Diagnosing risk of frailty in patients hospitalized with heart failure is a safe and effective means of improving patient management.
Investigators created a dynamic online nomogram that predicts risk of frailty in patients hospitalized with heart failure (HF), according to a study published in the International Journal of Nursing Sciences. Mechanisms of HF and frailty overlap, and patients with HF could have a 3-times greater risk of becoming frail compared to patients without HF.
“Our dynamic nomograph is equivalent to a web calculator,” wrote study authors in the article. “By inputting the corresponding variable value, we can get the risk of frailty.” Diagnosing frailty can facilitate effective and multidisciplinary interventions to reduce hospital burden and improve the clinical impact of patient management.
Older adults hospitalized with HF are at increased risk of frailty—defined as the loss of physiological reserve and function caused by biologic or age-related factors. Frailty is independent to HF. This population is 6-times more likely to have frailty than patients without HF, therefore identifying and treating it is important to delay aging, restore resilience, and reduce hospitalization rate and medical burden.
Tools to identify frailty are limited because they cannot predict the calculated risk of developing frailty; additionally, they are mainly available to patients in developed countries. The current study aimed to validate the efficacy of the online model at predicting risk of frailty in hospitalized patients with HF.
The study included 451 older adults in China who were hospitalized for HF. Investigators used the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis to predict frailty; they then evaluated 11 factors that predict frailty risk, including drinking, grip strength, multimorbidity (2 or more illnesses), cardiac function, hospitalizations, nutrition, and falls.
Risk of frailty was 4.42-times higher in patients with multimorbidity, and frailty incidence increased with increasing multimorbidity. Further, although multimorbidity factors into the development of frailty, investigators also observed that it can additionally worsen current incidence of frailty.
The data suggest that a patient’s current state of cardiac function could predict the severity of frailty; worse cardiac function was associated with increased frailty risk. “Changes in cardiac structure and function worsen frailty and underscore the importance of incorporating cardiac function evaluation into the frailty assessment of these patients,” study authors wrote.
The study includes some limitations. Investigators did not include external validation to support their findings. In addition, while a LASSO regression algorithm selects characteristics of the optimal model, it cannot solve multicollinearity—the correlation between the 2 independent variables (HF and frailty).
Approximately 64.4 million people have HF worldwide. Caused by damage to the heart, the heart becomes less able to fill with or pump blood. It can be difficult to manage older patients with HF because of comorbidities such as frailty, and the disease has a taxing financial burden.
Li Q, Chen Y, Qin D, et al. Development and validation of dynamic nomogram of frailty risk for older patients hospitalized with heart failure. Int J Nurs Sci. 2023. doi:10.1016/j.ijnss.2023.03.014