Evidence map›Paper›PMID 41877923›Full record

Observational studyFrontiers in endocrinology2026

Propensity score analysis of triglyceride-glucose index in newly diagnosed patients with essential hypertension as a predictor of microalbuminuria.

Nuoni Wang, Shihao Liu, Wei Wang, Yicheng Zou, Liangqing Ge, Sulan Huang

Abstract readObservational Study
In one paragraph

Observational study in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Nuoni WangDepartment of Cardiac Electrophysiology, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, China.
Shihao LiuDepartment of Cardiac Electrophysiology, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, China.
Wei WangDepartment of Science and Education, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, China.
Yicheng ZouDepartment of Science and Education, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, China.
Liangqing GeDepartment of Cardiology, Changde Hospital, Xiangya School of Medicine, Central South University(The First People's Hospital of Changde City), Changde, China.
Sulan HuangDepartment of Cardiology, Changde Hospital, Xiangya School of Medicine, Central South University(The First People's Hospital of Changde City), Changde, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The Triglyceride-Glucose (TyG) index has emerged as a potential predictor for microalbuminuria (MAU) in patients with essential hypertension. This study aims to assess the TyG index as a predictor of MAU in newly diagnosed hypertensive patients, using propensity score matching (PSM) to control for confounding factors. Methods: A cohort of 2,052 newly diagnosed hypertensive patients from Changde Hospital, China (January 2020 to December 2024), was analyzed. The TyG index cutoff value was determined by receiver operating characteristic (ROC) analysis, with a value of 9.125. PSM was employed to balance baseline differences between low and high TyG index groups, and logistic regression models were used to analyze the association between TyG index and MAU. Subgroup analyses and sensitivity analyses were conducted to evaluate the robustness of the findings. Results: In the final cohort, 2,052 patients were divided into two groups based on the optimal TyG index cutoff value of 9.125. After propensity score matching (PSM), the high TyG index group (≥9.125) exhibited significantly higher rates of MAU compared to the low TyG index group (<9.125). In the adjusted models, the odds ratio (OR) for MAU in the high TyG index group was 2.37 (95% CI 1.73-3.26). The analysis revealed a non-linear, L-shaped association between TyG index and MAU, with a marked increase in the prevalence of MAU in the high TyG group. Sensitivity analyses, including inverse probability treatment weighting (IPTW), reinforced these findings, with the high TyG index group consistently showing a higher risk of MAU across both original and matched cohorts. Conclusions: The TyG index is a simple and accessible biomarker for predicting MAU in newly diagnosed hypertensive patients, providing valuable insight for early detection of kidney damage in this population.

Indexed as

AlbuminuriaBlood GlucoseEssential HypertensionTriglyceridesAdultBiomarkersCase-Control StudiesChinaFemaleHumansMaleMiddle AgedOdds RatioPredictive Value of TestsPrevalencePropensity ScoreBiomarkersBlood GlucoseTriglyceridesessential hypertensioninsulin resistancemicroalbuminuriapropensity score analysisthe triglyceride-glucose index

Identifiers

PMID41877923
PMCPMC13006190

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.