Muscle strength and muscle mass as predictors of hospital length of stay in patients with moderate to severe COVID‐19: a prospective observational study

Abstract

Background
Strength and muscle mass are predictors of relevant clinical outcomes in critically ill patients, but in hospitalized patients with COVID-19, it remains to be determined. In this prospective observational study, we investigated whether muscle strength or muscle mass are predictive of hospital length of stay (LOS) in patients with moderate to severe COVID-19 patients.

Methods
We evaluated prospectively 196 patients at hospital admission for muscle mass and strength. Ten patients did not test positive for SARS-CoV-2 during hospitalization and were excluded from the analyses.

Results
The sample comprised patients of both sexes (50% male) with a mean age (SD) of 59 (±15) years, body mass index of 29.5 (±6.9) kg/m². The prevalence of current smoking patients was 24.7%, and more prevalent coexisting conditions were hypertension (67.7%), obesity (40.9%), and type 2 diabetes (36.0%). Mean (SD) LOS was 8.6 days (7.7); 17.0% of the patients required intensive care; 3.8% used invasive mechanical ventilation; and 6.6% died during the hospitalization period. The crude hazard ratio (HR) for LOS was greatest for handgrip strength comparing the strongest versus other patients (1.47 [95% CI: 1.07–2.03; P = 0.019]). Evidence of an association between increased handgrip strength and shorter hospital stay was also identified when handgrip strength was standardized according to the sex-specific mean and standard deviation (1.23 [95% CI: 1.06–1.43; P = 0.007]). Mean LOS was shorter for the strongest patients (7.5 ± 6.1 days) versus others (9.2 ± 8.4 days). Evidence of associations were also present for vastus lateralis cross-sectional area. The crude HR identified shorter hospital stay for patients with greater sex-specific standardized values (1.20 [95% CI: 1.03–1.39; P = 0.016]). Evidence was also obtained associating longer hospital stays for patients with the lowest values for vastus lateralis cross-sectional area (0.63 [95% CI: 0.46–0.88; P = 0.006). Mean LOS for the patients with the lowest muscle cross-sectional area was longer (10.8 ± 8.8 days) versus others (7.7 ± 7.2 days). The magnitude of associations for handgrip strength and vastus lateralis cross-sectional area remained consistent and statistically significant after adjusting for other covariates.

Conclusions
Muscle strength and mass assessed upon hospital admission are predictors of LOS in patients with moderate to severe COVID-19, which stresses the value of muscle health in prognosis of this disease.

Full text

Muscle strength and muscle mass as predictors of
hospital length of stay in patients with moderate to
severe COVID-19: a prospective observational study
Saulo Gil
1,2
, Wilson Jacob Filho
2
, Samuel Katsuyuki Shinjo
3
, Eduardo Ferriolli
2,4
, Alexandre Leopold Busse
2
,
Thiago Junqueira Avelino-Silva
2
, Igor Longobardi
1
, Gersiel Nascimento de Oliveira Júnior
1
, Paul Swinton
5
,
Bruno Gualano
1,3
, Hamilton Roschel
1,2
*& The HCFMUSP COVID-19 Study Group
†
1
Applied Physiology & Nutrition Research Group, School of Physical Education and Sport, Rheumatology Division, Faculdade de Medicina FMUSP, Universidade de Sao Paulo,
São Paulo, SP, Brazil;
2
Laboratorio de Investigacao Medica em Envelhecimento (LIM-
66
), Servico de Geriatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina,
Universidade de Sao Paulo, Sao Paulo, Brazil;
3
Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao
Paulo, Brazil;
4
Division of Internal and Geriatric Medicine, Department of Internal Medicine –Ribeirão Preto Medical School, Universidade de Sao Paulo, Ribeirao Preto,
Brazil;
5
School of Health Sciences, Robert Gordon University, Aberdeen, UK
Abstract
Background Strength and muscle mass are predictors of relevant clinical outcomes in critically ill patients, but in hos-
pitalized patients with COVID-19, it remains to be determined. In this prospective observational study, we investigated
whether muscle strength or muscle mass are predictive of hospital length of stay (LOS) in patients with moderate to
severe COVID-19 patients.
Methods We evaluated prospectively 196 patients at hospital admission for muscle mass and strength. Ten patients
did not test positive for SARS-CoV-2 during hospitalization and were excluded from the analyses.
