Objective:To develop and validate a nomogram prediction model for major adverse cardiovascular events (MACE) in elderly patients with chronic heart failure (CHF) based on the ratio of homocysteine to free triiodothyronine (HCY/FT3).Methods:This research was a prognostic study. A total of 1 301 elderly patients with CHF admitted to the Department of General Practice of Shanghai Fifth People′s Hospital Affiliated to Fudan University from January 2018 to January 2023 were enrolled and divided into MACE group ( n=564) and non-MACE group ( n=737) according to whether MACE occurred at the end of the follow-up. Baseline clinical data was collected. The follow-up period was 18 months, with the follow-up deadline being June 30, 2024. The primary endpoint was the occurrence of MACE, including death from any cause or re-hospitalization due to heart failure. Multivariate logistic regression analysis was used to determine the independent risk factors for MACE of elderly patients with CHF ( P<0.05). All patients included were randomly allocated into a training cohort ( n=913) and a validation cohort ( n=388) in a 7∶3 ratio. A nomogram prediction model was developed. The model was internally validated by bootstrapping. The discriminative ability of the model was assessed by calibration curves and receiver operating characteristic (ROC) curves. Results:Multivariable logistic regression analysis demonstrated that atrial fibrillation history, lower diastolic blood pressure, elevated uric acid, elevated free thyroxine (FT4), higher HCY/FT3 ratio, and lower left ventricular ejection fraction (LVEF) were independent predictors of MACE in elderly CHF patients ( P<0.05). A nomogram model incorporating these factors was developed. Internal validation using bootstrapping showed good calibration, as both training and validation cohort calibration curves closely approximated the ideal line. ROC curve analysis indicated an area under the curve of 0.721 (95% CI: 0.661-0.782) for the nomogram in predicting MACE. Conclusions:We developed and internally validated a nomogram incorporating the HCY/FT3 ratio to predict MACE risk in elderly CHF patients. This model demonstrated acceptable discrimination and good calibration, suggesting potential clinical utility for risk stratification.

Objective:To develop and validate a nomogram prediction model for major adverse cardiovascular events (MACE) in elderly patients with chronic heart failure (CHF) based on the ratio of homocysteine to free triiodothyronine (HCY/FT3).Methods:This research was a prognostic study. A total of 1 301 elderly patients with CHF admitted to the Department of General Practice of Shanghai Fifth People′s Hospital Affiliated to Fudan University from January 2018 to January 2023 were enrolled and divided into MACE group ( n=564) and non-MACE group ( n=737) according to whether MACE occurred at the end of the follow-up. Baseline clinical data was collected. The follow-up period was 18 months, with the follow-up deadline being June 30, 2024. The primary endpoint was the occurrence of MACE, including death from any cause or re-hospitalization due to heart failure. Multivariate logistic regression analysis was used to determine the independent risk factors for MACE of elderly patients with CHF ( P<0.05). All patients included were randomly allocated into a training cohort ( n=913) and a validation cohort ( n=388) in a 7∶3 ratio. A nomogram prediction model was developed. The model was internally validated by bootstrapping. The discriminative ability of the model was assessed by calibration curves and receiver operating characteristic (ROC) curves. Results:Multivariable logistic regression analysis demonstrated that atrial fibrillation history, lower diastolic blood pressure, elevated uric acid, elevated free thyroxine (FT4), higher HCY/FT3 ratio, and lower left ventricular ejection fraction (LVEF) were independent predictors of MACE in elderly CHF patients ( P<0.05). A nomogram model incorporating these factors was developed. Internal validation using bootstrapping showed good calibration, as both training and validation cohort calibration curves closely approximated the ideal line. ROC curve analysis indicated an area under the curve of 0.721 (95% CI: 0.661-0.782) for the nomogram in predicting MACE. Conclusions:We developed and internally validated a nomogram incorporating the HCY/FT3 ratio to predict MACE risk in elderly CHF patients. This model demonstrated acceptable discrimination and good calibration, suggesting potential clinical utility for risk stratification.