In this study, we observed an independent association between higher or lower TyG-BMIs and an elevated risk of all-cause mortality among the population undergoing PD. A U-shaped relationship was identified between TyG-BMI and all-cause mortality, with the inflection point at TyG-BMI = 209.73. At this time, patients have the lowest all-cause mortality rate, whereas those above or below this threshold have increased mortality rates. A J-shaped relationship was found between TyG-BMI and CVD mortality, with the inflection point at TyG-BMI = 206.64. The risk of CVD mortality remains relatively stable until the TyG-BMI reaches 206.64, after which it begins to increase rapidly. Sex differences were observed between the groups. Higher TyG-BMI values were associated with increased all-cause and cardiovascular mortality in men, whereas in women, lower TyG-BMI values were linked to elevated all-cause mortality but showed no difference in cardiovascular mortality risk between the groups. However, comorbidities such as hypertension and diabetes did not influence these relationships. These findings support the potential clinical utility of the TyG-BMI as a reference value and predictive marker. It is also essential to consider the modulating impact of gender differences.
A number of publications have reported that an elevated TyG-BMI is associated with an increased risk of cardiovascular diseases [12, 14, 15, 16, 17]. Our findings also indicate that higher TyG-BMIs are linked to an elevated risk of all-cause and CVD mortality in individuals undergoing PD than are TyG-BMIs ranging from 189.57 to 227.15. This could be attributed to the fact that participants with high TyG-BMIs presented higher SBP, TG, and BMIs, and a higher incidence of diabetes as well as original diseases such as diabetic nephropathy and hypertensive nephropathy, contributing to increased mortality. Importantly, IR was identified as one explanation for this association (25) and is a prominent characteristic in end-stage kidney disease patients [6, 8, 9, 26, 27], particularly in PD patients. In PD patients, prolonged exposure to glucose solutions, which are widely used in most countries, may lead to systemic hyperglycemia and obesity while exacerbating IR due to exposure to peritoneal glucose exposure along with advanced glycation end products and bioincompatible solutions [10, 11, 12]. On the basis of this premise, IR can induce an imbalance in glucose metabolism which subsequently triggers inflammation and oxidative stress. Furthermore, IR can stimulate increased production of free radicals and glycosylated products leading to nitric oxide (NO) inactivation [28, 29].
Kiran et al. elucidated the U-shaped correlation between BMI and mortality by enrolling 274 Asian PD patients [30]. Similarly, our findings revealed that a lower TyG-BMI was associated with an increased risk of all-cause mortality compared with the intermediate TyG-BMI, which is potentially linked to poor nutritional status [31, 32]. The TyG-BMI exhibited a U-shaped association with all-cause mortality in the population undergoing PD. The level associated with the lowest risk of all-cause mortality ranged from 189.57–227.15. Another study involving 2,689 PD patients demonstrated that the TyG-BMI had a linear association with all-cause and CVD mortality [12]. Importantly, our results indicated that higher and lower levels of glucose, triglycerides or BMI could lead to poorer prognosis. These findings strongly support the need to establish target ranges for triglycerides, glucose and BMI rather than specific target levels.
Numerous studies have demonstrated that the TyG-BMI serves as an independent predictor of adverse cardiovascular events [12, 14, 15, 16, 17]. It is also closely associated with IR, which not only contributes to the development of CVD in both the CKD patients and diabetic patients but also predicts the cardiovascular prognosis of CVD patients [6, 29]. Previous research has consistently shown a significant correlation between TyG-BMI and future CVD mortality, myocardial infarction, and stroke, indicating that insulin resistance plays a pivotal role in the pathogenesis and prognosis of cardiovascular diseases [12, 15, 17]. Our study similarly revealed a significant association between TyG-BMI and cardiovascular mortality. When the two groups were compared, the high TyG-BMI group clearly presented significantly higher rates of CVD-related death than did the middle group across all three models, however, no significant difference was observed between the low TyG-BMI group and the middle TyG-BMI group.
Interestingly, we observed that sex has a modifying effect on the risk of mortality. This phenomenon may be attributed to hormonal disparities (33), insulin resistance, visceral adiposity, endothelial dysfunction, and chronic inflammation. Furthermore, lifestyle variations (e.g., a higher prevalence of risky health behaviors such as smoking, excessive alcohol consumption, and sedentary habits among men) contribute to increased all-cause and cardiovascular disease mortality in men with elevated TyG-BMIs. Naturally, this necessitates thorough examination and validation within a more extensive cohort of peritoneal dialysis patients.
Study strengths and limitations
In this study, we identified an independent association between the TyG-BMI and all-cause as well as CVD mortality in a single PD center. Furthermore, we observed for the first time that the relationship between the TyG-BMI and all-cause mortality exhibited a U-shaped pattern in the population undergoing PD.
However, our study has several limitations. First, the levels of triglycerides and glucose may have been influenced by prescribed medications, which were not reported in our study, potentially introducing bias to the results. Second, data on triglycerides, glucose and BMI were only collected only once at baseline, and it remains unclear whether changes in TyG-BMI over time could impact its association with mortality. Therefore, longitudinal cohort studies are necessary to explore the persistence of the association between TyG-BMI and mortality over time. Third, we did not assess the homeostasis model assessment of insulin resistance or compare it with the TyG-BMI because of insufficient data on insulin levels during follow-up. Finally, potential residual confounding factors should be acknowledged given that this is an observational study.