Current issues and trends in Respiratory therapy - Applied Sciences
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Clinical Characteristics, Respiratory Mechanics, and Outcomes in
Critically Ill Individuals With COVID-19 Infection in an Underserved
Urban Population
Siddique Chaudhary, Sadia Benzaquen, Jessica G Woo, Jack Rubinstein, Atul Matta, Jeri Albano,
Robert De Joy III, Kevin Bryan Lo, and Gabriel Patarroyo-Aponte
BACKGROUND: The COVID-19 outbreak in the United States has disproportionately affected
Black individuals, but little is known about the factors that underlie this observation. Herein, we
describe these associations with mortality in a largely minority underserved population.
METHODS: This single-center retrospective observational study included all adult subjects with
laboratory-confirmed SARS-Cov-2 treated in our ICU between March 15 and May 10, 2020.
RESULTS: 128 critically ill adult subjects were included in the study (median age 68 y [interquar-
tile range 61–76], 45% female, and 64% Black); 124 (97%) required intubation. Eighty (63%) sub-
jects died during their in-patient stay, which did not differ by race/ethnicity. Compared with other
racial/ethnic groups, Blacks had a greater proportion of women (52% vs 30%, P 5 .02) and sub-
jects with hypertension (91% vs 78%, P 5 .035). Asthma (P 5 .03) was associated with lower in-
patient death, primarily among Black subjects (P 5 .02). Among Black subjects, increased age
(odds ratio 1.06 [95% CI 1.05–1.22] per year), positive fluid balance (odds ratio 1.06 [95% CI 1.01–
1.11] per 100 mL), and treatment with tocilizumab (odds ratio 25.0 [95% CI 3.5–180]) were inde-
pendently associated with in-patient death, while higher platelets (odds ratio 0.65 [95% CI 0.47–
0.89] per 50 3 103/mL) and treatment with intermediate dose anticoagulants (odds ratio 0.08 [95%
CI 0.02–0.43]) were protective. Among other race/ethnic groups, higher total bilirubin (odds ratio
1.75 [95% CI 0.94–3.25] per 0.2 mg/dL) and higher maximum lactate (odds ratio 1.43 [95% CI
0.96–2.13] per mmol/L) were marginally associated with increased death, while tocilizumab treat-
ment was marginally protective (odds ratio 0.24 [95% CI 0.05–1.25]). During first 72 h of ventila-
tion, those who died had less increase in PaO2=FIO2 (P 5 .046) and less reduction in PEEP (P 5 .01)
and FIO2 requirement (P 5 .002); these patterns did not differ by race/ethnicity. CONCLUSIONS:
Black and other race/ethnicity subjects had similar mortality rates due to COVID-19 but dif-
fered in factors that were associated with increased risk of death. In both groups, subjects who
died were older, had a positive fluid balance, and less improvement in PaO2=FIO2, PEEP, and
FIO2 requirement on ventilation. Key words: COVID-19; coronavirus; outcomes. [Respir Care
2021;66(6):897–908. © 2021 Daedalus Enterprises]
Introduction
In December 2019, Wuhan Province in China reported
an alarming number of cases presenting with respiratory ill-
ness that was caused by a novel coronavirus subsequently
named SARS-CoV-2.1,2 The clinical manifestation of infec-
tion by this virus is known as coronavirus disease 2019
(COVID-19), and as of this writing has resulted in > 28
million cases in the United States and > 500,000 deaths,
with Black individuals representing a significant portion of
the observed morbidity and mortality (55 deaths per
100,000).3,4
Significantly increased risk of death has been reported in
the elderly, in those with prior comorbid conditions,5,6 and
in patients requiring management in the ICU and mechani-
cal ventilation.3 Despite concentrated efforts in obtaining
novel therapeutic possibilities for these patients, the vast
majority of trials have failed to conclusively demonstrate
improved outcomes secondary to pharmaceutical interven-
tions, though clinical variables and ventilatory support have
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 897
been shown to have prognostic and possibly therapeutic
value.5,6
COVID-19 has disproportionately affected the Black
community in the United States.4 As of July 10, 2020, de-
mographic data collected by the Centers for Disease
Control and Prevention (CDC) from > 250 hospitals in
the COVID-19-associated Hospitalization Surveillance
Network for the week ending in June 27, 2020, 32.5%
of the hospitalized subjects were Black.3 Furthermore,
data from the CDC indicate that 23% of reported deaths
in the United States are Black, compared with 17%
Black in the general population (weighted population
distribution taking into account where deaths occurred),
and the rate is more than twice that of whites (55 deaths
per 100,000 versus 23 deaths per 100,000).4 Whether
there are racial/ethnic differences in risk factors for
death or response to treatment for COVID-19, however,
is not well understood.
In this study we report on the clinical characteristics
of a largely underserved, racially/ethnically diverse
population in a large urban center on the East Coast of
the United States and present key clinical and ventila-
tory characteristics associated with improved outcomes
in our population.
Methods
This is a single-center retrospective case series of all
ICU subjects admitted to the hospital who were diag-
nosed with COVID-19. The study was carried out at a
700-bed, tertiary care, academic medical center with a
28-bed medical ICU and a surge capacity of 60 ICU
beds during the COVID-19 pandemic. Subjects from
both medical and surgical ICUs were included. The
hospital primarily serves the neighboring communities
with a culturally and ethnically diverse population of
59% Black, 23% Hispanic, 12% white, and 4% Asian.
Almost half of the adults (45.1%) had a family income
of # $26,200, and 68% had a family income of #
$50,800. More than 80% of discharges are covered by
Medicare/Medicaid. We studied all adult subjects with
a confirmed SARS-CoV-2 polymerase chain reaction
test who were treated in the ICU between March 15 and
May 10, 2020. During this surge period, we only admit-
ted patients to the ICU if they required intubation,
while the patients on high-flow nasal cannula or CPAP
were managed on the step-down unit by our pulmonol-
ogists. Patients with incomplete data in terms of the
main clinical outcomes and demographics were
excluded from the study. The study was approved by
the hospital institutional review board, who deemed it
to be low risk and waived the requirement for informed
consent. Data were collected from the electronic medi-
cal records using International Classification of
Disease 9–10 codes. Subjects who presented with char-
acteristic symptoms were tested for COVID-19. A total
of 673 subjects were admitted to our hospital with con-
firmed COVID infection; of these subjects, 128 were
managed in the ICU during this time. We collected de-
mographic data, presenting comorbidities, laboratory
values and novel therapies used for COVID-19, and
mortality and hospital discharge data from the medical
record. Respiratory and hemodynamic values were col-
lected at baseline and at 24, 48, and 72 h.
Drs Chaudhury, Benzaquen, Matta, and Patarroyo-Aponte are affiliated
with the Division of Pulmonary and Critical Care and Sleep Medicine,
Einstein Medical Center, Philadelphia, Pennsylvania. Drs Benzaquen
and Patarroyo-Aponte are affiliated with the Department of Medicine,
Einstein Medical Center, Philadelphia, Pennsylvania. Drs Benzaquen,
Albano, De Joy, Lo, and Patarroyo-Aponte are affiliated with the Sidney
Kimmel College, Thomas Jefferson University, Philadelphia, Pennsylvania.
