Prognostic Value of Handgrip Strength in Older Patients With Heart Failure: A Post Hoc Analysis of FRAGILE‐HF

Abstract

Background

The prognostic value of handgrip strength, a simple and reliable indicator of sarcopenia, in older patients with heart failure remains uncertain. This study aimed to investigate the prognostic value of handgrip strength in hospitalized patients aged ≥65 years with heart failure.

Methods

This post hoc analysis used data from FRAGILE‐HF (Prevalence and Prognostic Value of Physical and Social Frailty in Geriatric Patients Hospitalized for Heart Failure), a prospective, multicenter cohort study involving patients aged ≥65 years hospitalized for heart failure. Handgrip strength was measured before discharge using a dynamometer, with the higher value from 2 trials recorded. Measurements were standardized by dividing 28 and 18 kg for men and women, respectively, per 2019 Asian Working Group for Sarcopenia criteria. Patients were categorized into tertiles (tertile 1, highest; tertile 2, middle; and tertile 3, lowest). The primary outcome was 2‐year all‐cause death.

Results

Among 1269 patients (median age, 81 years; 57.1% men), 275 died during follow‐up. Kaplan–Meier analysis revealed a stepwise increase in death across the lowest handgrip tertiles, which remained significant after multivariable adjustment (tertile 2 versus tertile 1: hazard ratio [HR], 1.64 [95% CI, 1.14–2.37]; P=0.007; tertile 3 versus tertile 1: HR, 2.03 [95% CI, 1.42–2.90]; P<0.001). The analysis using a linear model showed that the prognostic impact of reduced handgrip strength increased with age.

Conclusions

Lower handgrip strength was independently associated with death in older patients with heart failure, with stronger associations observed in the oldest patients. These findings highlight the additional prognostic value of handgrip strength beyond conventional risk factors.

Registration

URL: center6.umin.ac.jp; Unique Identifier: UMIN000023929.

Nonstandard Abbreviations and Acronyms

FRAGILE‐HF

Prevalence and Prognostic Value of Physical and Social Frailty in Geriatric Patients Hospitalized for Heart Failure

MAGGIC

Meta‐Analysis Global Group in Chronic Heart Failure

UMIN‐CTR

University Hospital Information Network–Clinical Trials Registry

Clinical Perspective.

What Is New?

• Lower handgrip strength, a simple marker of sarcopenia, is independently associated with a higher 2‐year mortality rate in older patients with heart failure, with the association being strongest in the oldest patients.

What Are the Clinical Implications?

• Because handgrip strength is quick, inexpensive, and noninvasive to measure, it provides a practical tool for risk stratification in this population.

• Incorporating handgrip strength assessment may enable earlier, targeted multidisciplinary management (eg, cardiac rehabilitation and nutritional support) for patients identified as higher risk.

The global burden of heart failure continues to rise, driven by an aging population and the increasing prevalence of lifestyle‐related diseases. ¹ , ² This condition not only increases mortality and hospitalization rates but also significantly reduces the quality of life of affected individuals. ³ Effective management of heart failure requires a comprehensive understanding of factors contributing to its progression and prognosis. One such factor is sarcopenia, or muscle failure, characterized by a progressive decline in muscle strength, mass, and function. Sarcopenia is associated with reduced physical capability, higher risk of disability and falls, and an increased mortality rate. ⁴ , ⁵ Among various methods for evaluating muscle weakness, handgrip strength has emerged as the most widely adopted in clinical practice and a key diagnostic criterion for sarcopenia. ⁶

