TyG index variability and cumulative TyG index may predict incident CKD in non-diabetic population

Written By : Jacinthlyn Sylvia |Medically Reviewed By : Dr. Kamal Kant Kohli Published On 2024-01-09T20:30:54+05:30 | Updated On 9 Jan 2024 8:30 PM IST

In a recent study highlighted the intricate connection between metabolic health and kidney function by identifying the triglyceride-glucose (TyG) index as a critical marker to predict the onset of chronic kidney disease (CKD) in non-diabetic individuals. The findings of this research were published in the BMC Cardiovascular Diabetology.

The TyG index was recognized as a reliable surrogate marker for insulin resistance and has previously been associated with incident CKD. The impact of the longitudinal patterns of TyG index on CKD risk among non-diabetic populations were unexplored so far.

The prospective study encompassed a total of 5484 non-diabetic participants who underwent annual health examinations from 2015 to 2017. The study calculated TyG index variability and cumulative TyG index to assess the longitudinal patterns. 879 participants developed CKD over a median follow-up of 3.82 years.

The participants in the highest TyG index variability quartile exhibited a hazard ratio (HR) of 1.772 (95% CI: 1.453, 2.162) while the individuals with highest cumulative TyG index quartile had an HR of 2.091 (95% CI: 1.646, 2.655) for incident CKD. These associations persisted even after adjusting for various factors.

The study underscored the significant improvement in discrimination and reclassification when baseline TyG, TyG index variability, and cumulative TyG index were included into the clinical risk model for CKD.

The findings suggest that both TyG index variability and cumulative TyG index serve as independent predictors of incident CKD in non-diabetic populations. This study emphasize the potential of monitoring longitudinal patterns of TyG index as a valuable tool to predict and prevent the onset of chronic kidney disease.

Reference:

Chen, N., Ma, L.-L., Zhang, Y., Chu, X., Dong, J., & Yan, Y.-X. (2024). Association of long-term triglyceride-glucose index patterns with the incidence of chronic kidney disease among non-diabetic population: evidence from a functional community cohort. In Cardiovascular Diabetology (Vol. 23, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s12933-023-02098-7

Cardiovascular Diabetologytriglyceride-glucose indexChronic kidney disease

Source : BMC Cardiovascular Diabetology

Jacinthlyn Sylvia

Neuroscience Masters graduate

Jacinthlyn Sylvia, a Neuroscience Master's graduate from Chennai has worked extensively in deciphering the neurobiology of cognition and motor control in aging. She also has spread-out exposure to Neurosurgery from her Bachelor’s. She is currently involved in active Neuro-Oncology research. She is an upcoming neuroscientist with a fiery passion for writing. Her news cover at Medical Dialogues feature recent discoveries and updates from the healthcare and biomedical research fields. She can be reached at editorial@medicaldialogues.in

Dr. Kamal Kant Kohli

Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: drkohli@medicaldialogues.in. Contact no. 011-43720751