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Factors Associated With Hyperuricemia in Patients With Coronary Heart Disease
Qinyu Sun1,2, Yifan Deng1,2, Zhiyuan Gao3
1Department of Cardiology, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, 225001 Yangzhou, Jiangsu, China.
Insights
Novel biomarkers, monocyte-to-high-density lipoprotein cholesterol ratio (MHR) and remnant cholesterol (RC), are linked to hyperuricemia (HUA) in new-onset coronary heart disease (CHD). These findings aid in clinical risk assessment and management of HUA in CHD patients.
Area of Science:
- Cardiology
- Biochemistry
- Internal Medicine
Background:
- Hyperuricemia (HUA) is increasingly recognized as a significant clinical factor in patients diagnosed with coronary heart disease (CHD).
- Understanding the clinical factors and novel biomarkers associated with HUA in newly diagnosed CHD is crucial for effective risk stratification and management.
- This study investigates the relationship between HUA and various clinical parameters, including novel biomarkers, in a cohort of newly diagnosed CHD patients.
Purpose of the Study:
- To identify clinical factors associated with hyperuricemia (HUA) in patients with newly diagnosed coronary heart disease (CHD).
- To evaluate the correlation of novel derived biomarkers, such as the monocyte-to-high-density lipoprotein cholesterol ratio (MHR) and remnant cholesterol (RC), with HUA.
- To provide a reference for clinical risk identification, prevention, and treatment strategies for HUA in CHD patients.
Main Methods:
- A retrospective study involving 2265 patients with newly diagnosed CHD.
- Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were employed to identify factors associated with HUA.
- A prediction model was constructed and validated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration plots.
Main Results:
- Independent factors associated with HUA included triglycerides, creatinine, monocyte-to-high-density lipoprotein cholesterol ratio (MHR), remnant cholesterol (RC), and alcohol use.
- The developed prediction model demonstrated good discrimination (AUROC 0.781 in modeling group, 0.780 in validation group) and clinical utility.
- MHR and RC showed a positive nonlinear relationship with HUA risk, with MHR having a stronger association in the hypertensive subgroup.
Conclusions:
- Novel biomarkers, MHR and RC, are significantly associated with HUA risk in patients with new-onset CHD.
- These biomarkers, alongside traditional factors like triglycerides and creatinine, support a multifactorial approach to evaluating HUA-related risk.
- The findings offer a valuable reference for clinical risk stratification and management of HUA in the context of CHD.
Background:
This study aimed to investigate clinical factors associated with hyperuricemia (HUA) in patients with newly diagnosed coronary heart disease (CHD) and to evaluate the correlation of novel derived biomarkers with HUA, thereby providing a reference for clinical risk identification, prevention, and treatment.
Methods:
This retrospective study analyzed 2265 patients with newly diagnosed CHD (2019-2024) who were randomly assigned to a modeling group (n = 1812) and a validation group (n = 453); HUA was defined as serum uric acid (UA) ≥420 μmol/L. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to identify associated factors. A prediction model was constructed and evaluated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration plots.
Results:
Independent factors associated with HUA included triglycerides (odds ratio (OR) = 1.097, 95% CI: 1.036-1.160), creatinine (OR = 1.030, 95% CI: 1.025-1.035), monocyte-to-high-density lipoprotein cholesterol ratio (MHR; OR = 1.447, 95% CI: 1.057-1.981), remnant cholesterol (RC; OR = 1.812, 95% CI: 1.406-2.337), and alcohol use (OR = 1.596, 95% CI: 1.202-2.119) (all p < 0.05). The model demonstrated good discrimination with areas under the ROC curve (AUROCs) of 0.781 (0.729-0.832) in the modeling group and 0.780 (0.751-0.808) in the validation group, as well as good calibration and clinical utility at threshold probabilities of 0.22-1.00 and 0.20-0.66, respectively. MHR and RC exhibited a positive nonlinear relationship with HUA risk, with a stronger association for MHR in the hypertensive subgroup (p < 0.05).
Conclusion:
MHR and RC are novel biomarkers associated with HUA risk in patients with new-onset CHD. When combined with traditional factors such as triglycerides and creatinine, these novel biomarkers support a multifactorial, integrated evaluation of HUA-related risk and serve as a reference for clinical risk stratification and management.
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