Cardiometabolic Indices as Predictors of Clinical Outcomes in Palliative Care Patients
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Background
Multiple cardiometabolic indices have been proposed for prognostic assessment, yet their comparative performance in palliative care remains unclear. The triglyceride-glucose body mass index (TyG-BMI) integrates metabolic dysfunction with adiposity, but whether it outperforms traditional lipid-based, inflammatory, and nutritional indices requires systematic evaluation.
Purpose
To comprehensively compare TyG-BMI against eleven established cardiometabolic indices for predicting sepsis, mechanical ventilation requirement, and 30-day mortality in palliative care patients, with specific focus on performance in diabetic subpopulations.
Patients and Methods
This retrospective cohort included 318 palliative care patients. Twelve indices were calculated: TyG-BMI (primary); lipid-based (AIP, CRI-I, CRI-II, Non-HDL, TG/HDL); inflammatory (NLR, PLR, SII, MHR); and nutritional (PNI, CAR). ROC analysis compared discriminative ability for sepsis, mechanical ventilation, and 30-day mortality. Subgroup analyses stratified by diabetes mellitus status were performed with interaction testing.
Results
Of 318 patients (mean age 67.4±14.8 years, 55% male), 121 (38.1%) had diabetes, 58 (18.2%) developed sepsis, 42 (13.2%) required mechanical ventilation, and 30 (9.4%) died within 30 days. TyG-BMI achieved the highest AUCs: 0.84 (95% CI 0.78-0.90) for sepsis, 0.82 (0.75-0.89) for ventilation, and 0.87 (0.82-0.92) for 30-day mortality—significantly superior to all comparator indices (p<0.001). In multivariate analysis, TyG-BMI independently predicted mortality (OR 2.38 per SD, 95% CI 1.78-3.18, p<0.001). In diabetic patients, TyG-BMI’s discriminative ability was markedly enhanced (mortality AUC 0.92, 95% CI 0.87-0.97; OR 2.65, 95% CI 1.88-3.74, p<0.001), while other indices showed minimal performance improvement (interaction p<0.001).
Conclusion
TyG-BMI demonstrates superior prognostic performance compared to traditional cardiometabolic indices for predicting sepsis and 30-day mortality in palliative care, with exceptional discriminative ability in diabetic patients.
