Physical Frailty May Predict 2-Year Prognosis in Elderly Patients With Acute Myocardial Infarction　- A Report From the FLAGSHIP Study.

BACKGROUND: Elderly patients with acute myocardial infarction (AMI) are a high-risk population for heart failure (HF), but the association between physical frailty and worsening prognosis, including HF development, has not been documented extensively.Methods and Results: As part of the FLAGSHIP study, we enrolled 524 patients aged ≥70 years hospitalized for AMI and capable of walking at discharge. Physical frailty was assessed using the FLAGSHIP frailty score. The primary outcome was a composite outcome of all-cause death and HF rehospitalization within 2 years after discharge. The secondary outcome was all-cause death and HF rehospitalization. After adjusting for confounders, physical frailty showed a significant association with an increased risk of the composite outcome (hazard ratio [HR]=2.09, 95% confidence interval [CI]: 1.03-4.22, P=0.040). The risk of HF rehospitalization increased with physical frailty, but the association was not statistically significant (HR=2.14, 95% CI: 0.84-5.44, P=0.110). Physical frailty was not associated with an increased risk of all-cause death (HR=1.45, 95% CI: 0.49-4.26, P=0.501). CONCLUSIONS: The findings suggest that physical frailty assessment serves as a stratifying tool to identify high-risk populations for post-discharge clinical events among ambulant elderly patients with AMI.

External Validation of the Japanese Clinical Score for Mortality Prediction in Patients With Acute Heart Failure.

BACKGROUND: To predict mortality in patients with acute heart failure (AHF), we created and validated an internal clinical risk score, the KICKOFF score, which takes physical and social aspects, in addition to clinical aspects, into account. In this study, we validated the prediction model externally in a different geographic area.Methods and Results: There were 2 prospective multicenter cohorts (1,117 patients in Osaka Prefecture [KICKOFF registry]; 737 patients in Kochi Prefecture [Kochi YOSACOI study]) that had complete datasets for calculation of the KICKOFF score, which was developed by machine learning incorporating physical and social factors. The outcome measure was all-cause death over a 2-year period. Patients were separated into 3 groups: low risk (scores 0-6), moderate risk (scores 7-11), and high risk (scores 12-19). Kaplan-Meier curves clearly showed the score's propensity to predict all-cause death, which rose independently in higher-risk groups (P<0.001) in both cohorts. After 2 years, the cumulative incidence of all-cause death was similar in the KICKOFF registry and Kochi YOSACOI study for the low-risk (4.4% vs. 5.3%, respectively), moderate-risk (25.3% vs. 22.3%, respectively), and high-risk (68.1% vs. 58.5%, respectively) groups. CONCLUSIONS: The unique prediction score may be used in different geographic areas in Japan. The score may help doctors estimate the risk of AHF mortality, and provide information for decisions regarding heart failure treatment.

Clinical Characteristics and Outcomes of Heart Failure Patients With Long-Term Care Insurance　- Insights From the Kitakawachi Clinical Background and Outcome of Heart Failure Registry.

BACKGROUND: In Japan, the long-term care insurance (LTCI) system has an important role in helping elderly people, but there have been no clinical studies that have examined the relationship between the LTCI and prognosis for patients with acute heart failure (HF).Methods and Results:This registry was a prospective multicenter cohort, 1,253 patients were enrolled and 965 patients with acute HF aged ≥65 years were comprised the study group. The composite endpoint included all-cause death and hospitalization for HF after discharge. We divided the patients into 4 groups: (i) patients without LTCI, (ii) patients requiring support level 1 or 2, (iii) patients with care level 1 or 2, and (iv) patients with care levels 3-5. The Kaplan-Meier analysis identified a lower rate of the composite endpoint in group (i) than in the other groups. After adjusting for potentially confounding effects using a Cox proportional regression model, the hazard ratio (HR) of the composite endpoint increased significantly in groups (iii) and (iv) (adjusted HR, 1.62; 95% confidence interval [CI], 1.22-1.98 and adjusted HR, 1.62; 95% CI, 1.23-2.14, respectively) when compared with group (i). However, there was no significant difference between groups (i) and (ii). CONCLUSIONS: The level of LTCI was associated with a higher risk of the composite endpoint after discharge in acute HF patients.