Results The sample comprised patients of both sexes (50% male) with a mean age (SD) of 59 (±15) years, body mass
index of 29.5 (±6.9) kg/m
2
. The prevalence of current smoking patients was 24.7%, and more prevalent coexisting
conditions were hypertension (67.7%), obesity (40.9%), and type 2 diabetes (36.0%). Mean (SD) LOS was 8.6 days
(7.7); 17.0% of the patients required intensive care; 3.8% used invasive mechanical ventilation; and 6.6% died during
the hospitalization period. The crude hazard ratio (HR) for LOS was greatest for handgrip strength comparing the
strongest versus other patients (1.47 [95% CI: 1.07–2.03; P= 0.019]). Evidence of an association between increased
handgrip strength and shorter hospital stay was also identified when handgrip strength was standardized according
to the sex-specific mean and standard deviation (1.23 [95% CI: 1.06–1.43; P= 0.007]). Mean LOS was shorter for
the strongest patients (7.5 ± 6.1 days) versus others (9.2 ± 8.4 days). Evidence of associations were also present for
vastus lateralis cross-sectional area. The crude HR identified shorter hospital stay for patients with greater
sex-specific standardized values (1.20 [95% CI: 1.03–1.39; P= 0.016]). Evidence was also obtained associating longer
hospital stays for patients with the lowest values for vastus lateralis cross-sectional area (0.63 [95% CI: 0.46–0.88;
P= 0.006). Mean LOS for the patients with the lowest muscle cross-sectional area was longer (10.8 ± 8.8 days) versus
others (7.7 ± 7.2 days). The magnitude of associations for handgrip strength and vastus lateralis cross-sectional area
remained consistent and statistically significant after adjusting for other covariates.
Conclusions Muscle strength and mass assessed upon hospital admission are predictors of LOS in patients with mod-
erate to severe COVID-19, which stresses the value of muscle health in prognosis of this disease.
Keywords COVID-19; Handgrip; Hospital stay; Skeletal muscle
Received:
1
April
2021
; Revised:
4
June
2021
; Accepted:
4
August
2021
*Correspondence to: Hamilton Roschel, Applied Physiology & Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning
in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Prof. Mello Moraes,
65
São Paulo, SP
01246
-
903
, Brazil. Phone: +
55 11 3061
.
8789
.
Email: hars@usp.br
ORIGINAL ARTICLE
© 2021 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the
original work is properly cited.
Journal of Cachexia, Sarcopenia and Muscle 2021; 12: 1871–1878
Published online 14 September 2021 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/jcsm.12789

†HCFMUSP COVID-19 Study Group: Eloisa Bonfá; Edivaldo Utiyama; Aluisio Segurado; Beatriz Perondi; Anna Miethke Morais; Amanda Montal; Leila Letaif; Solange Fusco;
Marjorie Fregonesi Rodrigues da Silva; Marcelo Rocha; Izabel Marcilio; Izabel Cristina Rios; Fabiane Yumi Ogihara Kawano; Maria Amélia de Jesus; Ésper Georges Kallas;
Carolina Carmo; Clarice Tanaka; Heraldo Possolo de Souza; Julio F. M. Marchini; Carlos Carvalho; Juliana Carvalho Ferreira; Anna Sara Shafferman Levin; Maura Salaroli
de Oliveira; Thaís Guimarães; Carolina dos Santos Lázari; Alberto José da Silva Duarte; Ester Sabino; Marcello Mihailenko Chaves Magri; Tarcisio E. P. Barros-Filho;
Maria Cristina Peres Braido Francisco.
Introduction
Aging and chronic conditions such as type 2 diabetes increase
the risk of developing severe forms of COVID-19. Neverthe-
less, apparently healthier, younger individuals may also re-
quire hospitalization and develop poor outcomes.
1–3
This
suggests that there might be undiscovered clinical features
associated with COVID-19 prognosis, with muscular parame-
ters being potential candidates.
Skeletal muscle constitutes ~40% of total body mass and
plays a pivotal role in different physiological process such as
immune response, regulation of glucose levels, protein syn-
thesis, and basal metabolic rate.
4–6
Handgrip strength and
muscle mass have been shown previously to be predictive
of clinical outcomes, such as hospital length of stay (LOS)
and mortality, in distinct populations.
7–11
In fact, the significance of muscle mass and strength to exer-
cise and activities of daily living has never been questioned.
Muscle also plays a central role in the response to stress in
acute conditions, a role that has been somewhat less
appreciated.
12
Cases of exacerbated cytokines production (i.
e.‘cytokine storm’) can lead to sepsis, which has been deemed
partially responsible for fatal cases of COVID-19.
13
In such con-
ditions, inflammation leads to multi-organ damage, affecting
mostly pulmonary, cardiac, hepatic, vascular, and renal sys-
tems. Preservation of protein content in key tissues and or-
gans, such as the brain, heart, and liver, is essential for
survival, and it can be maintained relatively constant under
acute stressful conditions, provided muscle mass is adequate
to supply the required amino acids.
14,15
Skeletal muscle is also
a major immunoregulatory organ, responsible for the produc-
tion of a wide range of soluble factors with anti-inflammatory
and immunoprotective effects, the so-called myokines, which
could help ameliorate exacerbated inflammation in this
disease.