Dr Woo is affiliated with the Department of Pediatrics, University of
Cincinnati College of Medicine, Cincinnati, Ohio. Dr Woo is affiliated
with the Division of Biostatistics and Epidemiology, Cincinnati
Children’s Hospital Medical Center, Cincinnati, Ohio. Dr Rubinstein is
affiliated with the Department of Internal Medicine, University of
Cincinnati College of Medicine, Cincinnati, Ohio.
The authors have disclosed no conflicts of interest.
Correspondence: Siddique Chaudhary MD, Einstein Medical Center,
Philadelphia, 5501 Old York Road Philadelphia PA 19141. E-mail:
[email protected]
DOI: 10.4187/respcare.08319
QUICK LOOK
Current knowledge
COVID-19 is a highly inflammatory viral disease and
since the start of the pandemic data has shown that the
outcomes in Black and underserved populations is
poor. There have been clinical and epidemiological
research in China, European countries and USA that
have described this clinical entity but little is known of
its effect on the Black population.
What This Paper contributed to Our Knowledge
In our cohort of predominantly Black subjects, we
found out that the mortality was high in patients who
are on mechanical ventilation, elderly patients with
comorbid conditions, and a positive fluid balance 48
h post intubation. We did not find any differences in
outcomes by race, although there was a slightly
higher mortality in Black individuals.
SEE THE RELATED EDITORIAL ON PAGE 1041
COVID-19 IN AN UNDERSERVED AREA
898 RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6
mailto:[email protected]
Statistical Analysis
Clinical and demographic data were evaluated relative
to the primary end point, in-patient death, overall, and
by race/ethnicity (Black versus white/Hispanic/other).
Unadjusted medians with interquartile ranges (IQR) were
obtained with non-parametric Kruskal-Wallis tests, while
number (percent) were obtained using chi-square or Fisher
exact tests, as appropriate. Multivariable logistic regression
was conducted to determine independent associations of
clinical, demographic, and treatment variables with in-
patient death, testing any variable with unadjusted P # .20
and with data available for at least 80% of subjects; elimi-
nation of variables was conducted sequentially by eliminat-
ing the least significant terms or most unstable odds ratio
estimates.
Longitudinal changes in respiratory parameters during
the first 72 h of ventilation were tested using mixed model-
ing, accounting for correlated measurements within person.
All models of respiratory parameters were adjusted for age,
race, sex, body mass index, and total days on the ventilator,
with the main discriminating variables being time (0, 24,
48, or 72 h after intubation) and in-patient death versus
survival. Linear trends were tested using time as a continu-
ous variable. Interactions of in-patient death or Black race
with time were also used to test for differences in change in
respiration parameters over time by race and outcome. For
all analyses, significant values are reported if P < .05 or if
inclusion of a term in the model improved model fit, using
reductions in –2 log-likelihood values $ 4 as evidence of a
better fitting model.
Results
One hundred twenty-eight subjects with laboratory-con-
firmed COVID-19 were admitted to the ICU. Intubation was
deemed necessary in 124 (97%) subjects. Demographic and
clinical characteristics are summarized in Table 1. Median
age was 68 y (IQR 61–75.5], and 57 (45%) were female.
Blacks represented 64% of the population and had a likeli-
hood of survival of 35% in comparison to 41% of the remain-
ing population; this difference was not statistically significant
(P ¼ .57). Overall, 83 (63%) subjects died while admitted.
Subjects who died in the hospital were a median of 6 y older
than those who did not (median age 64 vs 70, P ¼ .02); this
was statistically significant only in Black subjects (P ¼ .006).
Nearly all subjects had bilateral infiltrates upon admis-
sion (96%; Table 1). Cardiovascular comorbidities were
extremely common (88%), particularly hypertension (87%),
followed by diabetes (57%) and respiratory comorbidities
(32%). Two or more comorbidities were seen in 78% of sub-
jects. Despite a high proportion of subjects with history of
hypertension, diabetes, and coronary artery disease, only
38% of subjects were being treated with renin angiotensin
aldosterone system inhibition (angiotensin-converting
enzyme inhibitors and angiotensin receptor blockers) prior to
admission. Of the comorbidities, only respiratory, particu-
larly asthma, were negatively associated with in-patient
death; respiratory comorbidities were present in 44% of sub-
jects discharged alive versus 25% of in-patients who died
(P ¼ .033), and asthma was present in 15% of subjects dis-
charged alive versus 3% of in-patients who died (P ¼ .03).
Asthma was associated to a greater extent in Blacks who
were discharged alive (21% vs 4%, P ¼ .02), whereas over-
all respiratory comorbidities were more prevalent in other
race/ethnicity groups discharged alive (42% vs 15%,
P ¼ .049). Medication use did not differ by in-patient
death.
Laboratory parameters associated with in-patient death
included higher procalcitonin (P ¼ .01), higher creatinine
(P ¼.004), lower fibrinogen (P ¼.003), lower platelets
(P ¼ .03), and longer partial thromboplastin time (P ¼
.009), along with marginally higher alkaline phospha-
tase (P ¼ .051) (Table 2). These differed somewhat by
race/ethnicity. Among Black subjects, only lower fibrino-
gen was significantly associated with in-patient death
(P ¼ .02), with higher procalcitonin (P ¼ .08), lower pla-
telets (P ¼ .057), and lower lactate dehydrogenase (P ¼
.09) marginally associated. More admission laboratory
values were associated with in-patient death among
white/Hispanic/other subjects: higher lactate (P ¼ .02),
higher creatinine (P ¼ .003), higher direct bilirubin (P ¼
.005), higher total bilirubin (P ¼ .006), higher lactate dehy-
drogenase (P ¼ .005), higher procalcitonin (P ¼ .02), and
higher partial thromboplastin time (P ¼ .033). Considering
maximum values recorded during the hospitalization, in-
patient death was associated with higher lactate (P < .001,
significant in both race/ethnic groups), higher ferritin
(P ¼.02, significant in Black subjects only), higher procalci-
tonin (P ¼ .001, significant in both race/ethnic groups),
lower fibrinogen (P ¼ .009, significant in Black subjects
only), and higher creatinine (P ¼ .02 for maximum within
the first week, significant in white/Hispanic/other group
only). Maximum C-reactive protein was also marginally
higher for those with in-patient death (P ¼ .07, in Black sub-
jects only).
Table 3 presents the treatments and clinical outcomes
and associations with in-patient death. Several medica-
tions were administered to these subjects, with the most
common being anticoagulants (98%), tocilizumab (71%),
and hydroxychloroquine (66%). Of all medications noted,
only steroids were associated with better outcomes (44%
among all patients discharged alive vs 26% in those with
in-patient death, P ¼ .041), but this association was not
significant in either race/ethnic group. Conversely, treat-
ment with remdesivir was associated with improved out-
comes in white/Hispanic/other subjects (P ¼ .01) but not
Black subjects (P > .99).
