A nomogram incorporating ADL impairment predicted one-year mortality with an AUC of 0.794 in training and 0.780 in validation cohorts among older adults with AMI.
Observational (n=43,308)
Yes
Does a prognostic model incorporating Activities of Daily Living (ADL) impairment accurately predict 1-year mortality in older adults with acute myocardial infarction?
A prognostic nomogram incorporating ADL impairment accurately predicts 1-year mortality in older adults with acute myocardial infarction, highlighting the importance of functional assessment in geriatric cardiology.
Effect estimate: Nomogram predictive performance AUC 0.794 in training cohort and 0.780 in validation cohort (95% CI Training cohort AUC 95% CI 0.787−0.802; Validation cohort AUC 95% CI 0.768−0.791)
Purpose: Functional impairment, measured by Activities of Daily Living (ADL), is a major predictor of poor outcomes in older adults. However, among patients with acute myocardial infarction (AMI), a prognostic model that incorporates ADL status is lacking. This study aimed to develop and validate such a model for predicting one-year mortality in older adults with AMI. Patients and Methods: This study included 43,308 AMI patients admitted to the Tianjin Health and Medical Big Data Superplatform from January 2010 to March 2024. Patients were categorized by Barthel Index into ADL normal (n=41,312), mildly impaired ADL (n=1,318), moderately impaired ADL (n=452), and severely impaired ADL (n=226). The cohort was randomly split 7:3 for model development and validation. A nomogram for 1-year all-cause mortality was constructed using predictors identified by Lasso regression, with model performance evaluated through receiver operating characteristic curve (ROC), decision curve analysis (DCA), and calibration curve. Results: Baseline characteristics revealed that with increasing ADL impairment, patients were significantly older median (IQR): 73· 0 (68· 0-78· 0) vs 78· 0 (73· 0-83· 0) vs 79· 0 (73· 0-84· 0) vs 78· 0 (73· 0-83· 0), p < 0· 001, had higher Killip class, and received less percutaneous coronary intervention (PCI) (48· 9% vs 25· 0% vs 17· 3% vs 8· 9%, p < 0· 001). Kaplan-Meier analysis showed significantly increased mortality risks ( p < 0· 001). The final model incorporated seven predictors: ADL status, age, Killip class, ST-elevation myocardial infarction (STEMI) diagnosis, history of stroke, valvular heart disease, and diabetes mellitus. The nomogram achieved area under the curve (AUC) values of 0· 794 and 0· 780 in the training and validation cohorts, respectively. Conclusion: We developed and validated a clinically applicable nomogram for predicting one-year mortality in older adults with AMI, integrating ADL impairment into risk assessment. Incorporating functional evaluation into prognostic modeling may improve individualized management and early rehabilitation planning in geriatric cardiology. Keywords: acute myocardial infarction, activities of daily living, prognosis, nomogram predictive model
Zhang et al. (Sun,) conducted a observational in Older adults (aged ≥65 years) hospitalized with acute myocardial infarction (AMI), stratified by activities of daily living (ADL) impairment measured by Barthel Index (n=43,308). Nomogram incorporating ADL status, age, Killip class, STEMI diagnosis, history of stroke, valvular heart disease, diabetes mellitus vs. None (development and validation of prognostic model using observational data) was evaluated on One-year all-cause mortality (Nomogram predictive performance AUC 0.794 in training cohort and 0.780 in validation cohort, 95% CI Training cohort AUC 95% CI 0.787−0.802; Validation cohort AUC 95% CI 0.768−0.791). A nomogram incorporating ADL impairment predicted one-year mortality with an AUC of 0.794 in training and 0.780 in validation cohorts among older adults with AMI.