5
The potentially protective role of muscle tissue in
COVID-19 allows hypothesizing that muscle health may be an
important predictor of clinical outcomes in this disease.
Herein, we investigated whether muscle strength and mus-
cle mass assessed at hospital admission are predictive of LOS
in patients with moderate to severe COVID-19.
Methods
Study design
This is a prospective observational study conducted between
March 2020 and October 2020 in the Clinical Hospital of the
School of Medicine of the University of Sao Paulo in Brazil
(HCFMUSP) the largest quaternary referral teaching hospital
in Latin America. This study was approved by the local Ethics
Committee (Ethics Committee Approval Number
(31303720.7.0000.0068). All patients provided written in-
formed consent before entering the study. This manuscript
was reported according to the Strengthening the Reporting
of Observational Studies in Epidemiology (STROBE) State-
ment and comply with ethical guidelines for publishing in
the Journal of Cachexia, Sarcopenia and Muscle.
16
Participants
The inclusion criteria were (i) aged 18 or older; (ii) diagnosis
of COVID-19 by PCR for SARS-CoV-2 from nasopharyngeal
swabs or computed tomography scan findings (bilateral mul-
tifocal ground-glass opacities ≥50%) compatible with the dis-
ease; (iii) diagnosis of flu syndrome with hospitalization
criteria on hospital admission, presenting respiratory rate
≥24 breaths per minute, saturation <93% on room air or risk
factors for complications, such as heart disease, diabetes
mellitus, systemic arterial hypertension, neoplasms, immuno-
suppression, pulmonary tuberculosis, and obesity, followed
by COVID-19 confirmation. Exclusion criteria were (i) cancer
in the past 5 years; (ii) delirium; (iii) cognitive deficit that pre-
cluded the patient from reading and signing the informed
consent form; (iv) prior diagnosis of muscle degenerative dis-
ease (e.g. myopathies, amyotrophic lateral sclerosis, and
stroke); (v) patients already admitted under invasive mechan-
ical ventilation. Patients who met these criteria were consid-
ered to have moderate to severe COVID-19 according to
NIH.
17
Patients or the public were not involved in the design,
or conduct, or reporting, or dissemination plans of our
research.
Data collection
All patients were evaluated in the point-of-care within <48 h
upon hospital admission for handgrip strength and vastus
lateralis cross-sectional area, by means of ultrasound imag-
ing, and were followed until medical discharge.
Handgrip strength assessments were performed with the
patient seated holding the dynamometer (TKK 5101; Takei,
Tokyo, Japan) with the dominant hand and elbow posi-
tioned at a 90° angle. Three maximum attempts of 5 s with
1 min of the interval between attempts were performed,
and the best result was used for analysis. Vastus lateralis
1872 S. Gil et al.
Journal of Cachexia, Sarcopenia and Muscle 2021; 12: 1871–1878
DOI: 10.1002/jcsm.12789

Table 1 Demographics and clinical characteristics of patients at hospital admission
All patients (n= 186) Survivors (n= 174)
Sex, n(%)
Female 93 (50.0%) 88 (50.6%)
Male 93 (50.0%) 86 (49.4%)
Age, n(%)
<65 116 (62.4%) 112 (64.4%)
>65 70 (37.6%) 62 (35.6%)
Race, n(%)
White 95 (51.1%) 90 (51.7%)
Black 58 (31.2%) 52 (29.9%)
Yellow 33 (17.7%) 32 (18.4%)
Smoking status, n(%)
Never 140 (75.3%) 132 (75.9%)
Current 46 (24.7%) 42 (24.1%)
Co-morbidities, n(%)
Asthma 12 (6.5%) 11 (6.3%)
Heart failure 18 (9.7%) 16 (9.2%)
Obesity (BMI >30) 76 (40.9%) 70 (40.2%)
Type 2 diabetes 67 (36.0%) 56 (32.2%)
COPD 7 (3.8%) 7 (4.0%)
Chronic renal disease 11 (5.9%) 9 (5.2%)
Ethilism 7 (3.8%) 6 (3.4%)
Atrial fibrillation 8 (4.3%) 8 (4.6%)
Acute myocardial infarction 13 (7.0%) 13 (7.5%)
Hypertension 126 (67.7%) 113 (64.9%)
COVID-19 testing, n(%)