Although handgrip strength is recognized for its simplicity and reliability, studies on its prognostic value in patients with heart failure have yielded conflicting results. This discrepancy may be attributable to relatively small sample sizes and variations in patient age across studies. ⁷ , ⁸ , ⁹ Indeed, most studies have primarily focused on younger populations, despite older adults constituting the majority of patients with heart failure. This is particularly relevant, considering that aging is associated with a decline in muscle strength. ¹⁰ , ¹¹ Few studies have evaluated whether low handgrip strength remains associated with poor prognosis in older patients with heart failure. Recent systematic reviews and meta‐analyses have reported inconsistent findings on the prognostic value of handgrip strength in patients with heart failure. A meta‐analysis by Xiao et al demonstrated that reduced handgrip strength was associated with increased mortality and rehospitalization risk, regardless of study design, patient age, or follow‐up duration. ¹² Conversely, a review by Galli et al concluded that handgrip strength alone was not a significant predictor of all‐cause death. ¹³ These conflicting findings highlight ongoing uncertainty and the need for further research, particularly in older adults, who are underrepresented in prior studies. To address this gap, the present study aimed to examine the relationship between handgrip strength and prognosis in older patients with heart failure and to explore whether its prognostic value varies with age.

Methods

Data Availability Statement

Data are not available due to ethical restrictions.

Study Design and Patient Population

This study was a post hoc analysis of the FRAGILE‐HF (Prevalence and Prognostic Value of Physical and Social Frailty in Geriatric Patients Hospitalized for Heart Failure) study. This prospective multicenter cohort study investigated the prevalence and prognostic impact of multiple frailty domains. Details of the study and primary results have been published in previous studies. ¹⁴ , ¹⁵ Briefly, consecutive patients aged ≥65 years with heart failure who were admitted to 15 hospitals in Japan between September 2016 and March 2018 were included in the study. Heart failure decompensation was diagnosed according to the Framingham criteria. ¹⁶ Patients (1) with a history of heart transplantation or current use of a left ventricular assist device, (2) who underwent either chronic peritoneal dialysis or hemodialysis, (3) who developed acute myocarditis, (4) with missing data on BNP (brain natriuretic peptide) or NT‐proBNP (N‐terminal pro‐brain natriuretic peptide) levels at admission, and (5) with a BNP level of <100 pg/mL or an NT‐proBNP level of <300 pg/mL at admission were excluded. In the primary analysis, patients with missing data on handgrip strength were excluded. Oral medications prescribed at the time of discharge were recorded. Baseline physical examinations, blood tests, and echocardiography were performed with the patient in a stable condition before discharge. The study adhered to the principles of the Declaration of Helsinki and the Japanese Ethical Guidelines for Medical and Health Research Involving Human Subjects. As an observational study without the involvement of invasive procedures or interventions, written informed consent was not required according to the Ethical Guidelines for Medical and Health Research Involving Human Subjects issued by the Japanese Ministry of Health, Labor, and Welfare. All participants were allowed to withdraw from the study at any time. Additionally, study data, including study objectives, inclusion and exclusion criteria, and names of participating institutions, were posted on the UMIN‐CTR (University Hospital Information Network–Clinical Trials Registry; unique identifier: UMIN000023929) before the commencement of patient enrollment.

Measurement and Standardization of Handgrip Strength

Before discharge, handgrip strength was measured using a dynamometer (TKK 5101 Grip‐D; Takei, Tokyo, Japan). Participants were seated on a chair with their elbow joint flexed at 90 degrees and performed the test alternatively with their right and left hands. The higher value (kg) from 2 trials on each hand was recorded, and the higher of the 2 hands was used for analysis. Handgrip strength was standardized by dividing the recorded value by 28 kg for men and 18 kg for women, based on the cutoff values for low muscle strength defined by the 2019 Asian Working Group for Sarcopenia criteria. ⁶ For example, if a male patient had a maximum handgrip strength of 21 kg, the standardized value would be 21÷28=0.75. This standardized value represented the ratio of the patient’s grip strength relative to the sex‐specific cutoff, providing a relative measure of muscle strength. All patients were categorized into tertiles based on these standardized values, representing highest (tertile 1), middle (tertile 2), and lowest (tertile 3) relative handgrip strength. In addition, we defined “reduced handgrip strength” as a binary variable, using the standardized value: patients with a ratio <1.0 were classified as having reduced handgrip strength, while those with a ratio ≥1.0 were considered to have nonreduced handgrip strength.

