Triglyceride glucose index predicts in-hospital mortality in patients with ST-segment elevation myocardial infarction who underwent primary angiography

OBJECTIVES

To assess the correlation between triglyceride glucose (TyG) index and in-hospital mortality in patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

A total of 2190 patients with STEMI who underwent primary angiography within 12 h from symptom onset were selected from the prospective, nationwide, multicenter CAMI registry. TyG index was calculated with the formula: Ln [fasting triglycerides (mmol/L) × fasting glucose (mmol/L)/2]. Patients were divided into three groups according to the tertiles of TyG index. The primary endpoint was in-hospital mortality.

RESULTS

Overall, 46 patients died during hospitalization, in-hospital mortality was 1.5%, 2.2%, 2.6% for tertile 1, tertile 2, and tertile 3, respectively. However, TyG index was not significantly correlated with in-hospital mortality in single-variable logistic regression analysis. Nonetheless, after adjusting for age and sex, TyG index was significantly associated with higher mortality when regarded as a continuous variable (adjusted OR = 1.75, 95% CI: 1.16-2.63) or categorical variable (tertile 3 vs. tertile 1: adjusted OR = 2.50, 95% CI: 1.14-5.49). Furthermore, TyG index, either as a continuous variable (adjusted OR = 2.54, 95% CI: 1.42-4.54) or categorical variable (tertile 3 vs. tertile 1: adjusted OR = 3.57, 95% CI: 1.24-10.29), was an independent predictor of in-hospital mortality after adjusting for multiple confounders in multivariable logistic regression analysis. In subgroup analysis, the prognostic effect of high TyG index was more significant in patients with body mass index < 18.5 kg/m² (P _interaction = 0.006).

CONCLUSIONS

This study showed that TyG index was positively correlated with in-hospital mortality in STEMI patients who underwent primary angiography, especially in underweight patients.

Cardiopulmonary transit time: A novel PET imaging biomarker of in vivo physiology for risk stratification of heart transplant recipients

BACKGROUND

Myocardial blood flow (MBF) can be quantified using dynamic PET studies. These studies also inherently contain tomographic images of early bolus displacement, which can provide cardiopulmonary transit times (CPTT) as measure of cardiopulmonary physiology. The aim of this study was to assess the incremental prognostic value of CPTT in heart transplant (OHT) recipients.

METHODS

94 patients (age 56 ± 16 years, 78% male) undergoing dynamic 13N-ammonia stress/rest studies were included, of which 68 underwent right-heart catherization. A recently validated cardiac allograft vasculopathy (CAV) score based on PET measures of regional perfusion, peak MBF and left-ventricular (LV) ejection fraction (LVEF) was used to identify patients with no, mild or moderate-severe CAV. Time-activity curves of the LV and right ventricular (RV) cavities were obtained and used to calculate the difference between the LV and RV bolus midpoint times, which represents the CPTT and is expressed in heartbeats. Patients were followed for a median of 2.5 years for the occurrence of major adverse cardiac events (MACE), including cardiovascular death, hospitalization for heart failure or acute coronary syndrome, or re-transplantation.

RESULTS

CPTT was significantly correlated with cardiac filling pressures (r = .434, P = .0002 and r = .439, P = .0002 for right atrial and pulmonary wedge pressure), cardiac output (r = - .315, P = .01) and LVEF (r = - .513, P < .0001). CPTT was prolonged in patients with MACE (19.4 ± 6.0 vs 14.5 ± 3.0 heartbeats, P < .001, N = 15) with CPTT ≥ 17.75 beats showing optimal discriminatory value in ROC analysis. CPTT ≥ 17.75 heartbeats was associated with a 10.1-fold increased risk (P < .001) of MACE and a 7.3-fold increased risk (P < .001) after adjusting for PET-CAV, age, sex and time since transplant.

CONCLUSION

Measurements of cardiopulmonary transit time provide incremental risk stratification in OHT recipients and enhance the value of multiparametric dynamic PET imaging, particularly in identifying high-risk patients.