Gamma-glutamyl transferase to albumin ratio can predict severity of coronary artery disease detected by coronary computed tomography angiography

L-shaped association between gamma-glutamyl transferase-to-albumin ratio and dabigatran-related bleeding in non-valvular atrial fibrillation patients: a multicenter cohort study

Background

The correlation between the gamma-glutamyl transferase-to-albumin ratio (GAR) and the risk of bleeding in patients with non-valvular atrial fibrillation (NVAF) undergoing treatment with the dabigatran anticoagulant is poorly understood. This study aims to explore whether GAR is associated with bleeding events among patients with NVAF receiving dabigatran anticoagulant therapy.

Methods

We conducted a multicenter, observational cohort study in 12 Chinese hospitals from six provinces, including Beijing, Shanghai and Guangzhou, to evaluate the effectiveness and safety of dabigatran (110 mg) treatment in NVAF patients who were consecutively enrolled during February 2015 and December 2017. All patients had completed a 3-month follow-up period. The baseline variable of interest was the GAR, and the outcome variable was the occurrence of bleeding events. Both univariate and multivariate Cox proportional hazard models were used to evaluate the relationship between GAR and bleeding outcome.

Results

This prospective cohort study included a total of 834 patients (mean age 65.6±11.1 years; 56.8% male). Overall, 82 subjects experienced bleeding. The patients were categorized based on the tertiles of the GAR. Participants in tertile 2 (0.59-1.03) [hazard ratio (HR): 0.28; 95% confidence interval (CI): 0.14-0.55; P<0.001] and tertile 3 (≥1.04) (HR: 0.47; 95% CI: 0.25-0.89; P=0.02) exhibited a lower rate of bleeding compared to the reference group (T1: ≤0.58). Multivariable models with restricted cubic splines demonstrated a nonlinear relationship between GAR and bleeding outcome, with a GAR inflection point of 0.68. The HR (95% CI) was 0.05 (0.01-0.31) (P=0.002) for GAR values <0.68 and 0.96 (0.70-1.31) (P=0.78) for GAR values ≥0.68. Moreover, the correlation between decreased GAR and an increase in bleeding events remained consistent across various subgroups.

Conclusions

GAR is a prevalent, independent predictor of dabigatran-related bleeding in NVAF patients. Moreover, a significant L-shaped association between GAR and bleeding events has been observed.

Using new indices to predict metabolism dysfunction-associated fatty liver disease (MAFLD): analysis of the national health and nutrition examination survey database

BACKGROUND

Metabolism dysfunction-associated fatty liver disease (MAFLD), is the most common chronic liver disease. Few MAFLD predictions are simple and accurate. We examined the predictive performance of the albumin-to-glutamyl transpeptidase ratio (AGTR), plasma atherogenicity index (AIP), and serum uric acid to high-density lipoprotein cholesterol ratio (UHR) for MAFLD to design practical, inexpensive, and reliable models.

METHODS

The National Health and Nutrition Examination Survey (NHANES) 2007-2016 cycle dataset, which contained 12,654 participants, was filtered and randomly separated into internal validation and training sets. This study examined the relationships of the AGTR and AIP with MAFLD using binary multifactor logistic regression. We then created a MAFLD predictive model using the training dataset and validated the predictive model performance with the 2017-2018 NHANES and internal datasets.

RESULTS

In the total population, the predictive ability (AUC) of the AIP, AGTR, UHR, and the combination of all three for MAFLD showed in the following order: 0.749, 0.773, 0.728 and 0.824. Further subgroup analysis showed that the AGTR (AUC1 = 0.796; AUC2 = 0.690) and the combination of the three measures (AUC1 = 0.863; AUC2 = 0.766) better predicted MAFLD in nondiabetic patients. Joint prediction outperformed the individual measures in predicting MAFLD in the subgroups. Additionally, the model better predicted female MAFLD. Adding waist circumference and or BMI to this model improves predictive performance.

CONCLUSION

Our study showed that the AGTR, AIP, and UHR had strong MAFLD predictive value, and their combination can increase MAFLD predictive performance. They also performed better in females.