Positive PCR for SARS-CoV-2 160 (86.0%) 148 (85.1%)
Positive IgG for SARS-CoV-2 26 (14.0%) 26 (14.9%)
Acute COVID-19 symptoms, n(%)
Anosmia 37 (19.9%) 35 (20.1%)
Headache 41 (22.0%) 38 (21.8%)
Runny nose 17 (9.1%) 17 (9.8%)
Diarrhoea 33 (17.7%) 31 (17.8%)
Dysgeusia 31 (17.2%) 30 (17.2%)
Dyspnoea 151 (81.2%) 141 (81.0%)
Abdominal pain 19 (10.2%) 18 (10.3%)
Chest pain 19 (10.2%) 19 (10.9%)
Fatigue 47 (25.3%) 43 (24.7%)
Fever 107 (57.5%) 99 (56.9%)
Myalgia 50 (26.9%) 47 (27.0%)
Nausea 21 (11.3%) 20 (11.5%)
Earache 8 (4.3%) 8 (4.6%)
Cough 119 (64.4%) 110 (63.2%)
Dizziness 2 (1.1.%) 2 (1.1%)
Vomiting 18 (9.7%) 18 (10.3%)
Oxygen support, n(%)
No oxygen therapy 68 (36.6) 66 (37.9)
Oxygen therapy 104 (55.9) 98 (56.3)
Non-invasive ventilation 14 (7.5) 10 (5.7)
Biochemical parameters
Haemoglobin, mean (SD), g/L 12.6 (2.9) [n= 182] 12.7 (3.0) [n= 170]
Neutrophil, mean (SD), ×10
3
/mm
3
6.6 (4.1) [n= 178] 6.5 (4.2) [n= 166]
Lymphocytes, mean (SD), ×10
3
/mm
3
1.3 (1.1) [n= 176] 1.3 (1.2) [n= 165]
Platelets, mean (SD), ×10
3
/mm
3
255.8 (126.1) [n= 181] 259.0 (128.6) [n= 169]
C-reactive protein, mean (SD), mg/L 92.3 (87.7) [n= 167] 84.5 (80.6) [n= 156]
D-dimer, mean (SD), ng/mL 2383.8 (4770.2) [n= 134] 2159.8 (3995.4) [n= 124]
Creatinine, mean (SD), mg/dL 1.4 (2.1) [n= 176] 1.2 (0.9) [n= 164]
Urea, mean (SD), mg/dL 51.8 (39.2) [n= 177] 48.6 (33.1) [n= 165]
Pulmonary commitment
a
(≥50%), n(%) 42 (22.6%) 35 (18.8%)
ICU admission, n(%) 33 (17.7%) 22 (12.6)
Use of invasive mechanical ventilation, n(%) 7 (3.8) 1 (0.6%)
Hospital length of stay (day), median (IQR) 7 (4–11) 7 (4–11)
In-hospital death, n(%) 12 (6.5%) -
Handgrip strength, kgF, median (IQR) 21 (15–30) 22 (15–30)
Vastus lateralis CSA, cm
3
, median (IQR) 12 (12–19) 16 (12–18)
BMI, body mass index; COPD, chronic obstructive pulmonary disease; CSA, cross-sectional area; ICU, intensive care unit; IQR, interquartile
range.
a
Pulmonary commitment was evaluated using chest computed tomography.
Muscle parameters as predictors of length of stay in COVID-19 1873
Journal of Cachexia, Sarcopenia and Muscle 2021; 12: 1871–1878
DOI: 10.1002/jcsm.12789

cross-sectional area was assessed by a B-mode ultrasound
with a 7.5-MHz linear-array probe (SonoAce R3, Samsung-
Medison, Gangwon-do, South Korea) as previously
described.
18
Cross-sectional area analyses were performed
in a blinded fashion by a single investigator using ImageJ
(NIH, USA). All tests were conducted by the same investiga-
tor to avoid bias. Coefficients of variation for handgrip
strength and vastus lateralis cross-sectional area were
4.1% and 3.5%, respectively. Demographic, clinical, and bio-
chemical data of the patients were obtained through med-
ical records.
Outcome and stratification of patients
Our primary outcome was LOS, defined as time (days) from
hospital admission to medical discharge. To examine whether
muscle strength or mass were predictive of LOS, we ranked
patients according to handgrip strength and vastus lateralis
cross-sectional area into sex-specific tertiles. Then, we com-
pared the highest tertile (High) versus the combined mid
and lowest tertiles (High vs. Other), and the lowest tertile
(Low) versus the combined mid and highest tertiles (Low vs.
Other).
Sample size and statistical analyses
An a priori sample size estimate was made to achieve small
optimism in the predictor effect estimates as defined by a
global shrinkage factor of 0.9.
19
The expected shrinkage is
conditioned on the sample size (n), the total number of pre-
dictors (p) and a generalization of the proportion of variance
explained for multivariable models with time-to-event out-
comes (R2
CSapp ).
19
For the present study, p was set to 6 and
R2
CSapp to 0.5 based on findings from previous research
8,20,21
and therein, indicating a required sample size of n= 184.
