Abstract
Aims
Reduced skeletal muscle mass is a major component of sarcopenia, associated with impaired exercise capacity and poor prognosis in patients with heart failure (HF). Measurement of skeletal muscle mass by dual‐energy X‐ray absorptiometry may be affected by fluid retention, typically in the patients' lower extremities. The aim of the present study was to elucidate the association between upper and lower extremity skeletal muscle mass (USM and LSM) and all‐cause mortality in hospitalized patients with HF, after discharge.
Methods
This was a single‐centre observational cohort study of 418 patients (59% were men) admitted with a diagnosis of HF (71 ± 13 years), with a left ventricular ejection fraction of 39 ± 16%. USM and LSM were measured by dual‐energy X‐ray absorptiometry with patients in a stable state after decongestion therapy.
Results
The USM and LSM were 5.29 ± 1.18 and 13.78 ± 3.20 kg for men and 3.37 ± 0.68 and 9.19 ± 1.80 kg for women. A positive correlation was obtained between USM and LSM with mid‐upper arm circumference (r = 0.684, P < 0.001) and calf circumference (r = 0.822, P < 0.001), respectively. During a median follow‐up of 37 months, 92 (22.0%) of the 418 patients died. A Kaplan–Meier analysis revealed that sex‐specific quartiles of USM/height2 and LSM/height2 were associated with all‐cause mortality (both P < 0.001 by the log‐rank test). In Cox models adjusted by age, sex, creatinine, haemoglobin, NYHA class, and height2, the hazard ratio with 95% confidence intervals for all‐cause mortality was 0.557 [0.393–0.783] (P < 0.001) for USM per 1 kg, and 0.783 [0.689–0.891] (P < 0.001) for LSM per 1 kg. The receiver‐operator‐characteristic curve analysis showed a comparable area under the curve between the USM/height2 and LSM/height2 (0.557 vs. 0.568, P = 0.562) in predicting all‐cause mortality. The ratio of USM to LSM was significantly lower in 37 patients with residual leg oedema than in the 360 patients without oedema (36.1% vs. 38.1%, P = 0.004), suggesting the influence of oedema on measured LSM.
Conclusions
Both USM and LSM had a prognostic implication on mortality after discharge in HF, even though LSM may have been affected by leg oedema. These findings indicate that clinicians should not ignore a patient's USM or LSM in the prognostication of patients with HF.
Keywords: Skeletal muscle, Sarcopenia, Heart failure
Background
Abnormalities in the quantity and quality of skeletal muscle have been discussed with regard to sarcopenia, cachexia, frailty, and malnutrition and are closely related to impaired exercise tolerance and poor outcomes in patients with heart failure (HF). 1 , 2 , 3 , 4 , 5 Measurement of skeletal muscle mass by dual‐energy X‐ray absorptiometry (DXA) can be affected by fluid retention, 6 typically in patients' lower extremities. 7 However, no previous reports have examined the prognostic implications of upper and lower extremity skeletal muscle mass (USM and LSM) separately.
Aims
We hypothesized that both USM and LSM have a prognostic impact in HF. The purpose of the present study was to elucidate the association between upper/lower skeletal muscle mass and all‐cause mortality in hospitalized patients with HF, after discharge.