Follow‐Up and Study Outcomes

The final follow‐up date was set at March 31, 2020, allowing for a complete 2‐year follow‐up after the last patient’s discharge. The primary end point was 2‐year all‐cause death. Vital status was prospectively tracked through regular outpatient visits or, when unavailable, through telephone follow‐up to ensure comprehensive mortality data collection.

Statistical Analysis

Continuous variables are presented as medians with interquartile ranges, and categorical variables are expressed as counts and percentages. Where necessary, variables were log‐transformed for subsequent analysis. Baseline characteristics of patients were compared using the Mann–Whitney U and χ² tests for continuous and categorical variables, respectively. Kaplan–Meier survival curves were generated to evaluate all‐cause death, and differences in mortality rates between the groups were analyzed for statistical significance using log‐rank tests. Cox regression analysis was performed to determine the hazard ratios (HRs) and 95% CIs for assessing the prognostic significance of handgrip strength for the primary outcome. The factors used in the adjusted Cox proportional hazards model for the 2‐year mortality rate included the Meta‐Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score and log‐transformed BNP levels. ¹⁷ The MAGGIC risk score is a composite score derived from 13 clinical variables: age, lower ejection fraction, New York Heart Association class, serum creatinine, diabetes, not prescribed a beta blocker, lower systolic blood pressure, lower body mass, time since diagnosis, current smoker, chronic obstructive pulmonary disease, male sex, and not prescribed an angiotensin‐converting enzyme inhibitor or angiotensin‐receptor blocker. ¹⁷ The discrimination and calibration of this risk score have been well validated in Japanese patients with heart failure. ¹⁸ , ¹⁹ Because sex is a component of the MAGGIC risk score, it was indirectly adjusted for in the main analysis. In addition, we performed sex‐stratified Cox regression analyses to explore potential sex‐specific differences in the prognostic value of handgrip strength. The proportional hazards assumption for the Cox regression model was assessed through visual inspection of Schoenfeld residual plots. To assess how the prognostic significance of reduced handgrip strength varies with age, we constructed a linear model and restricted cubic spline models with 3, 4, and 5 knots and compared them with the Akaike information criterion. Interaction terms and their P values were calculated to evaluate whether the association between reduced handgrip strength and the 2‐year mortality rate was significantly influenced by age. Specifically, the interaction between age and reduced handgrip strength was incorporated into the Cox proportional hazards model, enabling the estimation of age‐specific HRs for reduced handgrip strength. The predicted HRs with 95% CIs were extracted from the model and plotted as a function of age. To illustrate the differential impact of reduced handgrip strength across different ages, HRs comparing reduced with nonreduced handgrip strength were derived from the interaction terms. These estimated HRs were then plotted against age, with CIs calculated to assess the precision of the estimates. To further evaluate the added prognostic value of reduced handgrip strength, we constructed 3 logistic regression models: (1) the baseline model (MAGGIC risk score plus log‐transformed BNP), (2) baseline model plus reduced handgrip strength (model 2), and (3) baseline model plus reduced handgrip strength and an age interaction term (model 3). Model discrimination was evaluated using the area under the curve of the receiver operating characteristic curve, and pairwise comparisons of areas under the curve were conducted using DeLong’s test. Additionally, continuous net reclassification improvement and integrated discrimination improvement were calculated to assess improvements in model performance. ²⁰ , ²¹ A 2‐tailed P value of <0.05 was considered significant. All analyses were conducted as a complete case analysis and performed using R Studio statistical software version 4.4.2 (R Foundation for Statistical Computing, Vienna, Austria).

Results

A total of 1332 patients were included in the FRAGILE‐HF study. Of these, 1290 patients with complete data on handgrip strength were evaluated, with a median age of 81 years, and 57.1% were men. According to handgrip strength, patients were divided into tertile 1 (highest, 430), tertile 2 (middle, 430), and tertile 3 (lowest, 430) groups. Clinical characteristics of patients at discharge are presented in Table 1. The tertile 2 and tertile 3 groups had older age, a higher proportion of men, a lower body mass index, and reduced left ventricular ejection fraction. In addition, the tertile 2 and tertile 3 groups exhibited lower hemoglobin levels but higher blood urea nitrogen and BNP levels.