Guided by this estimate, a total of 196 patients were evalu-
ated during their hospital stay.
The outcome (LOS) was analysed with multivariable Cox
proportional baseline hazard models with surviving patients
only and adjusted for sex (male or female), age group (18–
35, 36–55, or ≥56), obesity (BMI <30 or BMI ≥30), oxygen
support at admission (0–4L,5–9 L,and ≥10 L), and Type 2 di-
abetes (yes or no). Both crude and adjusted hazard ratios
(HRs) were estimated for handgrip strength and vastus
lateralis cross-sectional area. Each predictor was assessed as
both a discrete and continuous predictor. Discrete models
were conducted by calculating sex-specific tertiles as origi-
nally planned and then focusing on either the largest tertile
(High vs. Other) or the smallest tertile (Low vs. Other). Con-
tinuous models were also included and conducted by stan-
dardizing predictor values relative to the sex-specific mean
and standard deviation. HRs were accompanied with
corresponding 95% confidence intervals (95% CI), with all
analyses performed in the statistical environment R (version
3.5.3; R Core Team 2020) with the survival
22
and survminer
23
packages.
Results
Patients
One hundred ninety-six patients were evaluated. Ten patients
did not test positive for SARS-CoV-2 during the hospitaliza-
tion period and were excluded from the analyses. Table 1
shows the demographic, biochemical, and clinical characteris-
tics of the patients. Overall, 86% (160 of 186) had a positive
PCR test for SARS-CoV-2 at the enrollment, and 42% had
computed tomography scan findings suggestive (i.e. pulmo-
nary commitment ≥50%) for COVID-19. All the remaining
Figure 1 Kaplan–Meier plot of time from hospital admission to hospital
discharge according to handgrip strength.
1874 S. Gil et al.
Journal of Cachexia, Sarcopenia and Muscle 2021; 12: 1871–1878
DOI: 10.1002/jcsm.12789

patients (26 of 186) had the diagnosis confirmed by serology
assay (ELISA) to detect IgG against SARS-CoV-2 at some point
during the hospital stay. The sample comprised patients of
both sexes (50% male) with a mean (SD) age of 59 years
(±15) and a body mass index of 29.5 kg/m
2
(±6.9). The prev-
alence of current smoking patients was 24.7%, and more
prevalent coexisting conditions were hypertension (67.7%),
obesity (40.9%), and type 2 diabetes (36.0%).
The signs and symptoms more commonly observed at ad-
mission were dyspnoea (81.2%), cough (64.4%), fever
(57.5%), myalgia (26.9%), fatigue (25.3%), headache (22.0%),
anosmia (19.9%), diarrhoea (17.7%), dysgeusia (17.2%), nau-
sea (11.3%), abdomen pain (10.2%), chest pain (10.2%),
vomiting (9.7%), runny nose (9.1%), earache (4.3%), and dizzi-
ness (1.1%). Mean (SD) LOS was 8.6 days (7.7); 17.0% of the pa-
tients required intensive care; 3.8% used invasive mechanical
ventilation; and 6.6% died during the hospitalization period.
Primary outcome
The crude HR for time from hospital admission to discharge
was greatest for handgrip strength comparing the strongest
versus other patients (1.47 [95% CI: 1.07–2.03; P= 0.019]).
Evidence of an association between increased handgrip
strength and shorter hospital stay was also identified
when handgrip strength was standardized according
to the sex-specific mean and standard deviation
(1.23 [95% CI: 1.06–1.43; P= 0.007). The magnitude
of these associations remained consistent and
statistically significant after adjusting for other covariates
(Figure 1). Mean LOS was shorter for the strongest
patients (7.5 ± 6.1 days) versus others (9.2 ± 8.4 days)
(Table 2).
Similar results and evidence of associations were also pres-
ent for vastus lateralis cross-sectional area. The crude HR
identified shorter hospital stay for patients with greater
sex-specific standardized values (1.20 [95% CI: 1.03–1.39;
P= 0.016). Evidence was also obtained associating longer
hospital stays for patients with the lowest values for vastus
lateralis cross-sectional area (0.63 [95% CI: 0.46–0.88;
P= 0.006). The magnitude of these associations remained
consistent and statistically significant after adjusting for other
covariates (Figure 2). Mean LOS for the patients with the low-
est muscle cross-sectional area was longer (10.8 ± 8.8 days)
versus others (7.7 ± 7.2 days) (Table 2).