Living Alone and Gender Differences in Rehospitalization for Heart Failure After Discharge Among Acute Heart Failure Patients.

Home treatment for heart failure (HF) is one of the most important problems in patients after discharge as a secondary preventive measure for rehospitalization for HF. However, there are no detailed studies on gender differences in sociopsychological factors such as living alone for HF rehospitalization among patients with acute HF (AHF).This prospective multicenter cohort study enrolled patients with AHF between April 2015 and August 2017. Patients of each gender with first AHF were divided into those living alone and those not living alone. The primary endpoint was defined as rehospitalization for HF after discharge. Cox proportional hazard analysis was performed to determine the association between living alone and the endpoint.Overall, 581 patients were included in this study during the 3-year follow-up. The proportion of rehospitalization for HF was significantly higher in patients living alone than in those not living alone among male patients. However, female patients showed no difference in endpoints between the two groups. The difference was independently maintained even after adjusting for differences in social backgrounds in male patients (adjusted hazard ratio (HR) 2.02; 95% confidence interval (CI), 1.07-3.70). In female patients, the HR for rehospitalization for HF showed no difference between the two groups (adjusted HR, 0.99; 95% CI, 0.56-1.69).In this study population, male patients living alone after first AHF discharge had a higher risk of rehospitalization for HF than those not living alone, but these differences were not observed in female patients.

Estimation of reduced walking speed using simple measurements of physical and psychophysiological function in community-dwelling elderly people: a cross-sectional and longitudinal study.

BACKGROUND: Early detection of reduced mobility function is important in elderly people. Usual walking speed is useful to assess mobility function, but is often not feasible in a community setting. AIMS: This study aimed to explore a simple surrogate indicator of usual walking speed in elderly people. METHODS: The participants were 516 community-dwelling elderly people. As a baseline survey, the usual walking speed and candidates of surrogate indicators including physical function and psychophysiological function were measured. After 2 years, the occurrence of mobility limitation was assessed. RESULTS: In cross-sectional analysis, a linear regression model with maximum step length, age, and sex presented the most favourable adjusted R2 of 0.426 for estimating usual walking speed. Maximum step length (MSL) also showed good predictive accuracy for usual walking speed < 0.8 m/s {area under the curve [AUC] 0.908 [95% confidence interval (CI) 0.811, 1.000]} and < 1.0 m/s [AUC 0.883 (95% CI) 0.832, 0.933)] in receiver-operating characteristic (ROC) analysis. In longitudinal analysis, the predictive accuracy of MSL for mobility limitation [AUC 0.813 (95% CI 0.752, 0.874)] was similar to that of usual walking speed [AUC 0.808 (95% CI 0.747, 0.869)] in ROC analysis. CONCLUSIONS AND DISCUSSION: The results of this study suggest that MSL may serve as a simple surrogate indicator of UWS in elderly people.

Clinical Characteristics and Social Frailty of Super-Elderly Patients With Heart Failure　- The Kitakawachi Clinical Background and Outcome of Heart Failure Registry.

BACKGROUND: Social background is important in preventing admission/readmission of heart failure (HF) patients. However, few clinical studies have been conducted to assess the social background of these patients, especially elderly patients.Methods and Results:The Kitakawachi Clinical Background and Outcome of Heart Failure (KICKOFF) Registry is a prospective multicenter community-based cohort of HF patients, established in April 2015. We compared the clinical characteristics and social background of the super-elderly group (≥85 years old) and the non-super-elderly group (<85 years old). This study included 647 patients; 11.8% of the super-elderly patients were living alone, 15.6% were living with only a partner, and of these, only 66.7% had the support of other family members. The super-elderly group had less control over their diet and drug therapies than the non-super-elderly group. Most patients in the super-elderly group were registered for long-term care insurance (77.4%); 73.5% of the super-elderly patients could walk independently before admission, but only 55.5% could walk independently at discharge, whereas 94% of the non-super-elderly patients could walk independently before admission and 89.4% could walk independently at discharge. CONCLUSIONS: The KICKOFF Registry provides unique detailed social background information of Japanese patients with HF. Super-elderly patients are at serious risk of social frailty; they need the support of other people and their ability to perform activities of daily living decline when hospitalized.

