Prognostic Impact Of Low Triiodothyronine Syndrome In Patients With Acute Heart Failure

Background: Data from clinical studies have suggested a potential worse impact of low triiodothyronine(T3)syndrome on clinical outcomes in patients with acute heart failure(AHF).However,the optimal target goal that should be achieved for free T3 remain undefined.The aim of the prospective cohort study was to evaluate the effect of low T3 syndrome in the prognosis of AHF and quantify dose-response associations between free T3 and the risk of all-cause mortality.Methods: A total of 312 AHF patients with detailed thyroid hormone profile were prospectively enrolled.Low T3 syndrome was defined by low free T3(FT3 < 3.1pmol/L)level accompanied by normal thyroid-stimulating hormone(TSH)levels.We evaluated the association between free T3 and prognosis of AHF in multivariable Cox regression and restricted cubic spline analyses adjusted for cofounders.Results: Our results showed that 121(38.8%)cumulative deaths occurred over a median follow-up period of 35 months.Cardiovascular death was observed in 94 (30.1%)patients.72(23.1%)patients had low T3 syndrome.After adjusting confounders in the Cox model,low T3 syndrome associated hazard ratio(HR)and95% confidence intervals(CI)for all-cause mortality was 1.74(95%CI 1.16–2.61,P= 0.007),for cardiovascular mortality was 1.90(95%CI 1.21–2.98,P = 0.005).The regression splines suggested a negative linear relation for FT3 with mortality risk.Considering reclassification,adding low T3 syndrome to the fully adjusted model improved the risk prediction for all-cause mortality(Integrated discrimination improvement [IDI] 2.0%,P = 0.030;net reclassification improvement [NRI] 8.9%,P= 0.232)and cardiovascular mortality(IDI = 2.5%,P = 0.030;NRI 21.3%,P =0.013).Conclusion: Low-T3 syndrome should be considered as an important risk predictor for prognosis of AHF.Free T3 shows a linear negative association with mortality risk.Background: Acute heart failure(AHF)is associated with common all-cause death.However,there is no effective method to evaluate the prognosis of AHF.This study was to develop a simple and effective nomogram model for predicting all-cause mortality in patients with AHF.Methods: A total of 312 patients with AHF admitted to the First Affiliated Hospital of Nanjing Medical University from 2012 to 2019 were prospectively analyzed.A total of 289 patients with AHF treated in the Affiliated Hospital of Nantong University from 2013 to 2018 were included as the validation cohort,and the clinical baseline data were collected.Based on the results of multivariate Cox regression analysis,a nomogram was developed.The discrimination ability,calibration ability and clinical benefit of nomogram model were evaluated by concordance index,calibration curve and decision curve analysis.Results: In the training cohort,age,gender,N-terminal pro brain natriuretic peptide(NT-pro BNP),urea nitrogen and low T3 syndrome(LT3S)were the independent prognostic factors of patients with AHF,and finally the nomogram model was developed.In the validation cohort,the nomogram model had good discrimination ability(AUC = 0.700;95% CI 0.65-0.76)and calibration ability.The results of decision curve analysis showed that the nomogram model has higher clinical net benefit than the full model and empty model.Conclusion: The development of a simple nomogram model can accurately quantify the risk of all-cause mortality in patients with AHF.