Table 2 Crude and adjusted hazard ratio (HR) for hospital length of stay in surviving patients
Crude HR (95% CI) Pvalue Adjusted HR (95% CI) Pvalue
Sex
Male 1 (ref) 1 (ref)
Female 0.82 (0.60–1.10) 0.186 0.81 (0.59–1.13) 0.216
Age, years
18–35 years 1 (ref) 1 (ref)
36–55 years 0.69 (0.37–1.29) 0.239 0.70 (0.36–1.37) 0.299
≥56 years 0.63 (0.35–1.15) 0.132 0.64 (0.34–1.20) 0.164
Oxygen support at admission
0–4 L 1 (ref) 1 (ref)
5–9 L 1.42 (0.92–2.19) 0.111 1.34 (0.85–2.11) 0.210
≥10 L 1.08 (0.63–1.84) 0.787 0.96 (0.54–1.72) 0.897
Obesity
BMI <30 1 (ref) 1 (ref)
BMI ≥30 1.1 (0.80–1.47) 0.619 1.04 (0.66–1.30) 0.802
Type 2 diabetes
Yes 1 (ref) 1 (ref)
No 0.93 (0.67–1.28) 0.637 0.93 (0.66–1.30) 0.667
Handgrip strength: High vs. Other
Other 1 (ref) 1 (ref)
High 1.47 (1.07–2.03) 0.019* 1.48 (1.05–2.09) 0.024*
CSA
VL
: High vs. Other
Other 1 (ref) 1 (ref)
High 1.05 (0.76–1.45) 0.770 0.88 (0.59–1.32) 0.534
Handgrip strength: Low vs. Other
Other 1 (ref) 1 (ref)
Low 0.90 (0.65–1.24) 0.510 0.94 (0.66–1.33) 0.713
CSA
VL
: Low vs. Other
Other 1 (ref) 1 (ref)
Low 0.63 (0.46–0.88) 0.006** 0.59 (0.40–0.87) 0.007**
Handgrip strength: Standardized 1.23 (1.06–1.43) 0.007** 1.26 (1.07–1.48) 0.005**
CSA
VL
: Standardized 1.20 (1.03–1.39) 0.016* 1.24 (1.03–1.50) 0.023*
CSA
VL
, vastus lateralis cross-sectional area.
The Cox proportional hazards model was adjusted by sex (male or female), age (18–35, 36–55, or ≥56 years), oxygen support at admission
(0–4L,5–10 L, and ≥10 L), obesity (BMI <30 and BMI >30), and type 2 diabetes (yes or no).
*
P<0.05.
**
P<0.01.
Muscle parameters as predictors of length of stay in COVID-19 1875
Journal of Cachexia, Sarcopenia and Muscle 2021; 12: 1871–1878
DOI: 10.1002/jcsm.12789

Discussion
In this prospective observational study, we found muscle
strength (as assessed by handgrip) and muscle mass (as
assessed by vastus lateralis cross-sectional area) are predic-
tive of LOS in hospitalized patients with moderate to severe
COVID-19. To the best of our knowledge, this is the first study
to demonstrate the prognostic value of these skeletal muscle
parameters in this disease.
A recent study demonstrated that the Clinical Frailty Score
(CFS) independently predicted time to medical discharge and
mortality in COVID-19 patients.
20
Despite the value of these
findings, it is noteworthy that the CFS is a judgement-based
frailty tool that relies highly on experience and training for
proper categorization of the patients. Moreover, CFS is ulti-
mately an indirect measure of functional status and is mainly
used in geriatric patients. These are factors that might limit
the reliability of CFS in real-life clinical scenarios. Conversely,
handgrip strength is a simple, direct, easy handling, low-cost
measurement commonly utilized in the clinical setting as an
indicator of the general health status in individuals across a
wide age range. Indeed, handgrip strength assessed at hospi-
tal admission have been shown to be a predictive measure of
LOS and mortality in distinct populations.
7–11
Our findings ex-
tend this knowledge to patients admitted into the hospital
with acute COVID-19 symptoms, by showing that stronger pa-
tients had lower LOS than their weaker counterparts.
Muscle mass is also considered as an indicator of general
health status.
24,25
Previous studies have suggested that low
muscle mass (assessed by mid-arm circumference, calf cir-
cumference, and estimated by anthropometric equations)
may predict mortality among elderly.
24,25
In the current
study, we directly assessed, in the point-of-care, vastus
lateralis cross-sectional area using ultrasonography among
patients with COVID-19. Our findings suggest that low muscle
mass could contribute to higher LOS among COVID-19 pa-
tients. During a critical illness, net breakdown of muscle pro-
tein is stimulated to provide abundant amino acids to meet
these increased demands of tissues such as immune cells
and liver.
14
In this context, patients with limited muscle mass
reserves would presumably be more vulnerable to stress fac-
tors, such as severe burn injuries and cancer.
26,27
The present
findings suggest that this could be the case of COVID-19.
Muscle mass plays a key role in recovery from critical ill-
ness, whereas muscle strength and function are key to the re-
covery process.