Feasibility of neuromuscular electrical stimulation immediately after cardiovascular surgery.

OBJECTIVE: To determine the safety and feasibility of neuromuscular electrical stimulation (NMES) from postoperative days (PODs) 1 to 5 after cardiovascular surgery. DESIGN: Pre-post interventional study. SETTING: Surgical intensive care unit and thoracic surgical ward of a university hospital. PARTICIPANTS: Consecutive patients (N=144) who underwent cardiovascular surgery were included. Patients with peripheral arterial disease, psychiatric disease, neuromuscular disease, and dementia were excluded. Patients with severe chronic renal failure and those who required prolonged mechanical ventilation after surgery were also excluded because of the possibility of affecting the outcome of a future controlled study. INTERVENTIONS: NMES to the lower extremities was implemented from PODs 1 to 5. MAIN OUTCOME MEASURES: Feasibility outcomes included compliance, the number of the patients who had changes in systolic blood pressure (BP) >20 mmHg or an increase in heart rate >20 beats/min during NMES, and the incidence of temporary pacemaker malfunction or postoperative cardiac arrhythmias. RESULTS: Sixty-eight of 105 eligible patients participated in this study. Sixty-one (89.7%) of them completed NMES sessions. We found no patients who had excessive changes in systolic blood pressure, increased heart rate, or pacemaker malfunction during NMES. Incidence of atrial fibrillation during the study period was 26.9% (7/26) for coronary artery bypass surgery, 18.2% (4/22) for valvular surgery, and 20.0% (4/20) for combined or aortic surgery. No sustained ventricular arrhythmia or ventricular fibrillation was observed. CONCLUSIONS: The results of this study demonstrate that NMES can be safely implemented even in patients immediately after cardiovascular surgery.

Changes in walking speed 6 months after discharge may be more sensitive to subsequent prognosis than handgrip strength in patients hospitalized for heart failure.

BACKGROUND: Despite the prognostic importance of walking speed (WS) and handgrip strength (HGS) in patients with heart failure (HF), no study has reported the prognostic impact of changes in these parameters. This study aimed to examine the association between changes after discharge and the subsequent prognosis. METHODS: This study included 881 elderly patients hospitalized for HF. WS and HGS were measured at discharge and 6 months after discharge. Based on the presence of slowness (WS <0.98 m/s) or weakness (HGS <30.0 kg for men and < 17.5 kg for women) at both points, patients were divided into four groups (WS: A = -/-, B = -/+, C = +/-, D = +/+; HGS: E = -/-, F = -/+, G = +/-, H = +/+). The study endpoint was a composite of all-cause mortality and HF rehospitalization during the 18 months after 6 months of discharge. The Cox proportional hazards model was used to assess the association between the groups and study outcomes. RESULTS: Stratified by the WS change patterns, groups B and D showed higher risk of the study outcomes than group A [B: hazard ratio 2.34, 95% confidence interval (CI) 1.29-4.28; D: 2.38, 1.67-3.39], whereas group C was not. When stratified by the HGS change in patterns, only group H was associated with a worse prognosis (HR; 1.85, 95%CI; 1.31-2.60). CONCLUSION: Changes in WS were related to HF prognosis, suggesting that changes in WS may be more sensitive to further risk stratification than changes in HGS.

Home Based Exercise Rehabilitation Programs to Prevent Physical Frailty and Hospitalization-Associated Disability.

