Frontiers in endocrinology · 2026
Thyroid feedback quantile-based index predicts 90-day all-cause mortality or readmission in hospitalized heart failure patients: a retrospective cohort study.
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Ma Li, Li Huijuan, Gou Manting, Liu Xingbang, Zhang Tong
Аннотация
OBJECTIVE: The Thyroid Feedback Quantile-Based Index (TFQI), a recently developed indicator derived from thyroid stimulating hormone (TSH) and free thyroxine (FT4) levels, has demonstrated prognostic value in metabolic diseases. Nevertheless, its utility in predicting clinical endpoints among heart failure (HF) patients remains unclear. This study aimed to identify the optimal TFQI cutoff for risk stratification and to evaluate its association with adverse outcomes in HF patients.
METHODS: A total of 402 HF patients were enrolled in the study. Using the composite outcome of 90-day all-cause mortality or heart failure readmission, the X-tile project determined the optimal TFQI threshold. TFQI's predictive value was then evaluated using univariate and multivariate Cox regression, restricted cubic spline (RCS) analysis, and Kaplan-Meier curves.
RESULTS: A threshold of 0.10 best stratified high-risk patients (adjusted HR: 1.95, 95% CI: 1.11-3.43, P = 0.019). RCS analysis indicated a linear dose-response (P for non-linearity = 0.677). Kaplan-Meier analysis confirmed significantly worse survival with TFQI > 0.10 vs ≤ 0.10 (Log-rank P = 0.004).
CONCLUSIONS: A TFQI exceeding 0.10 is associated with a significantly increased risk of 90-day all-cause mortality or HF readmission in hospitalized HF patients. This study suggests TFQI acts as a promising exploratory biomarker correlated with adverse clinical outcomes in HF. Further large-scale, multicenter and prospective studies are still required to verify its clinical value and confirm its role in risk stratification.
METHODS: A total of 402 HF patients were enrolled in the study. Using the composite outcome of 90-day all-cause mortality or heart failure readmission, the X-tile project determined the optimal TFQI threshold. TFQI's predictive value was then evaluated using univariate and multivariate Cox regression, restricted cubic spline (RCS) analysis, and Kaplan-Meier curves.
RESULTS: A threshold of 0.10 best stratified high-risk patients (adjusted HR: 1.95, 95% CI: 1.11-3.43, P = 0.019). RCS analysis indicated a linear dose-response (P for non-linearity = 0.677). Kaplan-Meier analysis confirmed significantly worse survival with TFQI > 0.10 vs ≤ 0.10 (Log-rank P = 0.004).
CONCLUSIONS: A TFQI exceeding 0.10 is associated with a significantly increased risk of 90-day all-cause mortality or HF readmission in hospitalized HF patients. This study suggests TFQI acts as a promising exploratory biomarker correlated with adverse clinical outcomes in HF. Further large-scale, multicenter and prospective studies are still required to verify its clinical value and confirm its role in risk stratification.