COVID-19 IN AN UNDERSERVED AREA
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 899
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.9
9
1
9
(6
6
)
3
2
(6
0
)
.8
1
9
(4
7
)
1
4
(5
2
)
>
.9
9
D
ia
b
e
te
s
7
3
(5
7
)
2
8
(5
8
)
4
5
(5
6
)
.8
6
1
9
(6
6
)
3
1
(5
8
)
.6
4
9
(4
7
)
1
4
(5
2
)
>
.9
9
H
IV
2
(2
)
0
(0
)
2
(3
)
.5
3
0
(0
)
2
(4
)
.5
4
0
(0
)
0
(0
)
N
A
C
o
m
o
rb
id
it
ie
s,
n
o
.
.2
3
.3
4
.4
3
0
6
(5
)
0
(0
)
6
(8
)
0
(0
)
3
(6
)
0
(0
)
3
(1
1
)
1
2
2
(1
7
)
9
(1
9
)
1
3
(1
6
)
3
(1
0
)
9
(1
7
)
6
(3
2
)
4
(1
5
)
2
3
9
(3
0
)
1
8
(3
8
)
2
1
(2
6
)
1
2
(4
1
)
1
4
(2
6
)
6
(3
2
)
7
(2
6
)
3
2
8
(2
2
)
1
1
(2
3
)
1
7
(2
1
)
8
(2
8
)
1
0
(1
9
)
3
(1
6
)
7
(2
6
)
4
+
3
3
(2
6
)
1
0
(2
1
)
2
3
(2
9
)
6
(2
1
)
1
7
(3
2
)
4
(2
1
)
6
(2
2
)
M
e
d
ic
a
ti
o
n
s
a
t
a
d
m
is
si
o
n
A
n
ti
p
la
te
le
ts
6
0
(4
7
)
2
1
(4
4
)
3
9
(4
9
)
.5
8
1
4
(4
8
)
2
8
(5
3
)
.8
2
7
(3
7
)
1
1
(4
1
)
>
.9
9
N
S
A
ID
s
8
(6
)
3
(6
)
5
(6
)
>
.9
9
3
(1
0
)
6
(9
)
>
.9
9
0
(0
)
0
(0
)
N
A
A
C
E
i/
A
R
B
4
9
(3
8
)
2
2
(4
6
)
2
7
(3
4
)
.1
7
1
3
(4
5
)
2
1
(4
0
)
.8
1
9
(4
7
)
6
(2
2
)
.1
1
(C
o
n
ti
n
u
e
d
)
COVID-19 IN AN UNDERSERVED AREA
900 RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6
Figure 1 presents longitudinal respiratory parameters for
subjects during the first 72 h of ventilation, adjusting for
age, sex, race, body mass index, and total days on the venti-
lator. PaO2=FIO2 generally increased over time (P < .001)
but increased earlier and to a greater degree in those dis-
charged alive (P ¼ .046). Similarly, FIO2 requirements
(P < .001) decreased significantly over time but
decreased earlier and more in those discharged alive
(P ¼ .002). PEEP decreased only in surviving subjects
(P ¼.03), while plateau pressure decreased significantly
for all subjects (P ¼ .008) but did not differ by outcome.
Mean arterial pressure and compliance did not change
materially during ventilation, as shown in Figure 2.
None of the respiratory or ventilation parameters dif-
fered by race/ethnicity (data not shown). As shown in
Table 3, positive fluid balance in the first 48 h of intu-
bation was also significantly associated with greater
mortality (P ¼ .007) but was significant only in Black
subjects (P ¼ .01).
The full respiratory parameters at admission and at intu-
bation are presented in Table 4. At admission, oxygen inter-
face was predominantly either nasal cannula (54%) or non-
rebreathing mask (36%), with marginal difference by in-
patient death (P ¼ .054). Those subjects with in-hospital
death presented with higher oxygen requirements at admis-
sion and prior to intubation. On intubation, the median
PaO2=FIO2 was 63 (IQR 50–105), PEEP was 10 cm H2O
(IQR 7–10), plateau pressure was 25 cm H2O (IQR 22–30),
and compliance was 26 mL/cm H2O (IQR 21–33) (Table 4).
None of these values were significantly different between
survivors and in-patient deaths. Early intubation (defined as
within the first 2 d of hospitalization), prone positioning, air-
way pressure release ventilation, and vasodilator therapy
were not associated with in-patient death. Extubation was
successful in 35 subjects (29%), of whom 31 (89%) were
subsequently discharged alive (P < .001).
Because of differences in patient profiles by
race/ethnicity group, logistic regression models were
developed separately by race, testing variables with
unadjusted P # .20 (Fig. 3). Among Black subjects,
higher age (odds ratio [OR] 1.13 [95% CI 1.05–1.22]
per additional year of age, P ¼ .002), positive fluid bal-
ance (OR 1.06 [95% CI 1.02–1.11] per 100 mL, P ¼
.008), and tocilizumab treatment (OR 25 [95% CI 3.5–
180]) were independently associated with risk of in-
patient death, while a higher platelet count (OR 0.65
[95% CI 0.47–0.89] per 50,000/mL, P ¼ .008), and in-
termediate dose anticoagulation (OR 0.08 [95% CI
0.02–0.43]) were associated with improved outcomes.
Among white/Hispanic/other subjects, marginally asso-
ciated risk factors included higher total bilirubin at
admission (OR 1.75 [95% CI 0.93–3.25], P ¼ .08) and
higher maximum lactate (OR 1.43 [95% CI 0.96–2.13],
P ¼ .08), while tocilizumab treatment was marginallyTa
b
le
1
.
C
o
n
ti
n
u
e
d
O
v
e
ra
ll
A
ll
S
u
b
je
c
ts
B
la
c
k
W
h
it
e
/H
is
p
a
n
ic
/O
th
e
r
D
is
c
h
a
rg
e
d
A
li
v
e
In
-H
o
sp
it
a
l
D
e
a
th
P
D
is
c
h
a
rg
e
d
A
li
v
e
In
-H
o
sp
it
a
l
D
e
a
th
P
D
is
c
h
a
rg
e
d
A
li
v
e
In
-H
o
sp
it
a
l
D
e
a
th
P
N
o
v
e
l
a
n
ti
c
o
a
g
u
la
n
ts
1
3
(1
0
)
5
(1
0
)
8
(1
0
)
.9
4
1
(3
)
4
(8
)
.6
5
4
(2
1
)
4
(1
5
)
.7
0
H
e
p
a
ri
n
7
(5
)
3
(6
)
4
(5
)
.7
6
3
(1
0
)
3
(6
)
.6
6
0
(0
)
1
(4
)
>
.9
9
S
ta
ti
n
s
7
4
(5
8
)
3
0
(6
3
)
4
4
(5
5
)
.4
1
1
7
(5
9
)
3
1
(5
8
)
>
.9
9
1
3
(6
8
)
1
3
(4
8
)
.2
3
P
re
d
n
is
o
n
e
8
(6
)
3
(6
)
5
(6
)
>
.9
9
2
(7
)
4
(8
)
>
.9
9
1
(5
)
1
(4
)
>
.9
9
M
e
d
ic
a
ti
o
n
s,
n
o
.