Daily health management and exercise are important for staying healthy and avoiding the need for long-term care. However, it is not easy to maintain regular exercise. Therefore, exercise needs to be done efficiently. In recent years, due to the aging population and increasing severity of illness, older patients often experience a significant decline in physical function, even with minimal rest, which often interferes with their daily life after discharge from the hospital. Frailty not only affects ADLs, but also strongly influences prognosis, including the development of atherosclerotic disease and rehospitalization. This perspective is a summary of the 51st Metropolitan Public Lecture held on June 17, 2023, and discusses exercise-based rehabilitation programs that can be delivered at home to prevent physical frailty and avoid hospitalization-related disability.

Relationship between prehabilitation responsiveness and postoperative physical functional recovery in cardiovascular surgery.

BACKGROUND: The purpose of this study was to examine the relationship between responsiveness to prehabilitation and postoperative recovery of physical function in cardiac surgery patients. METHODS: Ninety-three cardiac surgery patients (mean age: 76.4 years) were included in this retrospective cohort study. Preoperative physical function was measured using the Short Physical Performance Battery (SPPB), and a prehabilitation exercise program was implemented for the SPPB domains with low scores. Among the patients, those whose SPPB score was over 11 from the start of prehabilitation and remained over 11 on the day before surgery were defined as the high-functioning group, and those whose SPPB score improved by 2 points or more from the start of prehabilitation and exceeded 11 points were defined as the responder group. Those whose SPPB score did not exceed 11 immediately before surgery were classified as non-responders. The characteristics of each group and postoperative recovery of physical function were investigated. RESULTS: There were no serious adverse events during prehabilitation. Mean days of prehabilitation was 5.4 days. The responder group showed faster improvement in postoperative physical function and shorter time to ambulatory independence than the non-responder group. The non-responder group had lower preoperative skeletal muscle index, more severe preoperative New York Heart Association classification, and a history of musculoskeletal disease or stroke. CONCLUSION: There were responders and non-responders to prehabilitation among cardiac surgery patients. Cardiac surgery patients who respond to prehabilitation had faster recovery of physical function. Further research is needed to determine what type of prehabilitation is more effective in postoperative recovery of physical function in cardiac surgery patients.

Prognostic impact of nutrition measures in patients with heart failure varies with coexisting physical frailty.

AIMS: Malnutrition is prevalent among patients with heart failure (HF); however, the effects of coexisting malnutrition and frailty on prognosis are unknown. This study examines the impact of malnutrition and frailty on the prognosis of patients with HF. METHODS AND RESULTS: We examined 1617 patients with HF aged 65 years or older (age: 78.6 ± 7.4; 44% female) from a Japanese multicentre prospective cohort study. The nutritional status was evaluated using the Geriatric Nutritional Risk Index (GNRI), Controlling Nutritional Status (CONUT), and Mini Nutritional Assessment Short Form on discharge. Frailty was assessed using the criteria determined in a previous study on patients with HF. The prognostic impact of each nutrition measure on the risk of composite all-cause mortality and cardiac readmissions within 2 years of hospital discharge was assessed using Kaplan-Meier survival curves and Cox proportional hazards model analysis for non-frail and frail groups. Over 2324.2 person-years of follow-up, 88 patients died and 448 patients experienced readmission due to HF. In the non-frail group, poor nutritional status assessed using the GNRI and CONUT was associated with an increased hazard ratio (HR) of composite outcomes in the crude model; however, adjustment for potential confounders diminished the association. In the frail group, all three nutritional indicators were associated with the cumulative incidence of the study outcome (log-rank test, P < 0.05). In multivariate analysis, only the CONUT score was associated with an increased HR even after adjustment for confounders. CONCLUSIONS: The CONUT score predicted a poor prognosis in HF patients with coexisting physical frailty, highlighting the potential clinical benefit of nutritional assessment based on biochemical data for further risk stratification.

Prognostic effects of cardiac rehabilitation in heart failure patients classified according to physical frailty: A propensity score-matched analysis of a nationwide prospective cohort study.