Methods
We retrospectively analysed data in a single‐centre observational cohort study of patients with HF. 2 The detailed study design has been described elsewhere. 2 Briefly, the inclusion criteria were patients with a diagnosis of HF based on Framingham criteria 7 and those who had undergone DXA during hospitalization. The exclusion criteria were patients with incomplete data (n = 1) and who died during hospitalization (n = 3). Informed consent was obtained from each patient. Our institutional ethics board approved the study, which was in line with ethical standards laid down in the 1964 Declaration of Helsinki. Blood examinations were performed at discharge. Echocardiography was performed during hospitalization. Measurement of muscle mass was performed using a DXA scan (Discovery, Hologic Japan Inc., Tokyo, Japan) with patients in a stable state after decongestion therapy. USM and LSM were defined as the sum of muscle mass in the upper and lower extremities, respectively. Data regarding the presence or absence of leg oedema and mortality after discharge were obtained from a review of the medical records of the hospital and form information sent from the referring hospital/clinic. The Student's t‐test or Mann–Whitney test for continuous variables and χ2 tests or Fisher's exact test for categorical variables were employed for comparing the groups, as appropriate. A Pearson coefficient was calculated between the two continuous variables. Multivariate linear regression analysis with the ratio of upper to lower extremity muscle mass as a dependent variable was performed. The Kaplan–Meier time‐to‐event curves using the log‐rank test were computed according to muscle mass. Cox proportional hazards models were adjusted by the same prognostic factors in HF as in the main study 2 (i.e. age, sex, creatinine, haemoglobin, NHYA class, and height squared) to investigate the association between muscle mass and all‐cause mortality. To compare the association with all‐cause mortality, receiver‐operator‐characteristic curve analysis was performed, and the area under the curve was assessed using DeLong's method. All statistical tests were two‐tailed, and a P value < 0.05 was considered statistically significant. Analyses were carried out using JMP Pro software 16 (SAS Institute Japan Inc., Tokyo, Japan).
Results
The study cohort consisted of 418 patients with 59.1% males, and the mean age was 71 ± 13 years. The baseline characteristics of the study population and the results from DXA are shown separately by sex and higher/lower USM and LSM using sex‐specific medians in Tables 1 and 2 . The median length of stay was 18 days (interquartile range, 14–27), and patients underwent DXA a median of 6 days (interquartile range, 1–12) before discharge. USM and LSM were 5.29 ± 1.18 and 13.78 ± 3.20 kg for men and 3.37 ± 0.68 and 9.19 ± 1.80 kg for women. Mid‐upper arm and calf circumference was measured after November 2016 in 44 patients, showing a positive correlation to USM (r = 0.684, P < 0.001) and LSM (r = 0.822, P < 0.001), respectively. The ratio of USM to LSM was 38.0% in the overall cohort. At discharge, leg oedema remained in 37 of the 397 (9.3%) patients and was not documented in 21 patients. The ratio of USM to LSM was significantly lower in patients with residual leg oedema than in those with no oedema at discharge (36.1 vs. 38.1%, P = 0.004). In the multivariate linear regression analysis, the presence of residual leg oedema was associated with a lower ratio of USM to LSM after adjustment for age and sex (standardized beta = −0.112, P = 0.025). During the median follow‐up of 37.0 months, 92 (22.0%) patients died. In the Kaplan–Meier analysis, there was a significant difference in all‐cause mortality among the sex‐specific quartiles of USM and LSM indexed by height squared (both P < 0.001; Figure 1 ). In the multivariate Cox models, the hazard ratio for all‐cause mortality was 0.557 [0.393–0.783] (P < 0.001) for 1 kg increase of USM and 0.783 [0.689–0.891] (P < 0.001) for 1 kg increase of LSM. The receiver‐operator‐characteristic curve analysis showed a comparable area under the curve between USM/height2 and LSM/height2 (0.557 vs. 0.568, P = 0.562) in predicting all‐cause mortality.
Table 1.