Table 1.

Baseline Characteristics of All Enrolled Patients

Variables	Tertile 1 (highest)	Tertile 2 (middle)	Tertile 3 (lowest)	P value	Missing rate, %
	N=430	N=430	N=430
Standardized handgrip strength, ratio	1.10 (1.01‐1.20)	0.83 (0.78–0.87)	0.58 (0.50‐0.67)	<0.001
Age, y	76 (71–82)	81 (76–86)	84 (79–89)	<0.001	0.0
Male sex	272 (63.3)	256 (59.5)	209 (48.6)	<0.001	0.0
NYHA class III/IV	50 (11.6)	61 (14.2)	77 (17.9)	0.032	0.0
Body mass index, kg/m2	22.0 (19.9–24.4)	20.9 (19.1–23.2)	19.9 (17.7–22.6)	<0.001	0.4
Systolic blood pressure, mm Hg	112.0 (103.0–126.0)	112.0 (100.3–124.0)	112.0 (102.0–124.0)	0.715	0.0
Diastolic blood pressure, mm Hg	62.0 (58.0–68.0)	61.0 (54.0–69.0)	60.0 (53.3, 68.0)	0.002	0.0
Heart rate, bpm	69.0 (61.0–80.0)	70.0 (60.0–79.0)	70.0 (61.0–80.0)	0.590	0.0
LVEF, %	41.0 (30.0–57.0)	46.0 (33.0–61.0)	48.5 (34.0–63.0)	<0.001	1.1
History of heart failure				0.013	0.2
De novo	221 (51.4)	187 (43.7)	174 (40.5)
<1.5 y	62 (14.5)	71 (16.6)	64 (14.9)
≥1.5 y	147 (34.3)	170 (39.6)	192 (44.7)
Comorbidities
Atrial fibrillation	210 (48.8)	194 (45.1)	171 (39.8)	0.027	0.0
Coronary artery disease	142 (33.0)	149 (34.7)	162 (37.7)	0.349	0.0
COPD	50 (11.6)	51 (11.9)	39 (9.1)	0.345	0.0
Diabetes	157 (36.5)	151 (35.1)	149 (34.7)	0.838	0.0
Hypertension	293 (68.1)	305 (70.9)	321 (74.7)	0.106	0.0
Prescription at discharge
Loop diuretic	220 (51.2)	237 (55.1)	258 (60.0)	0.033	0.0
Beta blocker	340 (79.1)	318 (74.0)	284 (66.0)	<0.001	0.0
ACE‐I/ARB	299 (69.5)	293 (68.1)	280 (65.1)	0.367	0.0
MRA	35 (8.1)	33 (7.7)	36 (8.4)	0.929	0.0
Laboratory data at discharge
Hemoglobin, g/dL	12.4 (11.0–14.0)	11.6 (10.3–13.0)	11.1 (9.9–12.5)	<0.001	0.2
Creatinine, mg/dL	1.15 (0.94–1.51)	1.17 (0.90–1.62)	1.15 (0.91–1.62)	0.803	0.2
Blood urea nitrogen, mg/dL	24.3 (19.0–33.8)	25.1 (19.0–36.0)	28.2 (20.9–38.0)	<0.001	0.2
Serum sodium, mmol/L	139.0 (137.0–141.0)	139.0 (137.0–141.0)	139.0 (137.0–141.0)	0.840	0.2
BNP, pg/mL	221.7 (115.3–436.0)	289.3 (150.4–504.9)	330.1 (166.4–581.4)	<0.001	13.2

Values are expressed as the median (interquartile range) and n (%). ACE‐I indicates angiotensin‐converting enzyme inhibitor; ARB, angiotensin receptor blocker; BNP, brain natriuretic peptide; COPD, chronic obstructive pulmonary disease; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonist; and NYHA, New York Heart Association.