Background: Research regarding cardiac rehabilitation (CR) in the prognosis of heart failure (HF) patients and frailty remains lacking. Here, the effects of CR on the 2-year prognosis of HF patients were examined according to their frailty status. Methods: This multicenter prospective cohort study enrolled patients hospitalized for HF. Patients who underwent ≥1 session per 2 weeks of CR within 3 months after discharge were categorized in the CR group. Patients were divided in a non-frailty (≤8 points) and physical frailty group (≥9 points) based on their FLAGSHIP frailty score. The score is based on HF prognosis, with a higher score indicating worsened physical frailty. A propensity score-matched analysis was performed to compare survival rates between the two groups according to their physical frailty status. Endpoints included HF re-hospitalization and all-cause mortality during a 2-year follow-up period. Results: Of 2697 patients included in the analysis, 285 and 95 matched pairs were distributed in the non-frailty and physical frailty groups, respectively, after propensity-score matching. CR was associated with lower incidence of HF rehospitalization in both non-frailty (hazard ratio 0.65; 95% confidence interval 0.44-0.96; p = 0.032) and physical frailty (0.54; 0.32-0.90; p = 0.019) groups. CR was not associated with all-cause mortality in either group (log-rank test, p > 0.05). Conclusion: These findings suggest the effects of CR on reduced HF rehospitalization, regardless of physical frailty status.

Gap in the prognostic impact of short physical performance battery among phenotypes of heart failure.

BACKGROUND: The Short Physical Performance Battery (SPPB) has been reported to predict clinical outcomes in patients with heart failure (HF). However, whether the discriminative capacity of SPPB score for adverse outcomes varies according to the phenotypes of HF, such as HF with reduced, mid-range, and preserved left-ventricular ejection fraction (HFrEF, HFmrEF, and HFpEF) remains unclear. The aim of this study was to investigate the difference in discriminative capacity of SPPB score for predicting 2-year mortality among phenotypes of HF. METHODS: We consecutively enrolled 542 adult patients admitted for HF (HFrEF, n = 187; HFmrEF, n = 94; HFpEF, n = 261). The patients underwent SPPB score when discharged from hospital. The primary endpoint was all-cause mortality during the 2 years after hospital discharge. We assessed the discriminative capacity of SPPB score for predicting mortality by using receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 95 events (17.5%) occurred during the follow-up period. The area under the curve of ROC (95% confidence interval) was 0.80 (0.71-0.88) in HFrEF, 0.61 (0.46-0.76) in HFmrEF, and 0.70 (0.61-0.79) in HFpEF group. After adjustment for potential confounders, the hazard ratios (95% confidence interval) of the lower SPPB score were 5.38 (2.34-14.6) in HFrEF group, 1.12 (0.36-3.29) in HFmrEF group, and 3.19 (1.68-6.22) in HFpEF group. CONCLUSIONS: Prognostic value of SPPB score varies according to the HF phenotype. SPPB score predicts mortality in patients with HFrEF and HFpEF, but not in patients with HFmrEF. These findings lead to more precise risk prediction by SPPB score in patients with HF.

Clinical benefit of combined assessment of physical and psychological frailty in patients with heart failure.

OBJECTIVES: Physical frailty becomes a robust risk factor in patients with heart failure (HF) and coexistence of physical and psychological frailty is likely to be a prognostic indicator. This study aimed to analyze the prognosis of coexistence of these two factors in patients with HF. METHODS: This study was a secondary analysis of a multicenter prospective cohort study (FLAGSHIP). We analyzed data from 2502 patients with HF from the FLAGSHIP study in Japan. We divided the patients into four physical frailty categories using a frailty score ranging from 0 to 14 (<4: I, 4-8: II, 9-12: III, and 14: IV, the score 13 does not exist in calculation). The higher category indicates more severe physical frailty. Psychological frailty was defined as the presence of cognitive decline and/or depressive symptoms. The study outcome was a 2-year composite outcome of rehospitalization for HF or all-cause mortality after hospital discharge. RESULTS: During the 3734.7 person-year follow-up, 774 patients experienced the composite outcome. After adjusting for confounders, physical and psychological frailty were independently associated with adverse outcomes. Using physical frailty category I, without psychological frailty as the reference, adjusted hazard ratios for adverse outcomes were 1.29 [95% confidence interval (CI) 0.86-1.92] for category I with psychological frailty, 0.99 (95% CI 0.71-1.37) for category II without psychological frailty, 1.61 (95% CI 1.16-2.23) for category II with psychological frailty, 1.56 (95% CI 1.14-2.15) for category III without psychological frailty, 1.62 (95% CI 1.20-2.20) for category III with psychological frailty, 1.50 (95% CI 1.05-2.14) for category IV without psychological frailty, and 2.16 (95% CI 1.59-2.94) for category IV with psychological frailty, respectively. CONCLUSIONS: Combined assessment of physical and psychological frailty leads to more detailed risk stratification of patients with HF.