Characteristics of patients according to sex
| Missing data | ||||
|---|---|---|---|---|
| All | Male | Female | ||
| N | 418 | 247 | 171 | |
| Age (years) | 0 | 71 (13) | 68 (14) | 76 (10) |
| Body mass index (kg/m2) | 0 | 22.1 (4.6) | 22.6 (4.5) | 21.6 (4.6) |
| Readmission | 0 | 27.8% | 27.1% | 28.7% |
| Co‐morbidity | ||||
| Hypertension | 0 | 75.1% | 76.5% | 73.1% |
| Diabetes | 0 | 36.6% | 37.3% | 35.7% |
| Coronary artery disease | 0 | 39.0% | 43.7% | 32.2% |
| Atrial fibrillation | 0 | 35.4% | 32.8% | 39.2% |
| Severe valvular disease | 0 | 32.8% | 29.2% | 38.0% |
| COPD | 0 | 5.3% | 7.7% | 1.8% |
| Stroke | 0 | 8.6% | 9.3% | 7.6% |
| Malignancy | 0 | 8.9% | 9.7% | 7.6% |
| Status at discharge | ||||
| NYHA class | 0 | |||
| ≤2 | 83.7% | 88.7% | 76.6% | |
| 3 | 15.8% | 10.5% | 23.4% | |
| 4 | 0.5% | 0.8% | 0.0% | |
| Systolic blood pressure (mmHg) | 1 | 110 (17) | 111 (18) | 110 (17) |
| Laboratory findings at discharge | ||||
| Haemoglobin (g/dL) | 0 | 12.0 (2.2) | 12.5 (2.2) | 11.3 (2.0) |
| Creatinine (mg/dL) | 0 | 1.39 (1.04) | 1.50 (1.14) | 1.24 (0.84) |
| Estimated GFR (mL/min/1.73 m2) | 0 | 46 (19) | 48 (19) | 42 (17) |
| Albumin (g/dL) | 1 | 3.62 (0.53) | 3.65 (0.54) | 3.57 (0.51) |
| BNP, median (pg/mL) | 0 | 240 [132–417] | 230 [116–408] | 247 [149–460] |
| Medication at discharge | ||||
| Beta‐blocker | 1 | 72.7% | 76.9% | 66.5% |
| ACE inhibitor/ARB | 0 | 81.8% | 85.4% | 76.6% |
| Loop diuretics | 0 | 78.7% | 76.5% | 81.9% |
| MRA | 0 | 59.6% | 61.5% | 56.7% |
| LVEF (%) | 0 | 39 (16) | 37 (16) | 43 (16) |
| HFrEF | 53.8% | 59.5% | 45.6% | |
| HFmrEF | 15.6% | 17.0% | 13.5% | |
| HFpEF | 30.6% | 23.5% | 40.9% | |
| Body composition | 0 | |||
| ASM/height2 (kg/m2) | 6.35 (1.28) | 6.88 (1.23) | 5.59 (0.92) | |
| USM (kg) | 4.51 (1.38) | 5.29 (1.18) | 3.37 (0.68) | |
| USM/height2 (kg/m2) | 1.74 (0.37) | 1.91 (0.34) | 1.50 (0.27) | |
| LSM (kg) | 11.90 (3.54) | 13.78 (3.20) | 9.19 (1.80) | |
| LSM/height2 (kg/m2) | 4.61 (0.95) | 4.97 (0.93) | 4.09 (0.69) | |
ACE, angiotensin‐converting enzyme; ARB, angiotensin receptor blocker; ASM, appendicular skeletal muscle mass; BNP, B‐type natriuretic peptide; COPD, chronic obstructive pulmonary disease; GFR, glomerular filtration rate; HFmrEF, heart failure with mildly reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; LSM, lower extremity skeletal muscle mass; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonist; NYHA, New York Heart Association; USM, upper extremity skeletal muscle mass.
Values presented as frequency (%), mean (standard deviation), or median [interquartile range].
Table 2.
