Last Year of Life, Frailty, and Out-of-Pocket Expenses in Older Adults: A Secondary Analysis of the Mexican Health and Aging Study

Relationship of frailty status with health resource use and healthcare costs in the population aged 65 and over in Catalonia

BACKGROUND

Frailty is a geriatric syndrome with repercussions on health, disability, and dependency.

OBJECTIVES

To assess health resource use and costs attributable to frailty in the aged population.

METHODS

A population-based observational longitudinal study was performed, with follow-up from January 2018 to December 2019. Data were obtained retrospectively from computerized primary care and hospital medical records. The study population included all inhabitants aged ≥ 65 years ascribed to 3 primary care centres in Barcelona (Spain). Frailty status was established according to the Electronic Screening Index of Frailty. Health costs considered were hospitalizations, emergency visits, outpatient visits, day hospital sessions, and primary care visits. Cost analysis was performed from a public health financing perspective.

RESULTS

For 9315 included subjects (age 75.4 years, 56% women), frailty prevalence was 12.3%. Mean (SD) healthcare cost in the study period was €1420.19 for robust subjects, €2845.51 for pre-frail subjects, €4200.05 for frail subjects, and €5610.73 for very frail subjects. Independently of age and sex, frailty implies an additional healthcare cost of €1171 per person and year, i.e., 2.25-fold greater for frail compared to non-frail.

CONCLUSIONS

Our findings underline the economic relevance of frailty in the aged population, with healthcare spending increasing as frailty increases.

Development and validation of dynamic nomogram of frailty risk for older patients hospitalized with heart failure

Objective

This study aimed to establish and validate a dynamic online nomograph for predicting the risk of frailty in older patients hospitalized with heart failure in China.

Methods

A total of 451 older adults with heart failure hospitalized were selected between December 2021 and November 2022 at the Department of Cardiovascular Medicine in a Class A tertiary hospital in Shandong, China. The data of patients were obtained by using Barthel Index, instrumental activity of daily living scale, mini nutrition assessment-short form, Pittsburgh sleep quality index scale, Morse fall risk assessment scale and general information scale. The brain natriuretic peptide and echocardiographic indexes of patients were collected by electronic medical records. All participants were randomly divided into the training set (n = 319) and the validation set (n = 132) at the ratio of 7:3. The training set is used for model construction, and the validation set is used for internal validation. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression method to filter modeling variables, while the multivariable logistic regression was used to establish the nomogram based on the screened optimal variables. The performance of the model was evaluated by the area under the curve (AUC) of the receiver operator characteristic (ROC) curve, Hosmer-Lemeshow test, calibration plot, and decision curve analysis (DCA).

Results

The prevalence of frailty in 451 patients was 50.6%, 51.4%, and 48.5% in the training and validation sets, respectively. Drinking, grip strength, New York Heart Association (NYHA) class, multimorbidity, hospitalization history of heart failure, Barthel Index, the instrumental activities of daily living, nutritional status, sleep, fall, and left atrial end-diastolic diameter were used for LASSO regression analysis as the significant predictors of frailty. According to internal validation, the AUC of the ROC curve for the nomogram was 0.920, with a sensitivity of 86.8% and specificity of 84.4%. Moreover, in the validation set, the P-values of the H-L test were 0.742, and the calibration curve had good concordance between the estimated frailty risk and actual observation, indicating the model was well-calibrated. The DCA results confirmed that the nomogram had a well-performance in clinical suitability.

Conclusions

An online dynamic nomogram predicting frailty for older patients hospitalized for heart failure in China was well-established and identified in this study. This model benefits medical professionals in identifying high-risk frailty in older hospitalized patients with heart failure, which could reduce the medical and disease burden of heart failure to a certain extent. However, further verification is needed in the future.

Characteristics and Quality of Diagnostic and Risk Prediction Models for Frailty in Older Adults: A Systematic Review

Several prediction models for frailty in older adults have been published, but their characteristics and methodological quality are unclear. This review aims to summarize and critically appraise the prediction models. Studies describing multivariable prediction models for frailty among older adults were included. PubMed, Embase, Web of Science, and PsycINFO were searched from outset to Feb 21, 2021. Methodological and reporting quality of included models were evaluated by PROBAST and TRIPOD, respectively. All results were descriptively summarized. Twenty articles including 39 models were identified. The included models showed good predictive discrimination with C indices ranging from 0.70 to 0.98. However, all studies except one were assessed as high risk of bias mainly due to inappropriate analysis; meanwhile, poor reporting quality was also frequently observed. Few mature prediction models can be used in practice. Researchers should pay more attention to external validation and improving the quality both in methodology and reporting.