Prognostic Effects of Cardiac Rehabilitation in Patients With Heart Failure (from a Multicenter Prospective Cohort Study).

The prognostic effects of cardiac rehabilitation (CR) are inconsistent in recent reports on heart failure (HF). Generally, participants in previous trials were relatively young and had HF with reduced ejection fraction. Herein, we examined the effects of CR on HF prognosis using a nationwide cohort study. This multicenter prospective cohort study included hospitalized patients with acute HF or worsening chronic HF. Patients who underwent CR once or more times weekly for 6 months after discharge were included in the CR group. The main study end point was a composite of all-cause mortality and HF rehospitalization during a 2-year follow-up period. We performed propensity score matching to compare the survival rates between the CR and non-CR groups. Of the 2,876 enrolled patients, 313 underwent CR for 6 months. After propensity score matching using confounding factors, 626 patients (313 pairs) were included in the survival analysis (median age: 74 years). CR was associated with a reduced risk of composite outcomes (hazard ratio [HR] 0.66; 95% confidence interval [CI] 0.48 to 0.91; p = 0.011), all-cause mortality (HR 0.53; 95% CI 0.30 to 0.95; p = 0.032), and HF rehospitalization (HR 0.66; 95% CI 47 to 0.92; p = 0.012). Subgroup analysis showed similar CR effects in patients with HF with preserved ejection fraction (≥50%) and HF with reduced ejection fraction (<40%). In the landmark analysis, CR did not reduce the aforementioned end points beyond 6 months after discharge (log-rank test: composite outcomes, p = 0.943; all-cause mortality, p = 0.258; HF rehospitalization, p = 0.831). CR is a standard treatment for HF regardless of HF type; however, further challenges may affect the long-term prognostic effects of CR.

Association between a pre-admission limitation in walking ability and post-discharge adverse outcomes among hospitalized patients with heart failure: Report from a multicenter prospective cohort study.

BACKGROUND: Although limited walking ability at discharge is a known risk factor for adverse outcomes in older patients with heart failure (HF), the association between pre-admission limitations and adverse outcomes is unknown. Therefore, we evaluated the prevalence of a pre-admission limitation in walking ability and its relationship with post-discharge outcomes among patients with HF with reduced, mid-range, and preserved left-ventricular ejection fraction (HFrEF, HFmrEF, and HFpEF). METHODS: We followed 2042 patients aged ≥65 years (HFrEF, n = 668; HFmrEF, n = 360; HFpEF, n = 1014) from a multicenter cohort study in Japan. A limitation in walking ability was defined as the necessity of any assistance or a walking aid. Adverse outcomes were defined as the composite of HF rehospitalization and all-cause death within 2 years after discharge. RESULTS: During 2978.0 person-years of follow-up, 563 patients were rehospitalized due to HF exacerbation and 103 patients died. In HFrEF, HFmrEF, and HFpEF groups, the prevalence of a pre-admission limitation in walking ability was 12.1%, 18.6%, and 21.1%, respectively, the crude hazard ratios [95% confidence interval] of a pre-admission limitation in walking ability were 2.46 [1.79-3.39], 1.34 [0.87-2.06], and 1.94 [1.53-2.47], and the adjusted hazard ratios were 2.21 [1.58-3.16], 1.19 [0.75-1.89], and 1.39 [1.06-1.82], respectively. CONCLUSIONS: A pre-admission limitation in walking ability is a predictor of post-discharge HF rehospitalization or all-cause death among patients with HFrEF and HFpEF, but not among patients with HFmrEF. Shortly after admission, information regarding pre-admission functional limitations should be obtained to better understand the risk of post-discharge adverse outcomes.