Characteristics of patients according to upper/lower extremity skeletal muscle mass by sex‐specific medians
| Missing data | USM/height2 | LSM/height2 | ||||||
|---|---|---|---|---|---|---|---|---|
| All | Below median | Above median | P | Below median | Above median | P | ||
| N | 418 | 208 | 210 | 208 | 210 | |||
| Age (years) | 0 | 71 (13) | 74 (10) | 68 (14) | <0.001 | 74 (10) | 68 (14) | <0.001 |
| Body mass index (kg/m2) | 0 | 22.1 (4.6) | 19.6 (2.7) | 24.6 (4.7) | <0.001 | 19.6 (2.8) | 24.7 (4.6) | <0.001 |
| Readmission | 0 | 27.8% | 28.4% | 27.1% | 0.827 | 29.8% | 25.7% | 0.383 |
| Co‐morbidity | ||||||||
| Hypertension | 0 | 75.1% | 69.7% | 80.5% | 0.013 | 70.2% | 80.0% | 0.024 |
| Diabetes | 0 | 36.6% | 30.3% | 42.9% | 0.008 | 35.1% | 38.1% | 0.544 |
| Coronary artery disease | 0 | 39.0% | 37.5% | 40.5% | 0.549 | 39.9% | 38.1% | 0.764 |
| Atrial fibrillation | 0 | 35.4% | 39.4% | 31.4% | 0.102 | 35.1% | 35.7% | 0.919 |
| Severe valvular disease | 0 | 32.8% | 37.5% | 28.1% | 0.048 | 35.1% | 30.5% | 0.349 |
| COPD | 0 | 5.3% | 6.3% | 4.3% | 0.390 | 5.8% | 4.8% | 0.668 |
| Stroke | 0 | 8.6% | 11.1% | 6.2% | 0.083 | 10.1% | 7.1% | 0.300 |
| Malignancy | 0 | 8.9% | 11.5% | 6.2% | 0.060 | 12.5% | 5.2% | 0.010 |
| Status at discharge | ||||||||
| NYHA class | 0 | 0.011 | 0.011 | |||||
| ≤2 | 83.7% | 78.9% | 88.6% | 78.9% | 88.6% | |||
| 3 | 15.8% | 20.2% | 11.4% | 20.2% | 11.4% | |||
| 4 | 0.5% | 1.0% | 0.0% | 1.0% | 0.0% | |||
| Systolic blood pressure (mmHg) | 1 | 110 (17) | 108 (18) | 113 (17) | 0.001 | 108 (18) | 112 (16) | 0.013 |
| Laboratory findings at discharge | ||||||||
| Haemoglobin (g/dL) | 0 | 12.0 (2.2) | 11.6 (2.0) | 12.3 (2.3) | 0.001 | 11.7 (2.1) | 12.3 (2.3) | 0.002 |
| Creatinine (mg/dL) | 0 | 1.39 (1.04) | 1.39 (0.87) | 1.40 (1.18) | 0.944 | 1.32 (0.69) | 1.46 (1.29) | 0.172 |
| Estimated GFR (mL/min/1.73 m2) | 0 | 46 (19) | 44 (17) | 47 (20) | 0.048 | 45 (18) | 46 (19) | 0.512 |
| Albumin (g/dL) | 1 | 3.62 (0.53) | 3.60 (0.50) | 3.64 (0.55) | 0.385 | 3.55 (0.49) | 3.69 (0.56) | 0.007 |
| BNP, median (pg/mL) | 0 | 240 [132–417] | 277 [162–506] | 212 [103–365] | <0.001 | 277 [153–510] | 213 [112–366] | <0.001 |
| Medication at discharge | ||||||||
| Beta‐blocker | 1 | 72.7% | 71.2% | 74.2% | 0.511 | 73.6% | 71.8% | 0.742 |
| ACE inhibitor/ARB | 0 | 81.8% | 76.4% | 87.1% | 0.005 | 77.4% | 86.2% | 0.023 |
| Loop diuretics | 0 | 78.7% | 78.9% | 78.6% | 1.000 | 80.8% | 76.7% | 0.340 |
| MRA | 0 | 59.6% | 60.1% | 59.1% | 0.843 | 61.5% | 57.6% | 0.427 |
| LVEF (%) | 0 | 39 (16) | 39 (16) | 40 (16) | 0.615 | 37 (16) | 41 (17) | 0.024 |
| HFrEF | 53.8% | 54.8% | 52.9% | 0.716 | 58.2% | 49.5% | 0.109 | |
| HFmrEF | 15.6% | 16.4% | 14.8% | 15.9% | 15.2% | |||
| HFpEF | 30.6% | 28.9% | 32.4% | 26.0% | 35.2% | |||
ACE, angiotensin‐converting enzyme; ARB, angiotensin receptor blocker; ASM, appendicular skeletal muscle mass; BNP, B‐type natriuretic peptide; COPD, chronic obstructive pulmonary disease; GFR, glomerular filtration rate; HFmrEF, heart failure with mildly reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; LSM, lower extremity skeletal muscle mass; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonist; NYHA, New York Heart Association; USM, upper extremity skeletal muscle mass.
