A Step Forward in the Assessment of Handgrip Strength in Heart FailureKeywords
Hand Strength; Reference Values; Heart Failure; Systolic Heart Failure; Diastolic Heart Failure
Palavras-chave
Força da Mão; Valores de Referência; Insuficiência Cardíaca; Insuficiência Cardíaca Sistólica; Insuficiência Cardíaca Diastólica
Keywords
Hand Strength; Reference Values; Heart Failure; Systolic Heart Failure; Diastolic Heart Failure
Palavras-chave
Força da Mão; Valores de Referência; Insuficiência Cardíaca; Insuficiência Cardíaca Sistólica; Insuficiência Cardíaca Diastólica
Heart failure (HF) affects millions of people worldwide, causing significant morbidity and mortality. Functional capacity, a critical determinant of prognosis and quality of life, is often impaired in HF patients due to muscle weakness and frailty, affecting up to 40% of this population.1,2 The manuscript Handgrip Strength in Heart Failure: Establishing a Reference Equation presents a pioneering effort by developing a validated reference equation to predict handgrip strength (HGS) in HF patients, addressing gaps in clinical assessment tools tailored to this group.3 This mini-editorial evaluates the contributions, strengths, limitations, and implications of this study for clinical practice.
Significance of Handgrip Strength in HF
HGS is a simple, non-invasive measure of muscle strength, correlating with physical condition and considered a prognostic marker in HF.4,5 A systematic review of 7,350 HF patients revealed that a 1 kg reduction in HGS increases mortality risk by 8% (RR 1.08, 95% CI 1.05–1.11).5 Unlike complex measures, such as cardiopulmonary exercise testing, HGS is low-cost, accessible, and feasible in all clinical settings, making it a straightforward tool to assess frailty and guide rehabilitation.6,7 However, existing HGS reference equations are mainly derived from healthy populations, failing to account for HF-specific factors, such as reduced cardiac output (CO) and muscle atrophy, leading to inaccurate conclusions.8 The manuscript's development of an HF-specific HGS equation represents a timely advance.
Strengths of the study
The cross-sectional study involving 274 patients (18–79 years) with stable HF (174 in the derivation arm and 100 in the validation arm) was adequate for establishing a reference equation.3 The authors employed rigorous methodology, using a dynamometer with standardized protocols to ensure reliable HGS measurements (e.g., three maximum contractions with the dominant hand).9 The multivariate regression model, incorporating age, sex, height, calf circumference, and New York Heart Association (NYHA) functional class, explains 57% of HGS variance (R²=0.578), with good predictive agreement (ICC=0.79, 95% CI 0.69–0.86) in the validation cohort.3 These variables align with known determinants of muscle strength: age and sex reflect neuromuscular decline and gender diferences,10 height correlates with bone and muscle mass,11 calf circumference may indicate lean body mass, and NYHA functional class reflects HF severity. The equation's slight underestimation (mean residual: 0.68±8.93 kg) is comparable to residuals in studies of healthy populations, suggesting acceptable accuracy.
Limitations and considerations
Despite its strengths, the study has limitations. The convenience sample from a single Brazilian public hospital may limit generalizability due to ethnic, socioeconomic, and healthcare access differences that can affect HGS. The absence of longitudinal data restricts insights into HGS changes over time or its prognostic utility in decompensated HF.3 The equation's reliance on calf circumference, while relevant, may be less practical in settings without trained anthropometrics, and the subjectivity of the NYHA functional class may introduce variability.12 External validation in diverse HF populations (different ethnicities and HF etiologies) is needed to confirm its practical applicability definitively.3 Compared to healthy population equations (e.g., Novaes et al., R²=0.677 for the dominant hand),13 the lower R² of the HF equation suggests unmeasured factors (nutritional status, exercise capacity, etc.) may influence HGS in HF.
Clinical and educational implications
This equation provides clinicians with a practical tool to assess HGS in HF patients, enabling the identification of frailty and muscle weakness for personalized interventions, such as physical training.14 The equation underscores the importance of condition-specific tools, enhancing understanding of HF's impact on physical condition and complementing discussions on HF management by highlighting the role of functional assessment in prognosis.15
Future directions
Future studies should validate the equation in diverse populations and explore its prognostic value in longitudinal settings. Incorporating additional variables (nutritional status, ejection fraction, etc.) may improve predictive value. Integrating HGS into routine HF assessments, alongside tools like the 6-minute walk test, could enhance cardiovascular risk stratification and personalize care.5
Conclusion
The proposed HGS reference equation for HF patients represents a significant step toward personalized functional assessment. Despite its limitations, the study's methodology and clinical relevance make it a simple and valuable tool for clinicians and educators. As HF management evolves, this equation can guide frailty screening and rehabilitation, ultimately improving patients’ functional outcomes.
References
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1 Fuentes-Abolafio IJ, Stubbs B, Pérez-Belmonte LM, Bernal-López MR, Gómez-Huelgas R, Cuesta-Vargas AI. Physical Functional Performance and Prognosis in Patients with Heart Failure: A Systematic Review and Meta-Analysis. BMC Cardiovasc Disord. 2020;20(1):512. doi: 10.1186/s12872-020-01725-5.