Impact of weight loss in patients with heart failure with preserved ejection fraction: results from the FLAGSHIP study.

AIMS: Weight loss (WL) is a poor prognostic factor for patients with heart failure (HF) with reduced ejection fraction. However, its prognostic impact on patients with HF with preserved ejection fraction (HFpEF) remains unestablished. The evidence regarding the effects of obesity on the prognosis of WL is also unclear. We aimed to identify the risk factors for WL and examine the association between WL and prognosis of HFpEF in obese and non-obese patients. METHODS AND RESULTS: In this multicentre cohort study, the data of 573 patients hospitalized with HFpEF [median age: 78 years (interquartile range, 71-84 years); 49.2% female] were identified from hospital databases. WL was defined as ≥5% weight reduction within 6 months after discharge. Obesity was defined according to Japanese criteria as body mass index ≥25 kg/m2 . The main study outcomes were all-cause mortality and HF rehospitalization between 6 and 24 months after hospital discharge. Logistic regression analysis and Cox proportional hazards regression analysis were performed to identify independent the risk factors associated with WL and to calculate the hazard ratios (HRs) associated with adverse outcomes. The prevalence of obesity at discharge was 21.1%. At 6 month follow-up, WL occurred in 17.4% and 10.8% of the obese and non-obese patients, respectively. Onset of WL in non-obese patients was associated with prior hospitalization for HF [odds ratio (OR) 2.39, 95% confidence interval (CI) 1.22-4.68, P = 0.011] and high levels of brain natriuretic peptide (OR 2.32, CI 1.17-4.60, P = 0.015). In obese patients, WL was associated with the use of mineralocorticoid receptor antagonists (OR 3.26, CI 1.08-9.76, P = 0.03) and vasopressin receptor antagonists (OR 6.61, CI 2.03-21.2, P = 0.001). During 1021.3 person-years of follow-up, 31 patients died, and upon 1081.0 person-years follow-up, 84 patients required rehospitalization for HF. In proportional hazards analysis, WL was associated with all-cause mortality (HR 5.12, CI 2.08-12.5, P < 0.001) and HF rehospitalization (HR 2.63, CI 1.38-5.01, P = 0.003) after adjustment for confounders in non-obese patients, but not in obese patients. CONCLUSIONS: Weight loss should be considered as an indicator for monitoring worsening of HF condition in non-obese patients with HFpEF. WL was not associated with adverse events in obese patients with HFpEF, possibly due to appropriate fluid management during follow-up.

A clinical score to predict mortality in patients after acute heart failure from Japanese registry.

AIMS: Clinical scores that consider physical and social factors to predict long-term observations in patients after acute heart failure are limited. This study aimed to develop and validate a prediction model for patients with acute heart failure at the time of discharge. METHODS AND RESULTS: This study was retrospective analysis of the Kitakawachi Clinical Background and Outcome of Heart Failure Registry database. The registry is a prospective, multicentre cohort of patients with acute heart failure between April 2015 and August 2017. The primary outcome to be predicted was the incidence of all-cause mortality during the 3 years of follow-up period. The development cohort derived from April 2015 to July 2016 was used to build the prediction model, and the test cohort from August 2016 to August 2017 was used to evaluate the prediction model. The following potential predictors were selected by the least absolute shrinkage and selection operator method: age, sex, body mass index, activities of daily living at discharge, social background, comorbidities, biomarkers, and echocardiographic findings; a risk scoring system was developed using a logistic model to predict the outcome using a simple integer based on each variable's ß coefficient. Out of 1253 patients registered, 1117 were included in the analysis and divided into the development (n = 679) and test (n = 438) cohorts. The outcomes were 246 (36.2%) in the development cohort and 143 (32.6%) in the test cohort. Eleven variables including physical and social factors were set into the logistic regression model, and the risk scoring system was created. The patients were divided into three groups: low risk (score 0-5), moderate risk (score 6-11), and high risk (score ≥12). The observed and predicted mortality rates were described by the Kaplan-Meier curve divided by risk group and independently increased (P < 0.001). In the test cohort, the C statistic of the prediction model was 0.778 (95% confidence interval: 0.732-0.824), and the mean predicted probabilities in the groups were low, 6.9% (95% confidence interval: 3.8-10%); moderate, 30.1% (95% confidence interval: 25.4%-34.8%); and high, 79.2% (95% confidence interval: 72.6%-85.8%). The predicted probability was well calibrated to the observed outcomes in both cohorts. CONCLUSIONS: The Kitakawachi Clinical Background and Outcome of Heart Failure score was helpful in predicting adverse events in patients with acute heart failure over a long-term period. We should evaluate the physical and social functions of such patients before discharge to prevent adverse outcomes.