Among the 1290 patients with available data on handgrip evaluated at baseline, 21 were lost to follow‐up, leaving 1269 patients for the outcome analysis. During the 2‐year follow‐up after discharge, 275 patients died. Kaplan–Meier curves (based on these 1269 patients) demonstrated that the mortality rate was higher in the lower‐tertile groups (log‐rank P<0.001; Figure 1). To investigate the association between handgrip strength and cardiovascular death, we reclassified the cause of death into cardiovascular death, including heart failure death, and noncardiovascular death on the basis of definitions described previously. ²² , ²³ Among 1094 patients with complete follow‐up, 127 (11.6%) died from cardiovascular causes. As shown in Figure S1, patients with lower handgrip strength had a significantly higher cardiovascular mortality rate (log‐rank P<0.001). The proportional hazards assumption for the Cox model was assessed and confirmed to be generally satisfied. Adjusted Cox proportional hazard analysis revealed that the 2‐year all‐cause mortality rate was significantly higher in tertile 2 and tertile 3 groups, even after adjustment for the MAGGIC risk score and log‐transformed BNP levels (tertile 2 versus tertile 1: HR, 1.64 [95% CI,1.14–2.37]; P=0.007; tertile 3 versus tertile 1: HR, 2.03 [95% CI, 1.42–2.90]; P<0.001; Table 2). Furthermore, when stratified by sex, with handgrip strength analyzed as a continuous variable, handgrip strength was associated with a 2‐year mortality rate in unadjusted and adjusted models (Table 2).

Figure 1. Kaplan–Meier curves of the primary end point.

The Kaplan–Meier curves illustrate the event‐free survival rates relative to the primary end point. The analysis revealed a significant stepwise increase in mortality rates in the tertile 2 and tertile 3 groups compared with the tertile 1 group.

Table 2.

Cox Proportional Hazards Analysis of Handgrip Strength as the Primary Outcome

	Unadjusted model			Adjusted model*
	HR	95% CI	P value	HR	95% CI	P value
Tertile 1 (highest)	1.00	Reference		1.00	Reference
Tertile 2 (middle)	1.88	1.34–2.62	<0.001	1.64	1.14–2.37	0.007
Tertile 3 (lowest)	2.56	1.85–3.53	<0.001	2.03	1.42–2.90	<0.001

Men	Unadjusted model			Adjusted model*
	HR	95% CI	P value	HR	95% CI	P value
Handgrip strength	0.94	0.92–0.97	<0.001	0.97	0.95–1.00	0.027

Women	Unadjusted model			Adjusted model*
	HR	95% CI	P value	HR	95% CI	P value
Handgrip strength	0.94	0.90–0.98	0.007	0.95	0.90–1.00	0.040

HR indicates hazard ratio.

^*Adjusted for the Meta‐Analysis Global Group in Chronic Heart Failure risk score and log‐transformed brain natriuretic peptide.

Figure 2 shows the association between reduced handgrip strength, as defined by the Asian Working Group for Sarcopenia criteria, and poor prognosis. We compared the model fit using linear model and restricted cubic spline terms for age and found that the linear model provided the best fit according to the lowest Akaike information criterion. This association became statistically stronger with advancing age. A significant interaction was observed between the prognostic impact of handgrip strength and age, even after adjustment for confounders in the model (P for interaction=0.043). The results demonstrated that the impact of reduced handgrip strength on all‐cause death increased with advancing age, indicating a stronger association in older age groups. In terms of prognostic capabilities, the addition of reduced handgrip strength and its interaction with age demonstrated a significant improvement in risk reclassification compared with the baseline model incorporating the MAGGIC risk score and log‐transformed BNP (net reclassification improvement, 0.236 [95% CI, 0.102–0.369]; P<0.001). Although no significant difference in area under the curve was observed between models, the model including the interaction between handgrip strength and age showed superior risk reclassification compared with the model with handgrip strength alone (net reclassification improvement, 0.208 [95% CI, 0.065–0.352]; P=0.004; area under the receiver operating characteristic curve of 0.709 for the model including the handgrip strength–age interaction versus 0.708 for the model with handgrip strength alone; P=0.856; Table 3).