Values presented as frequency (%), mean (standard deviation), or median [interquartile range].
Figure 1.
Kaplan–Meier estimates of the cumulative incidence of all‐cause mortality according to quartiles of USM/height2 and LSM/height2. Kaplan–Meier curve according to quartiles of USM/height2 (A) and LSM/height2 (B) for all‐cause mortality. LSM, lower extremity skeletal muscle mass; USM, upper extremity skeletal muscle mass.
Conclusions
The principal findings of the study were as follows: (i) Both USM and LSM were associated with all‐cause mortality in the Kaplan–Meier analyses; (ii) multivariate analysis revealed that both USM and LSM were associated with all‐cause mortality even after adjustment for multiple known prognostic factors in HF; and (iii) LSM was relatively higher than USM in patients with residual leg oedema.
The mechanisms associated with muscle mass and mortality have already been discussed in our previous study, 2 some of which (i.e. a beneficial ‘myokine’ or a good cardiorespiratory fitness in patients with a large muscle mass) may be common to USM and LSM. Given a potential benefit from adding upper extremity muscle interventions to lower extremity muscle interventions, 8 it may be meaningful to assess upper and lower extremity muscle masses separately. The difference in the radio of USM to LSM in patients with and without residual leg oedema may be indirect evidence that the LSM measured by DXA was overestimated due to fluid retention in the lower extremities. In patients with cirrhosis, USM is a better prognostic marker than appendicular skeletal muscle mass. 9 There are some limitations to this research, including a retrospective observational study design that may lead to sampling bias and a lack of data regarding muscle function, which is a major component of a diagnosis of sarcopenia. 10
In conclusion, this study showed that in hospitalized patients with HF, both USM and LSM were associated with all‐cause mortality after discharge. These findings are a caution that clinicians should not ignore a patient's USM or LSM in the prognostication of patients with HF.
Conflict of interest
K. Tamura has received lecture fees from Daiichi‐Sankyo, Mochida, Kyowa‐hakko Kirin, Pfizer, Boehringer Ingelheim Japan, and Dainippon‐Sumitomo. His institution has received a research grant from Daiichi‐Sankyo, Takeda, Mochida, Kyowa‐hakko Kirin, Pfizer, Novartis, Dainippon‐Sumitomo, AstraZeneca, Ono Pharmaceutical, Tsumura, Kaneka, and Oriental Yeast. K. Kimura has received lecture fees from Astrazeneca, Toa Eiyo Ltd., MSD, Bayer, and Daiichi‐Sankyo. His institution has received a research grant from MSD, Daiichi‐Sankyo, Ono Pharmaceutical, Phizer, Bayer, Takeda, Boehringer Ingelheim Japan, Tanabe Mitsubishi, and Astellas Pharma. Masaaki Konishi, Eiichi Akiyama, Yasushi Matsuzawa, Ryosuke Sato, Shinnosuke Kikuchi, Hidefumi Nakahashi, Kozo Okada, Noriaki Iwahashi, Masami Kosuge, Toshiaki Ebina, Kiyoshi Hibi, and Toshihiro Misumi declare that they have no conflicts of interest.
Funding
This study was supported by the Grant‐in‐Aid for Young Scientist (B) 19K16986 (M.K.).
Konishi, M. , Akiyama, E. , Matsuzawa, Y. , Sato, R. , Kikuchi, S. , Nakahashi, H. , Okada, K. , Iwahashi, N. , Kosuge, M. , Ebina, T. , Hibi, K. , Misumi, T. , Tamura, K. , and Kimura, K. (2023) Prognostic impact of upper and lower extremity muscle mass in heart failure. ESC Heart Failure, 10: 732–737. 10.1002/ehf2.14195.
