Anemia-driven heterogeneity in TG-UA Association: A DDML approach to precision management of hyperuricemia in hospitalized patients aged 50–65

Abstract

Hyperuricemia has posed a great threat in the globe and is also linked with serious health risks such as hyperlipidemia. Extensive researches have explored the relationship between hypertriglyceridemia and serum uric acid (UA), but the results are mixed due to multiple demographic and cardiovascular-related factors. Our research aims to delve into the relationship between triglyceride (TG) and serum UA across various demographic groups and groups with different anemic conditions. Our research concentrated on patients admitted to Beijing Fengtai Youanmen Hospital from August 2016 to June 2023, the final dataset encompassed clinical data from 43,758 patients, providing a robust basis for our analysis. Data analysis was conducted using Stata MP version 17.1 (Stata Corp LLC, College Station, TX, USA). By using double debiased machine learning method to delve into the relationship between TG and UA. Our findings indicate a strong association between elevated TG levels and increased UA levels among individuals aged 50–65 years (P < 0.001). Our results showed a positive relationship between TG and UA in non-anemic males aged 50–65 when TG levels were 1.1–1.90 mmol/L, and similarly among non-anemic females aged 50–65, TG-UA correlation persisted with TG levels below 2.30 mmol/L. Conversely, among anemic patients aged 50–65, both in male and female groups, there is no significant association between TG and UA levels. Our research suggests that to address hyperuricemia, reducing blood TG levels may be an effective strategy. However, this strategy should not be applied to anemic patients aged 50–65.