Study design and patient population
This is a post-hoc analysis of the FRAGILE-HF cohort study, in which 1,332 hospitalized patients aged ≥65 years with decompensation of heart failure, who could ambulate at discharge, were included. The study design and main results have already been published elsewhere 15. Briefly, the main objective of FRAGILE-HF was to evaluate the prevalence and prognostic impact of multi-frailty domains in older patients with heart failure who require hospitalization. The exclusion criteria were: (1) previous heart transplantation or left ventricular assist device implantation, (2) chronic peritoneal dialysis or hemodialysis, and (3) acute myocarditis. Patients with missing BNP or N-terminal-proBNP data, and patients with a BNP level <100 pg/mL or N-terminal-proBNP level <300 pg/mL at admission were also excluded as the diagnosis could be unclear in these cases. We enrolled patients with both heart failure with reduced and preserved ejection fraction. Fifteen hospitals in Japan enrolled patients from September 2016 to March 2018. Physical examination, echocardiography, blood samples, and drug history were obtained when patients were stable, prior to discharge. From the AST and ALT values obtained before discharge, patients were divided into three groups based on predetermined cut-off values of AAR as follows: low AAR, AAR<1.16; middle AAR, 1.16≤AAR<1.70; and high AAR, AAR≥1.70 5.
All participants were notified regarding their participation in the present study and it was explained that they were free to opt out of participation at any time. Written, informed consent was obtained from each patient prior to enrolment. Our study complies with the Declaration of Helsinki and Japanese Ethical Guideline for Medical and Health Research involving Human Subjects. The study protocol was approved by the Sakakibara Heart Institution of Okayama Research Ethics Committee. Study information including objectives, inclusion and exclusion criteria, primary outcome, and the names of participating hospitals were published in the publicly available University Hospital Information Network (UMIN-CTR, unique identifier: UMIN000023929) before the first patient was enrolled.
Assessment of physical frailty and physical function
Physical frailty was defined by the Fried phenotype model, which is the most widely applied model, and generally considered as the standard model for physical frailty 6. According to Fried's model, the frailty phenotype consists of the following five elements: slowness (gait speed), weakness (hand grip strength), weight loss, exhaustion, and low physical activity 16.
We also evaluated SPPB and 6-minute walk distance, performed by experienced physical therapists and/or heart failure specialists. The SPPB consists of 3 physical performance tests to assess each frailty domain, including balance (static standing balance), gait speed test (4-meter walk time), and weakness (time to complete 5 repeated chair stands) 17. Each test is scored from 0–4, for a total score of 0–12. For balance, the participants were asked to maintain their feet in side-by-side, semi-tandem, and tandem positions for 10 seconds each. For the gait speed assessment test, the participants’ usual speed was timed during a 4-meter walk. For the chair stand test, participants were asked to stand up and sit down five times as quickly as possible. The 6-minute walk distance was assessed in an unobstructed hallway according to the guideline as follows 18: patients were instructed to walk as fast as possible between two points positioned 30-meter apart and the distance walked in 6 min was recorded. Patients were allowed to use an assist device if needed.
Assessment of nutritional status
GNRI19 was used to evaluate the nutritional status of patients. The index was calculated as follows: 14.89 × serum albumin concentration (g/L) + 41.7 × (weight [kg]/ideal weight [kg]). Ideal weight was defined as: 22 × height (m2).
Outcomes
Prognosis of registered patients within 1 year of discharge was prospectively collected up to March 2019. Our primary outcome was all-cause death. After discharge, most patients were followed up in outpatient clinics at least every 3 months, and additionally on need-basis. For those without in-person follow-up scheduled in clinics, prognostic data were obtained from telephone interviews and medical records of other medical departments that cared for the patient or from the family.
Statistical analysis
Normally distributed data are expressed as mean and standard deviation, and non-normally distributed data are reported as median with interquartile range. Categorical data are shown as numbers and percentages. Data were compared between groups using Student’s t-tests or Mann-Whitney U tests for continuous variables and chi-squared or Fisher exact tests for categorical variables as appropriate. The associations between AAR and physical function and nutritional status were investigated using linear regression analysis. Association between physical frailty and AAR was evaluated with logistic regression analysis. In both multivariable analyses, age and gender were used as adjustment variables. Regarding time-dependent survival analysis, event-free survival curves were constructed using the Kaplan-Meier survival method and compared with log-rank statistics. The AUC for 1-year mortality was used to evaluate the predictive value of AAR for 1-year mortality. As for the prognostic outcome of all-cause death, the MAGGIC risk score was calculated for each patient as previously described 20. The discrimination and calibration of this risk score have been well validated in Japanese patients with heart failure 21. As adding BNP level at discharge has been shown to be associated with improvement of discrimination with adequate calibration 21, we used the MAGGIC risk score and log-transformed BNP as an adjustment variable in a multivariable prognostic model for the outcome of all-cause death.
A two-tailed P value <0.05 was considered statistically significant. Statistical analyses were performed using R version 3.1.2 (R Foundation for Statistical Computing, Vienna, Austria; ISBN 3-900051-07-0, URL http://www.R-project.org).
Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request