» https://doi.org/10.1186/s12872-020-01725-5 -
2 Marengoni A, Zucchelli A, Vetrano DL, Aloisi G, Brandi V, Ciutan M, et al. Heart Failure, Frailty, and Pre-Frailty: A Systematic Review and Meta-Analysis of Observational Studies. Int J Cardiol. 2020;316:161-71. doi: 10.1016/j.ijcard.2020.04.043.
» https://doi.org/10.1016/j.ijcard.2020.04.043 -
3 Parahiba SM, Ribeiro ECT, Knobloch IS, Dapper D, Perry IDS, Clausell NO, et al. Handgrip Strength in Heart Failure: Developing a Reference Equation. Arq Bras Cardiol. 2025; 122(9):e20240777. doi: https://doi.org/10.36660/abc.20240777i
» https://doi.org/10.36660/abc.20240777i -
4 Pandey A, Kitzman D, Reeves G. Frailty is Intertwined with Heart Failure: Mechanisms, Prevalence, Prognosis, Assessment, and Management. JACC Heart Fail. 2019;7(12):1001-11. doi: 10.1016/j.jchf.2019.10.005.
» https://doi.org/10.1016/j.jchf.2019.10.005 -
5 Wang Y, Pu X, Zhu Z, Sun W, Xue L, Ye J. Handgrip Strength and the Prognosis of Patients with Heart Failure: A Meta-Analysis. Clin Cardiol. 2023;46(10):1173-84. doi: 10.1002/clc.24063.
» https://doi.org/10.1002/clc.24063 -
6 Porto JM, Nakaishi APM, Cangussu-Oliveira LM, Freire RC Jr, Spilla SB, Abreu DCC. Relationship between Grip Strength and Global Muscle Strength in Community-Dwelling Older People. Arch Gerontol Geriatr. 2019;82:273-8. doi: 10.1016/j.archger.2019.03.005.
» https://doi.org/10.1016/j.archger.2019.03.005 -
7 Lee SC, Wu LC, Chiang SL, Lu LH, Chen CY, Lin CH, et al. Validating the Capability for Measuring Age-Related Changes in Grip-Force Strength Using a Digital Hand-Held Dynamometer in Healthy Young and Elderly Adults. Biomed Res Int. 2020;2020:6936879. doi: 10.1155/2020/6936879.
» https://doi.org/10.1155/2020/6936879 -
8 Reichenheim ME, Lourenço RA, Nascimento JS, Moreira VG, Neri AL, Ribeiro RM, et al. Normative Reference Values of Handgrip Strength for Brazilian Older People Aged 65 to 90 Years: Evidence from the Multicenter Fibra-BR Study. PLoS One. 2021;16(5):e0250925. doi: 10.1371/journal.pone.0250925.
» https://doi.org/10.1371/journal.pone.0250925 -
9 Núñez-Cortés R, Cruz BDP, Gallardo-Gómez D, Calatayud J, Cruz-Montecinos C, López-Gil JF, et al. Handgrip Strength Measurement Protocols for All-Cause and Cause-Specific Mortality Outcomes in More than 3 Million Participants: A Systematic Review and Meta-Regression Analysis. Clin Nutr. 2022;41(11):2473-89. doi: 10.1016/j.clnu.2022.09.006.
» https://doi.org/10.1016/j.clnu.2022.09.006 -
10 Napper AD, Sayal MK, Holmes MWR, Cudlip AC. Sex Differences in Wrist Strength: A Systematic Review. PeerJ. 2023;11:e16557. doi: 10.7717/peerj.16557.
» https://doi.org/10.7717/peerj.16557 -
11 Byambaa A, Altankhuyag I, Damdinbazar O, Jadamba T, Byambasukh O. Anthropometric and Body Circumference Determinants for Hand Grip Strength: A Population-Based Mon-Timeline Study. J Aging Res. 2023;2023:6272743. doi: 10.1155/2023/6272743.
» https://doi.org/10.1155/2023/6272743 -
12 Ibrahim K, May CR, Patel HP, Baxter M, Sayer AA, Roberts HC. Implementation of Grip Strength Measurement in Medicine for Older People Wards as Part of Routine Admission Assessment: Identifying Facilitators and Barriers Using a Theory-Led Intervention. BMC Geriatr. 2018;18(1):79. doi: 10.1186/s12877-018-0768-5.
» https://doi.org/10.1186/s12877-018-0768-5 -
13 Novaes RD, Miranda AS, Silva JO, Tavares BVF, Dourado VZ. Reference Equations for Predicting Handgrip Strength in Brazilians middle-Aged and Elderly Subjects. Fisioter Pesq. 2009;16(3):217-22. doi: 10.1590/S1809-29502009000300005.
» https://doi.org/10.1590/S1809-29502009000300005 - 14 Lee L, Patel T, Costa A, Bryce E, Hillier LM, Slonim K, et al. Screening for Frailty in Primary care: Accuracy of Gait Speed and Hand-Grip Strength. Can Fam Physician. 2017;63(1):e51-e57.
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15 Alley DE, Shardell MD, Peters KW, McLean RR, Dam TT, Kenny AM, et al. Grip Strength Cutpoints for the Identification of Clinically Relevant Weakness. J Gerontol A Biol Sci Med Sci. 2014;69(5):559-66. doi: 10.1093/gerona/glu011.
» https://doi.org/10.1093/gerona/glu011