Impact of home- and community-based services in the long-term care insurance system on outcomes of patients with acute heart failure: Insights from the Kitakawachi Clinical Background and Outcome of Heart Failure Registry.

AIM: In Japan, the long-term care insurance (LTCI) system is important for elderly people living at home; however, no clinical studies have revealed a relationship between home- or community-based services and outcomes in patients with acute heart failure (AHF). METHODS: This was a prospective multicenter cohort study of patients with AHF enrolled between April 2015 and August 2017. Patients aged ≥65 years with LTCI were divided into those receiving home- and community-based services (service users) and without home and community-based services (service non-users). The endpoint was defined as a composite endpoint, which included all-cause mortality and hospitalization for heart failure after discharge. Subgroup analyses were performed for elderly patients (<85 years) or super-elderly patients (≥85 years). RESULTS: The study participants were eligible for LTCI two times more than community-dwelling people were. At the 1-year follow-up period, the rate of the composite endpoint showed no significant difference between service users and service non-users among all patients or super-elderly patients. However, in elderly patients, the rate of the composite endpoint was significantly lower among service users than service non-users. The difference was independently maintained even after adjustments for differences in comorbidities or in social backgrounds (adjusted hazard ratio 0.62; 95% confidence interval 0.38-0.99, and adjusted hazard ratio 0.57; 95% confidence interval 0.35-0.90, respectively). CONCLUSIONS: In this study, adverse events following discharge of patients with AHF who used home- and community-based services were prevented only in elderly patients, not in super-elderly patients. Geriatr Gerontol Int 2020; 20: 967-973.

Maximal calf circumference reflects calf muscle mass measured using magnetic resonance imaging.

BACKGROUND: Calf circumference (CC) has been used as a surrogate for calf muscle mass, which facilitates venous blood return to the heart through active skeletal muscle. However, the correlation between CC and calf muscle mass has not been extensively examined. This study aimed to examine the relationship between CC and calf muscle mass considering differences in sex and physique in elderly individuals. METHODS: A total of 124 community-dwelling elderly individuals ≥60 years of age (61 men, mean [±SD] age 74.3 ± 5.7 years) were enrolled. Maximal CC was measured using a tape measure with the subject supine. The cross-sectional area of skeletal muscle tissues was measured using magnetic resonance imaging from the point of greatest calf circumference to 5 cm proximal and distal. Calf muscle mass was calculated by multiplying the area of each slice by slice thickness (5 mm). RESULTS: CC was strongly correlated with calf muscle mass in male and female subjects (male: r = 0.908, P < 0.001; female: r = 0.892, P < 0.001). Multiple regression analysis revealed that CC and body mass index (BMI) were independent associate factors of calf muscle mass. The following estimation formulae were derived: (male) calf muscle mass (cm3) = 47.82 × CC (cm)-12.50 × BMI (kg/m2) -732.80; (female) calf muscle mass (cm3) = 32.23 × CC (cm) -4.85 × BMI (kg/m2) -429.94. CONCLUSIONS: A strong correlation was found between CC and calf muscle mass according to magnetic resonance imaging. Sex differences and BMI should be considered for accurate estimation of calf muscle mass using CC.