.4
2
.2
2
.4
2
0
1
9
(1
5
)
5
(1
0
)
1
4
(1
8
)
3
(1
0
)
6
(1
1
)
2
(1
1
)
8
(2
9
)
1
3
9
(3
0
)
1
5
(3
1
)
2
4
(3
0
)
1
0
(3
4
)
1
7
(3
2
)
5
(2
6
)
7
(2
6
)
2
3
9
(3
0
)
1
7
(3
5
)
2
2
(2
8
)
9
(3
1
)
1
3
(2
5
)
8
(4
2
)
9
(3
3
)
3
2
2
(1
7
)
6
(1
3
)
1
6
(2
0
)
3
(1
0
)
1
5
(2
8
)
3
(1
6
)
1
(4
)
4
9
(7
)
5
(1
0
)
4
(5
)
4
(1
4
)
2
(4
)
1
(5
)
2
(7
)
D
a
ta
a
re
p
re
se
n
te
d
a
s
n
(%
)
o
r
m
e
d
ia
n
(i
n
te
rq
u
a
rt
il
e
ra
n
g
e
).
B
M
I
¼
b
o
d
y
m
a
ss
in
d
e
x
N
A
¼
n
o
t
a
v
a
il
a
b
le
E
S
R
D
¼
e
n
d
-s
ta
g
e
re
n
a
l
d
is
e
a
se
H
IV
¼
h
u
m
a
n
im
m
u
n
o
d
e
fi
c
ie
n
c
y
v
ir
u
s
N
S
A
ID
¼
n
o
n
st
e
ro
id
a
l
a
n
ti
-i
n
fl
a
m
m
a
to
ry
d
ru
g
A
C
E
i/
A
R
B
¼
a
n
g
io
te
n
si
n
-c
o
n
v
e
rt
in
g
e
n
z
y
m
e
in
h
ib
it
o
rs
a
n
d
a
n
g
io
te
n
si
n
re
c
e
p
to
r
b
lo
c
k
e
rs
COVID-19 IN AN UNDERSERVED AREA
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 901
T
a
b
le
2
.
L
a
b
o
ra
to
ry
P
a
ra
m
e
te
rs
o
f
IC
U
S
u
b
je
c
ts
W
it
h
C
O
V
ID
-1
9
a
n
d
A
ss
o
c
ia
ti
o
n
s
W
it
h
In
-P
a
ti
e
n
t
D
e
a
th
b
y
R
a
c
e
/E
th
n
ic
it
y
O
v
e
ra
ll
A
ll
S
u
b
je
c
ts
B
la
c
k
W
h
it
e
/H
is
p
a
n
ic
/O
th
e
r
D
is
c
h
a
rg
e
d
A
li
v
e
In
-H
o
sp
it
a
l
D
e
a
th
P
D
is
c
h
a
rg
e
d
A
li
v
e
In
-H
o
sp
it
a
l
D
e
a
th
P
D
is
c
h
a
rg
e
d
A
li
v
e
In
-H
o
sp
it
a
l
D
e
a
th
P
A
d
m
is
si
o
n
la
b
o
ra
to
ry
p
a
ra
m
e
te
rs
A
lk
a
li
n
e
p
h
o
sp
h
a
ta
se
,
IU
/L
8
2
(6
7
–
1
1
5
)
7
8
(6
5
–
9
2
)
8
5
(7
2
–
1
3
1
)
.0
5
1
7
8
(6
1
–
9
7
)
8
2
.5
(7
2
.5
–
1
1
4
)
.1
3
7
8
(6
5
–
9
2
)
9
6
.5
(7
2
–
1
5
7
)
.1
4
A
la
n
in
e
a
m
in
o
tr
a
n
sf
e
ra
se
,
IU
/L
2
7
(1
8
–
4
9
)
2
6
.5
(1
8
–
4
2
)
3
1
.5
(1
8
–
5
2
)
.4
9
2
6
(1
8
–
4
2
)
2
5
.5
(1
6
–
4
8
.5
)
.8
5
3
0
(1
3
–
4
2
)
4
2
(2
0
–
5
9
)
.1
1
A
sp
a
rt
a
te
a
m
in
o
tr
a
n
sf
e
ra
se
,
IU
/L
4
5
.5
(2
9
.5
–
7
4
)
4
3
(3
2
–
5
4
)
4
6
(2
9
–
8
1
)
.2
4
3
7
(3
2
–
7
1
)
4
6
(2
8
.5
–
7
7
.5
)
.7
1
4
9
(2
7
–
5
4
)
5
3
(3
1
–
8
8
)
.1
4
W
h
it
e
b
lo
o
d
c
e
ll
c
o
u
n
t,
1
0
3
/m
L
8
,3
8
0
(6
,1
5
5
–
1
2
,9
4
5
)
8
,9
9
5
(6
,5
6
0
–
1
3
,1
4
5
)
8
,1
7
0
(5
,8
7
5
–
1
2
,6
1
5
)
.5
1
1
0
,1
2
0
(7
,0
1
0
–
1
3
,0
6
0
)
7
,8
8
0
(5
,7
2
0
–
1
2
,4
0
0
)
.3
0
8
,5
7
0
(5
,2
2
0
–
1
3
,2
3
0
)
8
,9
3
0
(6
,1
9
0
–
1
2
,8
3
0
)
.8
8
N
e
u
tr
o
p
h
il
,
%
8
0
.1
(7
0
.8
–
8
4
.9
)
7
8
.8
(7
0
.6
–
8
5
.2
)
8
0
.5
(7
0
.8
–
8
4
.9
)
.6
0
7
5
.5
(6
2
.9
–
8
4
.5
)
8
0
.6
(6
9
.0
–
8
5
.0
)
.2
3
8
1
.8
(7
3
,7
–
8
6
.8
)
8
0
.5
(7
8
.0
–
8
4
.4
)
.4
8
L
y
m
p
h
o
c
y
te
,
%
9
.8
(6
.5
–
1
5
.9
)
8
.6
5
(6
.5
–
1
6
.1
)
1
0
.1
(6
.3
–
1
5
.9
)
.6
5
8
.5
(7
.0
–
1
6
.7
)
1
0
.8
(7
.4
–
1
6
.1
)
.6
0
8
.8
(6
.1
–
1
5
.1
)
9
.3
(5
.3
–
1
2
.6
)
.9
6
B
a
n
d
s,
%
0
(0
–
2
.6
)
0
(0
–
1
)
0
(0
–
6
)
.3
5
0
(0
–
3
.1
)
0
(0
–
3
.1
)
.8
8
0
(0
–
0
)
0
(0
–
1
2
.5
)
.0
7
T
ro
p
o
n
in
,
n
g
/m
L
0
.0
4
(0
.0
2
–
0
.1
2
)
0
.0
4
(0
.0
1
–
0
.1
2
)
0
.0
4
(0
.0
2
–
0
.1
5
)
.2
1
0
.0
4
(0
.0
1
–
0
.1
4
)
0
.0
4
(0
.0
2
–
0
.1
2
)
.7
3
0
.0
4
(0
.0
1
–
0
.0
7
)
0
.0
5
(0
.0
3
–
0
.2
8
)
.1
5
L
a
c
ta
te
,
m
m
o
l/
L
1
.8
0
(1
.2
9
–
3
.0
0
)
1
.8
0
(1
.2
0
–
2
.4
0
)
1
.8
2
(1
.3
3
–
3
.2
8
)
.1
4
1
.8
7
(1
.4
1
–
2
.5
0
)
1
.8
(1
.2
–
3
.2
)
.9
0
1
.3
2
(1
.1
0
–
2
.2
4
)
2
.2
(1
.5
–
4
.6
)
.0
2
S
e
ru
m
so
d
iu
m
,
m
m
o
l/
L
1
3
8
(1
3
6
–
1
4
3
)
1
3
8
(1
3
6
–
1
4
0
)
1
3
8
(1
3
5
–
1
4
5
)
.3
2
1
3
8
(1
3
6
–
1
3
9
)
1
3
8
(1
3
6
–
1
4
3
)
.5
0
1
3
8
(1
3
6
–
1
4
0
)
1
4
0
(1
3
2
–
1
4
9
)
.4
3
C
re
a
ti
n
in
e
,
m
g
/d
L
1
.4
5
(1
.0
–
2
.4
5
)
1
.1
(0
.8
–
1
.7
5
)
1
.6
(1
.1
–
2
.7
5
)
.0
0
4
1
.2
(0
.9
–
2
.2
)
1
.5
(1
.0
–
2
.5
)
.1
8
1
.1
(0
.7
–
1
.7
)
2
.0
(1
.4
–
2
.8
)
.0
0
3
B
il
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…
High-Flow Nasal Cannula Therapy in COVID-19: Using the ROX Index
to Predict Success
Abhimanyu Chandel, Saloni Patolia, A Whitney Brown, A Claire Collins, Dhwani Sahjwani,
Vikramjit Khangoora, Paula C Cameron, Mehul Desai, Aditya Kasarabada, Jack K Kilcullen,
Steven D Nathan, and Christopher S King
BACKGROUND: Optimal timing of mechanical ventilation in COVID-19 is uncertain. We sought to
evaluate outcomes of delayed intubation and examine the ROX index (ie, [SpO2=FIO2]/breathing fre-
quency) to predict weaning from high-flow nasal cannula (HFNC) in patients with COVID-19.
METHODS: We performed a multicenter, retrospective, observational cohort study of subjects with
respiratory failure due to COVID-19 and managed with HFNC. The ROX index was applied to pre-
dict HFNC success. Subjects that failed HFNC were divided into early HFNC failure (^ 48 h of
