive association was observed between PHR and diabetes/prediabetes. After adjusting for model 3, the OR for the combined outcome of diabetes and prediabetes associated with a per-unit increase in PHR was 1.17 (95% CI: 1.05-1.30). Participants in the highest PHR quartile had an OR of 2.55 (95% CI: 1.52-4.28) compared to those in the lowest quartile. Two-stage regression analysis identified a breakpoint at PHR = 4.55, with a positive association observed when PHR was below this value (OR = 1.33, 95% CI: 1.03-1.70). ROC analysis demonstrated good discriminatory ability of the model, with an AUC of 0.824 (95% CI: 0.803-0.845), sensitivity of 83.2%, and specificity of 66.5%. Stratified analyses revealed significant associations between PHR and diabetes/prediabetes across most demographic groups, with interactions observed for sex, alcohol consumption, and BMI, suggesting these factors may modify the association. This study suggests that an elevated PHR may be associated with a higher likelihood of diabetes and prediabetes. Consequently, PHR could serve as a valuable marker for estimating the association of diabetes and prediabetes development.
本研究旨在调查美国成年人中血小板与高密度脂蛋白胆固醇比值（PHR）与糖尿病/糖尿病前期之间的关联。本研究分析了2005 - 2018年国家健康和营养检查调查（NHANES）的数据。PHR通过血小板计数除以高密度脂蛋白胆固醇（HDL-C）浓度来计算。糖尿病和糖尿病前期根据既定的临床标准进行分类。采用多变量逻辑回归分析来估计比值比（OR）和95%置信区间（CI）。我们使用带有受限立方样条（RCS）的两阶段逻辑回归模型来评估潜在的非线性关系并确定拐点。使用受试者工作特征（ROC）曲线评估模型的判别能力，曲线下面积（AUC）用于衡量模型性能。还报告了最佳阈值下的敏感性和特异性。此外，进行了亚组和交互分析以确定不同人群组之间的差异。该研究纳入了20229名符合条件的参与者，平均年龄为47.84岁，女性占51.80%。在参与者中，14.29%被诊断患有糖尿病，44.36%患有糖尿病前期。观察到PHR与糖尿病/糖尿病前期之间存在正相关。在对模型3进行调整后，PHR每增加一个单位，糖尿病和糖尿病前期联合结局的OR为1.17（95% CI：1.05 - 1.30）。与最低四分位数的参与者相比，最高PHR四分位数的参与者的OR为2.55（95% CI：1.52 - 4.28）。两阶段回归分析确定在PHR = 4.55处有一个断点，当PHR低于此值时观察到正相关（OR = 1.33，95% CI：1.03 - 1.70）。ROC分析表明模型具有良好的判别能力，AUC为0.824（95% CI：0.803 - 0.845），敏感性为83.2%，特异性为66.5%。分层分析显示，在大多数人口统计学组中，PHR与糖尿病/糖尿病前期之间存在显著关联，在性别、饮酒和体重指数方面观察到交互作用，表明这些因素可能会改变这种关联。本研究表明，PHR升高可能与患糖尿病和糖尿病前期的可能性较高有关。因此，PHR可作为评估糖尿病和糖尿病前期发生关联的有价值标志物。
