Abstract
PURPOSE: Sepsis is associated with significant endocrine dysfunction, particularly in thyroid hormone metabolism. This study aims to investigate the association between thyroid hormone sensitivity indices and prognosis in sepsis, exploring their potential as early prognostic markers. METHODS: We conducted a retrospective analysis of sepsis patients admitted to the Affiliated Hospital of Guangdong Medical University. Nonlinear associations between thyroid hormones (FT3, FT4, TSH), sensitivity indices (FT3/FT4, TFQI, PTFQI, TSHI, TT4RI), and sepsis mortality were assessed using restricted cubic spline models. Kaplan-Meier curves along with Cox proportional hazards models were used to investigate the longitudinal associations. K-means clustering was applied to thyroid hormone profiles to identify distinct phenotypes. RESULTS: Among 2,391 sepsis patients, non-survivors exhibited significantly lower levels of thyroid hormone and sensitivity indices compared to survivors. Restricted cubic spline analysis revealed a nonlinear dose-response relationship, with lower FT3, TFQI, PTFQI, TSHI, and TT4RI levels associated with increased mortality risk. Multiple Cox regression models identified FT3 (HR = 0.95, 95% CI: 0.93-0.98, p = 0.001), TSH (HR = 0.89, 95% CI: 0.80-0.99, p = 0.004), TFQI (HR = 0.66, 95% CI: 0.51-0.84, p < 0.001), PTFQI (HR = 0.47, 95% CI: 0.37-0.61, p < 0.001), TSHI (HR = 0.92, 95% CI: 0.85-0.99, p = 0.040), and TT4RI (HR = 0.98, 95% CI: 0.97-0.99, p = 0.001) as independent predictors of 90-day mortality. K-means clustering identified two distinct phenotypes, with Phenotype 2, characterized by profound thyroid hormone suppression and reduced sensitivity indices, was associated with a 36% higher mortality risk (HR = 1.42, 95% CI: 1.04-1.91, p = 0.029). CONCLUSION: Impaired thyroid hormone sensitivity are significantly associated with increased mortality in sepsis, emphasizing their potential as prognostic biomarkers and suggest their utility in risk stratification and personalized management of sepsis patients.