HFNC therapy prior to mechanical ventilation) and late failure (> 48 h). Standard statistical compari-
sons and regression analyses were used to compare overall hospital mortality and secondary end
points, including time-specific mortality, need for extracorporeal membrane oxygenation, and ICU
length of stay between early and late failure groups. RESULTS: 272 subjects with COVID-19 were
managed with HFNC. One hundred sixty-four (60.3%) were successfully weaned from HFNC, and
111 (67.7%) of those weaned were managed solely in non-ICU settings. ROX index >3.0 at 2, 6, and
12 hours after initiation of HFNC was 85.3% sensitive for identifying subsequent HFNC success. One
hundred eight subjects were intubated for failure of HFNC (61 early failures and 47 late failures).
Mortality after HFNC failure was high (45.4%). There was no statistical difference in hospital mor-
tality (39.3% vs 53.2%, P 5 .18) or any of the secondary end points between early and late HFNC
failure groups. This remained true even when adjusted for covariates. CONCLUSIONS: In this ret-
rospective review, HFNC was a viable strategy and mechanical ventilation was unecessary in the
majority of subjects. In the minority that progressed to mechanical ventilation, duration of HFNC
did not differentiate subjects with worse clinical outcomes. The ROX index was sensitive for the
identification of subjects successfully weaned from HFNC. Prospective studies in COVID-19 are
warranted to confirm these findings and to optimize patient selection for use of HFNC in this
disease. Key words: COVID-19; SARS-CoV-2; high-flow nasal cannula; hypoxemic respiratory failure;
viral pneumonia; respiratory insufficiency. [Respir Care 2021;66(6):909–919. © 2021 Daedalus
Enterprises]
Introduction
Patients with coronavirus disease 2019 (COVID-19) face
substantial morbidity and mortality related to viral pneumo-
nitis that can progress to ARDS.1 The optimal management
strategy for respiratory failure related to the novel severe
acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is
still evolving. Patients with COVID-19 who require mechan-
ical ventilation are at high risk for poor outcomes and have a
likelihood of mortality estimated at approximately 40%.2
Dr Chandel is affiliated with the Department of Pulmonary and Critical
Care, Walter Reed National Military Medical Center, Bethesda,
Maryland. Dr Patolia is affiliated with the Virginia Commonwealth
University School of Medicine, Richmond, Virginia. Drs Brown,
Khangoora, Nathan, and King are affiliated with the Department of
Advanced Lung Disease and Transplant, Inova Fairfax Hospital, Falls
Church, Virginia. Dr Collins is affiliated with Advanced Lung Disease
Research, Inova Fairfax Hospital, Falls Church, Virginia. Dr Sahjwani is
affiliated with the Department of Pediatrics, Inova Fairfax Hospital,
Falls Church, Virginia. Ms Cameron is affiliated with Respiratory
Therapy, Inova Fairfax Hospital, Falls Church, Virginia. Drs Desai,
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 909
Though overall mortality of the disease, including the mor-
tality of patients in the ICU, has decreased over the course of
the pandemic, COVID-19 remains a significant burden on
the worldwide health care infrastructure.3 Mortality may be
related to the progressive course of the viral infection, but it
could be perpetuated by the inherent complications of me-
chanical ventilation itself.
High-flow nasal cannula (HFNC) devices can deliver
warmed, humidified oxygen at flows up to 60 L/min and
FIO2 up to 1.0. This modality of oxygen delivery can
reduce the need for intubation and mechanical ventila-
tion for patients with acute hypoxemic respiratory fail-
ure.4,5 Data also suggest that early use of this therapy
may decrease the need for invasive mechanical ventila-
tion in COVID-19.6 Success of HFNC can be predicted
by the ROX index (ie, [SpO2=FIO2]/breathing frequency),
which is a score that has been validated in the treatment
of pneumonia and ARDS. This clinical score was ini-
tially applied based on clinical data at 2 h, 6 h, and 12 h
after application of HFNC.7 The score has been subse-
quently applied to the use of HFNC in the treatment of
COVID-19, and investigators have proposed values that
correlate with subsequent failure of HFNC and need for
endotracheal intubation.8-11 Most prior research related
to HFNC use in patients with COVID-19 has focused
efforts on utilizing the ROX index to identify patients at
risk of subsequent endotracheal intubation, and data
regarding the use of the index to select patients who may
ultimately be weaned from HFNC are lacking.