12
If there is a preexisting deficiency of muscle
mass before the onset of an acute illness, one may speculate
that the expected loss of muscle mass and function associ-
ated with hospitalization may push the patient over a thresh-
old that makes recovery of normal function unlikely to ever
occur.
12
The impact of this physiopathological mechanism
on long-term effects of COVID-19 (long COVID) remains to
be explored.
Limitations
First, the longitudinal design of this study does not allow
causative conclusions. Second, although this study was ade-
quately powered to detect changes in the selected outcomes,
this was still a small cohort composed by patients with het-
erogeneous clinical features, medication regimen and disease
manifestations, possibly subject to unmeasured confounders.
While the Cox proportional hazards models were controlled
for several potentially confound variables, direct sub-group
comparisons were not possible due to sample size con-
straints. Third, our results are confined to patients with mod-
erate to severe COVID-19 and should be read with care
regarding other clinical settings. Finally, the minimal clinically
important difference in LOS among patient with COVID-19 is
yet unknown, which limits the ability to make clinical infer-
ences about the present findings.
Figure 2 Kaplan–Meier plot of time from hospital admission to hospital
discharge according to vastus lateralis cross-sectional area.
1876 S. Gil et al.
Journal of Cachexia, Sarcopenia and Muscle 2021; 12: 1871–1878
DOI: 10.1002/jcsm.12789

Conclusions
Muscle strength and mass assessed on hospital admission are
predictors of LOS in patients with COVID-19. While it is un-
known whether these muscular parameters add to the prog-
nostic value provided by the more established and accepted
predictors that already have been identified,
28
the present
data suggest that muscle health may benefit patients with
moderate to severe COVID-19. The evidence provided by this
study paves the way for randomized controlled trials to test
the utility of preventive or in-hospital interventions in short-
ening LOS among these patients through improving muscle
mass and/or function.
Acknowledgements
The authors are thankful to the task force of HCFMUSP
COVID-19 Study Group: Rosemeire Keiko, Danielle Pedroni
de Moraes, Renato Madrid Baldassare, Antônio José Pereira,
Elizabeth de Faria, Gisele Pereira, Lucila Pedroso da Cruz,
Marcelo, Cristiano de Azevedo Ramos, and Vilson
Cobello Junior.
Conflict of interest
The authors have declared that no conflict of interest exists.
Funding
The authors acknowledge the support by Coordenação de
Aperfeiçoamento de Pessoal de Nível Superior (CAPES -
PROEX), the Brazilian National Council for Scientific and
Technological Development (CNPq, grant 301571/2017-1).
S.G., H.R., and B.G. are supported by grants from the
Conselho Nacional de Pesquisa e Desenvolvimento (CNPq,
166622/2020-6; 428242/2018-9; and 301914/2017-6). B.G.
and S.G. is also supported by a grant from the Sao Paulo
Research Foundation (FAPESP 2017/13552-2; 2020/08091-9).
References
1. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He
JX, et al. Clinical Characteristics of Corona-
virus Disease 2019 in China. N Engl J Med
2020;382:1708–1720.
2. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y,
et al. Clinical features of patients
infected with 2019 novel coronavirus
in Wuhan, China. Lancet 2020;395:
497–506.
3. Richardson S, Hirsch JS, Narasimhan M,
Crawford JM, McGinn T, Davidson KW,
et al. Presenting Characteristics, Comorbid-
ities, and Outcomes Among 5700 Patients
Hospitalized With COVID-19 in the New
York City Area. JAMA 2020;323:2052–2059.
4. Brandt C, Pedersen BK. The role of
exercise-induced myokines in muscle ho-
meostasis and the defense against chronic
diseases. J Biomed Biotechnol 2010;2010:
520258.
5. Egan B, Zierath JR. Exercise metabolism
and the molecular regulation of skeletal
muscle adaptation. Cell Metab 2013;17:
162–184.
6. Lightfoot A, McArdle A, Griffiths RD. Mus-
cle in defense. Crit Care Med 2009;37:
S384–S390.
7. Burtin C, Bezuidenhout J, Sanders KJC,
Dingemans AC, Schols A, Peeters STH,
et al. Handgrip weakness, low fat-free
mass, and overall survival in non-small cell
lung cancer treated with curative-intent ra-
diotherapy. J Cachexia Sarcopenia Muscle
2020;11:424–431.
8. Mendes J, Azevedo A, Amaral TF. Handgrip
strength at admission and time to dis-
charge in medical and surgical inpatients.
JPEN J Parenter Enteral Nutr
2014;38:481–488.
9. Moisey LL, Mourtzakis M, Cotton BA,
Premji T, Heyland DK, Wade CE, et al. Skel-
etal muscle predicts ventilator-free days,
ICU-free days, and mortality in elderly ICU
patients. Crit Care 2013;17:R206.
