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Yin JL, Yang J, Song XJ, Qin X, Chang YJ, Chen X, Liu FH, Li YZ, Xu HL, Wei YF, Cao F, Bai XL, Wu L, Tao T, Du J, Gong TT, Wu QJ. Triglyceride-glucose index and health outcomes: an umbrella review of systematic reviews with meta-analyses of observational studies. Cardiovasc Diabetol 2024; 23:177. [PMID: 38783270 PMCID: PMC11118729 DOI: 10.1186/s12933-024-02241-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Accepted: 04/20/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Numerous meta-analyses have explored the association between the triglyceride-glucose (TyG) index and diverse health outcomes, yet the comprehensive assessment of the scope, validity, and quality of this evidence remains incomplete. Our aim was to systematically review and synthesise existing meta-analyses of TyG index and health outcomes and to assess the quality of the evidence. METHODS A thorough search of PubMed, EMBASE, and Web of Science databases was conducted from their inception through to 8 April 2024. We assessed the quality of reviews using A Measurement Tool to Assess Systematic Reviews (AMSTAR) and the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. This study was registered with PROSPERO (CRD: 42024518587). RESULTS Overall, a total of 95 associations from 29 meta-analyses were included, investigating associations between TyG index and 30 health outcomes. Of these, 83 (87.4%) associations were statistically significant (P < 0.05) according to the random effects model. Based on the AMSTAR tool, 16 (55.2%) meta-analyses were high quality and none was low quality. The certainty of the evidence, assessed by the GRADE framework, showed that 6 (6.3%) associations were supported by moderate-quality evidence. When compared with the lowest category of the TyG index, the risk of contrast-induced nephropathy (CIN) [relative risk (RR) = 2.25, 95%CI 1.82, 2.77], the risk of stroke in patients with diabetes mellitus (RR = 1.26, 95%CI 1.18, 1.33) or with acute coronary syndrome disease (RR = 1.56, 95%CI 1.06, 2.28), the prognosis of coronary artery disease (CAD)-non-fatal MI (RR = 2.02, 95%CI 1.32, 3.10), and the severity of CAD including coronary artery stenosis (RR = 3.49, 95%CI 1.71, 7.12) and multi-vessel CAD (RR = 2.33, 95%CI 1.59, 3.42) increased with high TyG index. CONCLUSION We found that the TyG index was positively associated with many diseases including the risk of CIN and stroke, the prognosis of CAD, and the severity of CAD which were supported by moderate-quality evidence. TyG index might be useful to identify people at high-risk for developing these diseases.
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Affiliation(s)
- Jia-Li Yin
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China
| | - Jing Yang
- Department of Endocrinology, The Fourth Affiliated Hospital of China Medical University, Shenyang, China
| | - Xin-Jian Song
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Jiao Chang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xing Chen
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Fang-Hua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yi-Zi Li
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - He-Li Xu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Fan Cao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xue-Li Bai
- Department of Obstetrics and Gynecology, The Fourth Affiliated Hospital of China Medical University, Shenyang, China
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Tao Tao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Jian Du
- Department of Endocrinology, The Fourth Affiliated Hospital of China Medical University, Shenyang, China.
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China.
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China.
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
- NHC Key Laboratory of Advanced Reproductive Medicine and Fertility, (China Medical University), National Health Commission, Shenyang, China.
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Chen S, Li Z, Li H, Zeng X, Yuan H, Li Y. Novel lipid biomarkers and ratios as risk predictors for premature coronary artery disease: A retrospective analysis of 2952 patients. J Clin Hypertens (Greenwich) 2023; 25:1172-1184. [PMID: 37986641 PMCID: PMC10710552 DOI: 10.1111/jch.14751] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 10/23/2023] [Accepted: 10/30/2023] [Indexed: 11/22/2023]
Abstract
This study examined the associations between emerging lipid biomarkers (small dense low-density lipoprotein cholesterol [sdLDL-C), lipoprotein(a) [Lp(a)], and free fatty acids [FFA]), two ratios (sdLDL-C/LDL-C and the triglyceride-glucose [TyG) index), and the Gensini score (GS) in patients with premature coronary artery disease (PCAD) in relation to the extent of coronary stenosis. The authors evaluated a cohort of 2952 individuals undergoing coronary angiography (CAG), encompassing those with PCAD (n = 1749), late-onset coronary artery disease (LCAD; n = 328), and non-coronary artery disease (non-CAD; n = 575). Noteworthy differences were observed in the levels of the novel lipid biomarkers and ratio indexes among the PCAD, LCAD, and non-CAD groups (p < .05). Multiple logistic regression analyses pinpointed Lp(a) (OR = 2.62, 95% CI 1.22-5.63, p = .014) and the TyG index (OR = 2.53, 95% CI 1.08-5.93, p = .033) as independent risk factors for PCAD. Furthermore, these biomarkers and ratio indexes discerned substantial distinctions among PCAD patients with varying GS (p < .05). Consequently, these markers can proficiently anticipate the gravity of coronary artery stenosis (GS > 40) in PCAD patients, as evidenced by the ROC analysis. In conclusion, sdLDL-C, Lp(a), FFA, and the sdLDL-C/LDL-C and TyG indexes have considerable potential as risk and diagnostic markers for coronary artery stenosis in individuals afflicted with PCAD.
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Affiliation(s)
- Si Chen
- Department of Clinical LaboratoryPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- State Key Laboratory of ComplexSevere and Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Department of Clinical LaboratoryBeijing Anzhen HospitalCapital Medical UniversityBeijingChina
| | - Zhan Li
- Department of Clinical LaboratoryPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- State Key Laboratory of ComplexSevere and Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Haolong Li
- Department of Clinical LaboratoryPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- State Key Laboratory of ComplexSevere and Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Xiaoli Zeng
- Department of Clinical LaboratoryBeijing Anzhen HospitalCapital Medical UniversityBeijingChina
| | - Hui Yuan
- Department of Clinical LaboratoryBeijing Anzhen HospitalCapital Medical UniversityBeijingChina
| | - Yongzhe Li
- Department of Clinical LaboratoryPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- State Key Laboratory of ComplexSevere and Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
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