Figure 2. Association between reduced handgrip strength and 2‐year mortality rate.

The analysis demonstrated that the prognostic impact of reduced handgrip strength increased with advancing age.

Table 3.

Comparisons of Prognostic Models for Predicting the 2‐Year Mortality Rate

Models		Updated models
		Model 2	Model 3
Baseline models	Baseline model* AUC: 0.703, 95% CI: 0.665–0.741	AUC comparison: P=0.300	AUC comparison: P=0.385
		NRI: 0.282 (95% CI, 0.169–0.395); P<0.001	NRI: 0.236 (95% CI, 0.102–0.369); P<0.001
	Baseline model plus handgrip strength (Model 2) AUC: 0.708, 95% CI: 0.671–0.745		AUC comparison: P=0.856
			NRI: 0.208 (95% CI, 0.065–0.352); P=0.004
	Base model plus handgrip strength × age (Model 3) AUC: 0.709 (95% CI, 0.671–0.746)

AUC indicates area under the curve; and NRI, net reclassification improvement.

^*Baseline model (model 1) comprises the Meta‐Analysis Global Group in Chronic Heart Failure risk score and log‐transformed brain natriuretic peptide.

Discussion

This retrospective analysis of data from the FRAGILE‐HF registry, which included hospitalized older patients with heart failure, investigated the prognostic value of handgrip strength in this population. The main findings of the study are as follows. (1) A decline in handgrip strength provided incremental prognostic value to the validated risk model, including known risk factors; and (2) the prognostic value of handgrip strength varied across the older population. Notably, reduced handgrip strength was associated with a poor prognosis, and this association became more pronounced with advancing age.

Handgrip strength has long been recognized as a crucial indicator of health and is included in most definitions of sarcopenia. ²⁴ , ²⁵ Although handgrip strength primarily reflects upper‐body muscle strength, studies have suggested a reasonable correlation between handgrip strength, total‐body muscle strength, and lower‐limb muscle strength. Low handgrip strength has been established as a significant predictor of adverse outcomes, including all‐cause death, cardiovascular death, and cardiovascular disease. ²⁶ These associations were prominently demonstrated in the 2015 Prospective Urban Rural Epidemiology study. ²⁷ , ²⁸ By contrast, some studies have reported inconsistent associations between handgrip strength and prognosis in heart failure. For example, a study involving 546 Mexican patients with chronic heart failure found that a low handgrip strength index alone did not independently predict death in either men or women. ²⁹ Similarly, a retrospective cohort study of 603 older patients with acute heart failure found no association between handgrip strength and all‐cause death. However, other components of the frailty score were linked to death. ³⁰ These discrepancies may be attributed to the relatively small sample sizes and differences in patient age groups across studies. By contrast, our study analyzed a larger, prospectively collected registry data set comprising >1000 older patients with heart failure. This comprehensive approach yielded robust and reliable results, demonstrating a significant association between handgrip strength and adverse outcomes in this population. A recent study by Maeda et al using the FRAGILE‐HF cohort demonstrated that a higher Ishii score, which incorporates handgrip strength, age, calf circumference, and sex, was associated with a worse prognosis in older patients hospitalized with heart failure. ³¹ While their study highlighted the prognostic value of a composite sarcopenia screening tool, it did not isolate the contribution of individual components, particularly handgrip strength, to mortality risk. In contrast, we specifically evaluated standardized handgrip strength as an independent and continuous variable, allowing a more nuanced assessment of its prognostic impact. Furthermore, our analysis revealed that the prognostic value of reduced handgrip strength was more pronounced with increasing age, a relationship not explored in the previous study. These findings build upon and extend prior work by demonstrating the age‐dependent prognostic relevance of handgrip strength alone, independent of other sarcopenia‐related measures. Several previous studies have demonstrated that age influences the prognostic significance of physiological markers. For example, although weight loss is typically associated with an increased risk of cancer and cardiovascular death, its prognostic impact varies across age groups. ³² Similarly, a lower body mass index is more strongly associated with cancer death in older individuals than in younger individuals. ³³ In the present study, lower handgrip strength, assessed using the 2019 Asian Working Group for Sarcopenia cutoff values, was identified as a stronger prognostic indicator. These findings align with the results of previous studies and have clinical implications.