10. Zhuang CL, Zhang FM, Li W, Wang KH, Xu
HX, Song CH, et al. Associations of low
handgrip strength with cancer mortality: a
multicentre observational study. J Cachexia
Sarcopenia Muscle 2020;11:1476–1486.
11. Konishi M, Akiyama E, Matsuzawa Y, Sato
R, Kikuchi S, Nakahashi H, et al. Prognostic
impact of muscle and fat mass in patients
with heart failure. J Cachexia Sarcopenia
Muscle 2021;12:568–576.
12. Wolfe RR. The underappreciated role of
muscle in health and disease. Am J Clin
Nutr 2006;84:475–482.
13. Fajgenbaum DC, June CH. Cytokine Storm.
N Engl J Med 2020;383:2255–2273.
14. Wolfe RR, Martini WZ. Changes in interme-
diary metabolism in severe surgical illness.
World J Surg 2000;24:639–647.
15. Zhang XJ, Chinkes DL, Cox RA, Wolfe RR.
The flow phase of wound metabolism is
characterized by stimulated protein syn-
thesis rather than cell proliferation. J Surg
Res 2006;135:61–67.
16. von Haehling S, Morley JE, Coats AJS, Anker
SD. Ethical guidelines for publishing in the
Journal of Cachexia, Sarcopenia and Mus-
cle: update 2019. J Cachexia Sarcopenia
Muscle 2019;10:1143–1145.
17. NIH. Coronavirus disease 2019 (COVID-19)
treatment guidelines. National Institutes
of Health, U.S. Department of Health and
Human Services. 2020. https://www.
covid19treatmentguidelines.nih.gov/
18. Lixandrao ME, Damas F, Chacon-Mikahil
MP, Cavaglieri CR, Ugrinowitsch C, Bottaro
M, et al. Time Course of Resistance
Training-Induced Muscle Hypertrophy in
the Elderly. J Strength Cond Res
2016;30:159–163.
19. Riley RD, Snell KI, Ensor J, Burke DL, Harrell
FE Jr, Moons KG, et al. Minimum sample size
for developing a multivariable prediction
model: PART II - binary and time-to-event
outcomes. Stat Med 2019;38:1276–1296.
20. Hewitt J, Carter B, Vilches-Moraga A, Quinn
TJ, Braude P, Verduri A, et al. The effect of
frailty on survival in patients with
COVID-19 (COPE): a multicentre, European,
observational cohort study. Lancet Public
Health 2020;5:e444–e451.
21. Kerr A, Syddall HE, Cooper C, Turner GF,
Briggs RS, Sayer AA. Does admission grip
strength predict length of stay in
hospitalised older patients? Age Ageing
2006;35:82–84.
22. Therneau T. A Package for Survival Analysis
in R. R Package Version 3.1–12. 2020.
Accessed 11 June 2020.
23. Kassambara A, Kosinski M, Biecek P.
Survminer: Drawing Survival Curves
Using’Ggplot2’. R PackageVersion 0.4.6.
2020. Accessed 11 June 2020.
24. Wang H, Hai S, Liu Y, Liu Y, Dong B. Skeletal
Muscle Mass as a Mortality Predictor
among Nonagenarians and Centenarians:
A Prospective Cohort Study. Sci Rep
2019;9:2420.
Muscle parameters as predictors of length of stay in COVID-19 1877
Journal of Cachexia, Sarcopenia and Muscle 2021; 12: 1871–1878
DOI: 10.1002/jcsm.12789

25. Weng CH, Tien CP, Li CI, L’Heureux A, Liu
CS, Lin CH, et al. Mid-upper arm circumfer-
ence, calf circumference and mortality in
Chinese long-term care facility residents:
a prospective cohort study. BMJ Open
2018;8:e020485.
26. Kadar L, Albertsson M, Areberg J, Landberg
T, Mattsson S. The prognostic value of
body protein in patients with lung cancer.
Ann N Y Acad Sci 2000;904:584–591.
27. Pereira CT, Barrow RE, Sterns AM, Hawkins
HK, Kimbrough CW, Jeschke MG, et al. Age-
dependent differences in survival after se-
vere burns: a unicentric review of 1,674 pa-
tients and 179 autopsies over 15 years. J
Am Coll Surg 2006;202:536–548.
28. Wongvibulsin S, Garibaldi BT, Antar AAR,
Wen J, Wang MC, Gupta A, et al.
Development of Severe COVID-19 Adaptive
Risk Predictor (SCARP), a Calculator
to Predict Severe Disease or Death
in Hospitalized Patients With COVID-19.
Ann Intern Med 2021;174:777–785.
1878 S. Gil et al.
Journal of Cachexia, Sarcopenia and Muscle 2021; 12: 1871–1878
DOI: 10.1002/jcsm.12789