Substantial controversy exists as to the optimal timing
of initiation of invasive mechanical ventilation in the
management of COVID-19 respiratory failure. Some have
argued for more aggressive, early intubation to avoid pos-
sible patient self-induced lung injury.12-14 Others have
advocated for longer trials of noninvasive supplemental
oxygen modalities as a means to avoid endotracheal intu-
bation and associated complications.15,16 Thus, despite
possible hazards associated with delayed intubation, many
clinicians have utilized extended trials of HFNC in
patients with COVID-19 respiratory failure.16,17 The aim
of this study was to evaluate predictors of successful
weaning and overall outcomes in subjects managed with
HFNC for the support of respiratory failure related to
COVID-19.
Methods
Study Population
We performed a multicenter, retrospective, observational
study of subjects treated for acute respiratory failure second-
ary to COVID-19 and managed with HFNC within the Inova
Health System. The Inova Health System consists of 5 hospi-
tals, including a large tertiary care center and 4 community
hospitals. Subjects were included if they were $ 18 y old,
had a laboratory-confirmed diagnosis of COVID-19 by poly-
merase chain reaction testing, and were treated with HFNC
for $ 2 h. Patients were excluded if endotracheal intubation
was performed prior to initiation of HFNC (eg, following
extubation to reduce the risk of re-intubation) or performed
on an elective basis (eg, for elective surgical care). To mini-
mize heterogeneity of the studied population, patients who
were switched to noninvasive ventilation prior to endotra-
cheal intubation were also excluded. Given the objective to
compare outcomes associated with early versus late endotra-
cheal intubation, patients for whom endotracheal intubation
was not within their goals of care were also excluded.
QUICK LOOK
Current knowledge
High-flow nasal cannula (HFNC) is routinely used as
part of the care of patients with respiratory failure
related to COVID-19. Significant debate exists as to
the optimal timing of progression to invasive mechani-
cal ventilation in the event of clinical worsening or fail-
ure to wean from HFNC.
What this paper contributes to our knowledge
In this multicenter, observational, cohort study, HFNC
was frequently successful in avoiding the need for
invasive mechanical ventilation. The ROX index (ie,
[SpO2=FIO2]/breathing frequency) was sensitive for the
identification of subjects who could be managed with
HFNC without the subsequent need for endotracheal
intubation. Clinical outcomes did not differ between
subjects based on the duration of HFNC therapy prior
to the initiation of mechanical ventilation. Extended
use of HFNC may be reasonable in the care of patients
with COVID-19 as a measure to avoid invasive me-
chanical ventilation.
Kasarabada, and Kilcullen are affiliated with Medical Critical Care
Service, Inova Fairfax Hospital, Falls Church, Virginia.
The authors have disclosed no conflicts of interest.
Correspondence: Abhimanyu Chandel MD, Walter Reed National Military
Medical Center, Department of Pulmonary and Critical Care, 8901 Rockville
Pike, Bethesda, MD, 20814. E-mail: [email protected]
DOI: 10.4187/respcare.08631
SEE THE RELATED EDITORIAL ON PAGE 1044
HFNC FOR COVID-19 RESPIRATORY FAILURE
910 RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6
mailto:[email protected]
Data were collected for subjects admitted to the Inova
Health System between March 1, 2020, and June 9, 2020.
The study was approved by the institutional review board
(U20-06-4134) at Inova Fairfax Hospital. All data were col-
lected from the electronic medical record.
Inova Health System’s COVID-19 Management
Protocol
The strategy for the management of acute respiratory fail-
ure was fairly homogenous across our health care system.
Efforts were made to avoid intubation where feasible with the
use of HFNC (Optiflow, Fisher & Paykel, Auckland, New
Zealand). Noninvasive ventilation was largely avoided early
on due to concerns regarding aerosolizing the SARS-CoV-2
virus but was increasingly utilized over time. Inhaled nitric
oxide was delivered in a blend with oxygen via HFNC, and
self-proning was incorporated where deemed clinically
appropriate. Failure of HFNC was defined as the need for me-
chanical ventilation despite HFNC application. The need for
endotracheal intubation after HFNC was at the discretion of
the treating clinician, but it was generally based on the pres-
ence of hypoxemia with a failure to maintain SpO2 > 88% de-
spite receiving the maximum FIO2 allowed by the HFNC,
breathing frequency > 35 breaths/min with associated respi-
ratory distress, severe metabolic acidosis, cardiopulmonary
arrest, or altered mental status requiring intubation for avoid-
ance of aspiration. In the event of the need for mechanical
ventilation, subjects were typically managed initially with
moderate PEEP (10–12 cm H2O) and a lung-protective venti-
lator strategy. Neuromuscular blockade and prone positioning
were frequently utilized in subjects with severe ARDS. The
choice of sedation and analgesia was at the discretion of the
attending intensivist and was targeted to a Richmond
Agitation Sedation Scale of 0 to –2.18 Subjects were consid-
ered for extracorporeal membrane oxygenation (ECMO) if
they were < 60 y old, were on invasive mechanical ventila-
tion for < 10 d, had SpO2=FIO2 < 100, and failed lung-protec-
tive ventilation despite neuromuscular blockade and prone
positioning.
Adjunct therapeutics targeting COVID-19 disease were
administered at the discretion of the attending physician and
commonly included systemic glucocorticoids and remdesi-
vir. The use of convalescent plasma was infrequent during
the study period. Given high patient volumes related to the
COVID-19 pandemic across the Inova Health system,
changes in the usual protocol for treatment and monitoring
of patients with respiratory failure at our facilities were nec-
essary. All patients managed with invasive mechanical venti-
lation were treated in an intensive care environment.
However, expansion of the level of acuity managed outside
of an intensive care setting was required, and many subjects
were managed with HFNC in augmented step-down units up
to the point of requiring endotracheal intubation.