Several potential biological mechanisms may underlie the observed association between reduced handgrip strength and adverse outcomes in patients with heart failure. Severe heart failure is known to promote systemic inflammation and oxidative stress, both of which contribute to muscle atrophy and impaired physical function. ³⁴ , ³⁵ Moreover, patients with heart failure often experience a cumulative burden of multimorbidity, which can complicate disease management, reduce physical activity levels, and exacerbate medication‐related side effects, ultimately resulting in diminished exercise tolerance and muscle weakness. ³⁶ , ³⁷ These interconnected factors may partially explain the link between reduced muscle strength and poorer survival in this population.

Handgrip strength is a simple and effective method for assessing muscle strength. ³⁸ It is quick and easy to measure, making it an easily accessible tool that can be conveniently performed even in busy outpatient settings. Furthermore, exercise interventions and cardiac rehabilitation, such as resistance training, have been proven to prevent physical decline in older adults. ³⁹ , ⁴⁰ As this study highlights, the early detection of muscle weakness through handgrip strength assessment offers significant potential to facilitate timely and targeted therapeutic interventions, especially in older patients with heart failure.

Study Limitations

The present study has some limitations. First, as a post hoc analysis of data from a prospective observational cohort study, it is subject to inherent limitations. Although adjustments were made for covariates, the potential impact of unexamined confounding factors, such as musculoskeletal conditions that may affect handgrip strength, cannot be completely ruled out. Second, handgrip strength was assessed only once during the initial admission period, precluding the ability to monitor patient condition changes over time. Third, excluding patients with missing handgrip strength data may have introduced selection bias, potentially influencing the study results. Finally, this cohort study was limited to older Japanese patients with heart failure, which may restrict the generalizability of the findings to other populations. Further research involving diverse populations, such as those in Western countries, is warranted to validate these results.

Conclusions

Lower handgrip strength was associated with adverse postdischarge outcomes in older patients with heart failure, providing additional prognostic value beyond conventional, well‐validated risk factors. This association was particularly pronounced in older patients, irrespective of these traditional risk factors.

Sources of Funding

This work was supported by Novartis Pharma Research Grants, a Japan Heart Foundation Research Grant, and the Japan Society for the Promotion of Science Kakenhi (22K16147). This work was partially supported by AMED under Grant Number 25ek0109755s2702.

Disclosures

Dr Kagiyama is affiliated with a department funded by Paramount Bed Co., Ltd, based on collaborative research agreements, and received honoraria from Novartis Japan; Otsuka Pharmaceutical Co., Ltd; Nippon Boehringer Ingelheim Co., Ltd; and Eli Lilly Japan; and research grants from AstraZeneca, AMI Inc., and EchoNous. Dr Kamiya received funding outside the submitted work from Eiken Chemical Co., Ltd and SoftBank Corp. Dr Kasai is affiliated with a department sponsored by Philips Unk Onics, ResMed, Teijin Home Healthcare, and Fukuda Denshi. Dr Matsue received honoraria from Otsuka Pharmaceutical Co.; EN Otsuka Pharmaceutical Co., Ltd.; Novartis Pharma K.K.; Bayer Inc.; and AstraZeneca, and a collaborative research grant from Pfizer Japan Inc.; Otsuka Pharmaceutical Co.; EN Otsuka Pharmaceutical Co., Ltd.; Nippon Boehringer Ingelheim Co., Ltd.; Roche Diagnostics International Ltd.; and Roche Diagnostics K.K. The remaining authors have no disclosures to report.

Supporting information

Figure S1