References
- 1. Konishi M, Kagiyama N, Kamiya K, Saito H, Saito K, Ogasahara Y, Maekawa E, Misumi T, Kitai T, Iwata K, Jujo K, Wada H, Kasai T, Nagamatsu H, Ozawa T, Izawa K, Yamamoto S, Aizawa N, Makino A, Oka K, Momomura SI, Matsue Y. Impact of sarcopenia on prognosis in patients with heart failure with reduced and preserved ejection fraction. Eur J Prev Cardiol. 2020; 28: 1022–1029. [DOI] [PubMed] [Google Scholar]
- 2. Konishi M, Akiyama E, Matsuzawa Y, Sato R, Kikuchi S, Nakahashi H, Maejima N, Iwahashi N, Kosuge M, Ebina T, Hibi K, Misumi T, Haehling S, Anker SD, Tamura K, Kimura K. Prognostic impact of muscle and fat mass in patients with heart failure. J Cachexia Sarcopenia Muscle. 2021; 12: 568–576. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Anker SD, Negassa A, Coats AJ, Afzal R, Poole‐Wilson PA, Cohn JN, Yusuf S. Prognostic importance of weight loss in chronic heart failure and the effect of treatment with angiotensin‐converting‐enzyme inhibitors: An observational study. Lancet. 2003; 361: 1077–1083. [DOI] [PubMed] [Google Scholar]
- 4. Uchmanowicz I, Lee CS, Vitale C, Manulik S, Denfeld QE, Uchmanowicz B, Rosińczuk J, Drozd M, Jaroch J, Jankowska EA. Frailty and the risk of all‐cause mortality and hospitalization in chronic heart failure: A meta‐analysis. ESC Heart Fail. 2020; 7: 3427–3437. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Wood N, Straw S, Scalabrin M, Roberts LD, Witte KK, Bowen TS. Skeletal muscle atrophy in heart failure with diabetes: From molecular mechanisms to clinical evidence. ESC Heart Fail. 2021; 8: 3–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Proctor DN, O'Brien PC, Atkinson EJ, Nair KS. Comparison of techniques to estimate total body skeletal muscle mass in people of different age groups. Am J Physiol. 1999; 277: E489–E495. [DOI] [PubMed] [Google Scholar]
- 7. McKee PA, Castelli WP, McNamara PM, Kannel WB. The natural history of congestive heart failure: The Framingham study. N Engl J Med. 1971; 285: 1441–1446. [DOI] [PubMed] [Google Scholar]
- 8. Jondeau G, Katz SD, Zohman L, Goldberger M, McCarthy M, Bourdarias JP, LeJemtel TH. Active skeletal muscle mass and cardiopulmonary reserve. Failure to attain peak aerobic capacity during maximal bicycle exercise in patients with severe congestive heart failure. Circulation. 1992; 86: 1351–1356. [DOI] [PubMed] [Google Scholar]
- 9. Eriksen CS, Kimer N, Suetta C, Møller S. Arm lean mass determined by dual‐energy X‐ray absorptiometry is superior to characterize skeletal muscle and predict sarcopenia‐related mortality in cirrhosis. Am J Physiol Gastrointest Liver Physiol. 2021; 320: G729–G740. [DOI] [PubMed] [Google Scholar]
- 10. Chen L‐K, Woo J, Assantachai P, Auyeung T‐W, Chou M‐Y, Iijima K, Jang HC, Kang L, Kim M, Kim S, Kojima T, Kuzuya M, Lee JSW, Lee SY, Lee WJ, Lee Y, Liang CK, Lim JY, Lim WS, Peng LN, Sugimoto K, Tanaka T, Won CW, Yamada M, Zhang T, Akishita M, Arai H. Asian working group for sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. 2020; 21: 300–307.e2. [DOI] [PubMed] [Google Scholar]