Data Collection
Data were abstracted in a structured format by 3 of the
authors (AC, SP, and DS), including demographics, comor-
bid diseases (as documented in the admitting history and
physical), and clinical data (eg, vital signs within 1 h prior
to HFNC application and for 12 h thereafter, common labo-
ratory results, and illness severity as estimated with the
Sequential Organ Failure Assessment [SOFA]). The ROX
index was calculated and recorded at 2 h, 6 h, and 12 h after
HFNC application. Laboratory data were collected when
available within 6 h of initiation of HFNC. Adjunctive
measures provided while subjects were receiving HFNC,
such as the use of prone positioning or the administration
of inhaled nitric oxide, remdesivir, or systemic steroids
(ie, the equivalent of prednisone $ 20 mg/d) were also
recorded. The primary outcome examined was overall hos-
pital mortality. Secondary outcomes included the need for
ECMO, mortality at 14 d and at 28 d after HFNC and endo-
tracheal intubation, and ICU length of stay. Data were also
collected and compared for ICU-related complications,
including the development of ventilator-associated pneu-
monia (ie, a combination of new or progressive radio-
graphic infiltrate with a positive respiratory specimen and a
clinically documented diagnosis), pneumothorax, second-
ary infection (ie, a positive culture or related microbiologic
data thought to be pathologic by the treating clinician),
acute kidney injury (ie, a rise in serum creatinine of $ 0.3
mg/dL over 48 h), need for renal replacement therapy, and
imaging-confirmed venous thromboembolism (ie, based on
the finalized radiographic report or documented point-of-
care ultrasound findings in subjects with acute decompen-
sation and suspected pulmonary embolism).
Subjects were first divided into those managed with
HFNC who were successfully weaned from this modality
and those who were ultimately intubated. Those who under-
went endotracheal intubation after HFNC failure were then
divided into 2 groups; early failure (defined as # 48 h of
HFNC therapy prior to endotracheal intubation) and late
failure (intubation after > 48 h of HFNC therapy).
Statistical Analysis
Distribution of all continuous data were examined for
normality using visual inspection and the Wilk-Shapiro
test. Characteristics of the groups are presented using the
mean 6 SD for normally distributed data and compared
between groups using the 2-sample t test. Data that were
not normally distributed are presented as median (interquar-
tile range) and compared using the Wilcoxon rank-sum
test. Categorical data are presented as counts with prop-
ortions and compared using the Fisher exact test (2-tailed).
The diagnostic accuracy of the ROX index to predict suc-
cess of HFNC (ie, application without subsequent need for
HFNC FOR COVID-19 RESPIRATORY FAILURE
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 911
mechanical ventilation) is presented using a receiver oper-
ating characteristic curve together with sensitivity, specific-
ity, and predictive values at the defined cutoffs, and
summarized using the area under the curve together with
the 95% CI. To compare clinical outcomes between early
and late HFNC failure, we performed logistic regression
(overall ICU mortality, 14-d mortality, and 28-d mortality).
ICU length of stay demonstrated a positively skewed distri-
bution. To minimize the effects of outliers and to account
for this distribution, negative binomial regression was uti-
lized to compare this outcome. P values < .05 were consid-
ered statistically significant. Univariate and multivariate
logistic regression analysis of factors possibly associated
with mortality were performed. Variables were included in
the model if they were statistically significant based on uni-
variate analysis and subsequently removed by means of the
stepwise backward elimination method with P < .15.
Outcome data were available for all subjects at the time of
analysis. Any missing clinical data were handled via com-
plete case analysis (only cases with available data were ana-
lyzed). All statistical analyses were performed using
STATA 14 (StataCorp, College Station, Texas).
Results
During the study period, our search strategy identified 393
subjects with respiratory failure secondary to COVID-19
who required the use of HFNC within the Inova Health
System. Patients who did not receive HFNC therapy prior to
endotracheal intubation (n ¼ 27), were switched to noninva-
sive ventilation (n ¼ 21), were intubated for an elective rea-
son (n ¼ 1), or were < 18 y old (n ¼ 6) were excluded.
Given that the primary study objective was to analyze the
outcomes of subjects who ultimately underwent endotracheal
intubation, 66 patients were excluded as intubation and me-
chanical ventilation did not align with their goals of care. Of
the remaining 272 subjects, 164 (60.3%) recovered without
intubation and were weaned successfully from HFNC,
whereas 108 (39.7%) subjects were intubated after failing
HFNC, with 61 intubated after # 48 h of HFNC and 47 intu-
bated after > 48 h of HFNC application (Fig. 1).
The characteristics of the 164 subjects managed with
HFNC who were successfully weaned from this modality
are presented in Table 1. Compared to those who underwent
intubation, subjects who were successfully weaned from
HFNC were more likely to be younger and have no comor-
bidities. A history of active cancer, higher initial SOFA
score, higher lactate, higher procalcitonin, and lower neutro-
phil to lymphocyte ratio were all associated with subsequent
failure of HFNC. Subjects weaned successfully from HFNC
received this therapy for longer and had a higher median
ROX index at the defined cutoffs compared to those subjects
who required mechanical ventilation. None of the subjects
successfully weaned from HFNC died prior to hospital dis-
charge. Receiver operator curves based on the ROX index
were estimated at 2 h, 6 h, and 12 h after initiation of HFNC
Patients with confirmed COVID-19
respiratory failure treated with
HFNC
393
Subjects enrolled
272
Improved and weaned from HFNC
164 (60.3%)
Intubated after HFNC failure
108 (39.7%)
Failure of HFNC ≤48 h
61 (56.5%)
Failure of HFNC >48 h
47 (43.5%)
Do-not-intubate: 66
Switched to NIV: 21
No trial of HFNC prior to
endotracheal intubation: 27
Electively intubated for
surgical procedure: 1
Age <18 y: 6
Excluded
121
Figure 1. Flow chart. HFNC ¼ high-flow nasal cannula, NIV ¼ noninvasive ventilation.
HFNC FOR COVID-19 RESPIRATORY FAILURE
912 RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6
to predict the success of HFNC. Overall diagnostic accuracy
was good, and this improved with a longer duration of
HFNC application (Fig. 2). The diagnostic accuracy of a
ROX index at 12 h was the best (area under the curve 0.78
[95% CI 0.72–0.84]), and an index of > 3.67 had a sensitiv-
ity of 84.1%, specificity of 49.4%, positive predictive value
of 71.5%, and a negative predictive value of 67.1% for pre-
dicting success of HFNC, thus satisfying the closest-to-(0,1)
criterion for threshold selection. For subjects who were not
intubated or weaned from HFNC within the first 12 h after
HFNC initiation, a ROX index > 3.0 at each time point (ie,
2 h, 6 h, and 12 h) had a sensitivity of 85.3%, specificity of
51.1%, positive predictive value of 75.5%, and a negative
predictive value of 66.7% for the subsequent success of
HFNC.
The characteristics of the 108 subjects intubated after
HFNC failure are displayed by group in Table 2. The mean
age was 60 y, and the majority were male (69.4%) and non-
White (87.0%). Most had comorbidities (78.7%), of which
the most common were hypertension (48.1%), diabetes
mellitus (41.7%), and hyperlipidemia (31.5%). Most clini-
cal characteristics were similar between the 2 groups; how-
ever, SOFA score was significantly higher in the early
HFNC failure group compared to the late HFNC failure
Table 1. Baseline Characteristics of Subjects Treated With HFNC
All Subjects
(n ¼ 272)
Weaned from HFNC
(n ¼ 164)
HFNC Failure
(n ¼ 108) P
Age, y 57 6 13 54 6 14 60 6 13 < .001
Female 92 (33.8) 60 (36.6) 32 (29.6) .24
Race, non-White 248 (91.2) 154 (93.9) 94 (87.0) .08
Body mass index, kg/m2 28.7 (25.2–33.4) 28.6 (25.5–33.2) 28.7 (24.9–33.6) .90
HFNC duration, d 3 (1–6) 4 (2–7) 2 (1–4) < .001
Comorbid diseases
No comorbid disease 83 (3.5) 60 (36.6) 23 (21.3) .01
Hypertension 116 (42.6) 64 (39.0) 52 (48.1) .17
Diabetes mellitus 101 (37.1) 56 (34.1) 45 (41.7) .25
Chronic kidney disease 20 (7.4) 8 (4.9) 12 (11.1) .061
End-stage renal disease 8 (2.9) 4 (2.4) 4 (3.7) .72
Coronary artery disease 9 (3.3) 5 (3.0) 4 (3.7) .74
Hyperlipidemia 74 (27.2) 40 (24.4) 34 (31.5) .21
Asthma 13 (4.8) 9 (5.5) 4 (3.7) .57
COPD 2 (0.7) 1 (0.6) 1 (0.9) > .99
Active cancer 7 (2.6) 1 (0.6) 6 (5.6) .02
HFrEF 4 (1.5) 2 (1.2) 2 (1.9) .65
Systemic anticoagulation 9 (3.3) 8 (4.9) 1 (0.9) .09
Clinical data at HFNC initiation
Heart rate, beats/min 93 (80–104) 89 (80–103) 95 (82–104) .19
Mean arterial pressure, mm Hg 89.7 6 13.0 89.3 6 12.9 9.3 6 13.2 .57
Breathing frequency, breaths/min 29 (24–36) 28 (24–36) 30 (26–37) .059
Oxygen saturation 93 (90–96) 93 (90–96) 93 (89–95) .22
SOFA score 3 (1–5) 2 (1–4) 4 (2–7) < .001
White blood cells, �109 per mL 8.3 (6.0–11.4) 8.0 (6.0–1.9) 8.9 (6.1–11.6) .40
Neutrophil to lymphocyte ratio 6.5 (4.2–11.7) 6.1 (3.9–1.6) 8.1 (4.9–12.0) .02
Lactate, mmol/L 1.7 (1.3–2.3) 1.5 (1.3–2.1) 1.9 (1.4–2.8) < .005
C-reactive protein, mg/L 16.8 (10.0–24.2) 16.7 (9.8–23.6) 17.2 (1.8–26.3) .51
D-dimer, mg/mL 1.3 (0.9–2.5) 1.3 (0.8–2.2) 1.3 (0.9–2.7) .25
Procalcitonin, ng/mL 0.3 (0.1–0.6) 0.2 (0.1–0.5) 0.3 (0.1–1.0) .033
ROX index
2 h after HFNC 4.5 (3.3–6.0) 4.9 (3.7–6.7) 3.6 (2.8–4.8) < .001
6 h after HFNC 4.6 (3.6–6.3) 5.1 (4.1–6.9) 3.9 (3.0–4.8) < .001
12 h after HFNC 4.7 (3.4–6.2) 5.3 (4.3–6.9) 3.8 (2.6–4.5) < .001
Data presented as mean 6 SD, median (interquartile range), or n (%) unless otherwise indicated.
HFNC ¼ high-flow nasal cannula
HFrEF ¼ heart failure with reduced ejection fraction
SOFA ¼ Sequential Organ Failure Assessment
HFNC FOR COVID-19 RESPIRATORY FAILURE
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 913
group. Additionally, subjects who failed HFNC late were
more likely to have received adjuvant therapies such as
self-proning (39.3% vs 72.3%, P < .001), inhaled nitric
oxide (14.8% vs 42.6%, P < .002), remdesivir (19.7% vs
40.4%, P ¼ .031), and systemic steroids (27.9% vs 53.2%,
P ¼ .01) prior to intubation compared to those intubated af-
ter early HFNC failure.
Clinical outcomes are summarized in Table 3. Overall
hospital mortality for subjects requiring invasive mechanical
ventilation was high (45.4%), which did not differ signifi-
cantly between the early and late failure groups (39.3% vs
53.2%, P ¼ .18). Furthermore, mortality at 14 d after initia-
tion of HFNC (24.6% vs 25.5%, P > .99), at 14 d after intu-
bation (24.6% vs 34.0%, P ¼ .29), at 28 d after initiation of
HFNC (34.4% vs 42.6%, P ¼ .43), and at 28 d after intuba-
tion (34.4% vs 51.1%, P ¼ .12) were not significantly differ-
ent between the groups. ECMO requirements (13.1% vs
14.9%, P ¼ .79) and median (IQR) ICU length of stay were
also similar (14 d [IQR 9–20] vs 15 d [IQR 8–23], P ¼ .95).
Table 4 demonstrates the relationship between clinical
factors and overall hospital mortality for subjects intubated
after HFNC failure. In univariate regression analysis,
significant factors were age, male gender, heart rate, mean
arterial pressure, and SOFA score. After adjustment for
multiple variables, no significant difference between the
primary or secondary end points was noted for either group
(Table 5).
Additional ICU complications by early versus late HFNC
failure are displayed in Table 6. Notably, pneumothorax, sec-
ondary infection, and acute kidney injury were common,
occurring in 11.1%, 29.6%, and 55.6% of the study popula-
tion, respectively. There were no significant differences for
any of the complications between the groups.
Discussion
Our study documents the clinical outcomes of 272 sub-
jects with respiratory failure related to COVID-19 that was
treated with HFNC. A significant portion (60.3%) of subjects
with respiratory failure related to COVID-19 were managed
successfully with HFNC and never required initiation of me-
chanical ventilation. Strikingly, 111 (67.7%) of these sub-
jects were managed successfully in non-ICU settings. Of the
108 subjects treated with HFNC who ultimately required
1
0.
75
0.
25
0
0.
50
S
en
si
tiv
ity
1
0.
75
0.
25
0
0.
50
S
en
si
tiv
ity
1
0.
75
0.
25
0
0.
50
S
en
si
tiv
ity
0 0.25
* *
*
†
0.50 0.75 1
1 - Specificity
0 0.25 0.50 0.75 1
1 - Specificity
0 0.25 0.50 0.75 1
1 - Specificity
A B
C
Figure 2. Receiver operator characteristic curves for ROX index at 2 h (A), 6 h (B), and 12 h (C) as predictor of high-flow nasal cannula success.
A: Area under the curve (AUC) ¼ 0.70 (CI 0.63–0.76). * ROX index > 3.41, 83.5% sensitivity, 42.6% specificity, positive predictive value (PPV)
68.8%, negative predictive value (NPV) 63.0%. B: AUC ¼ 0.72 (CI 0.65–0.79). * ROX index > 3.46, 89.3.% sensitivity, 41.8% specificity, PPV
69.9%, NPV 71.4% C: AUC ¼ 0.78 (CI 0.72–0.84). C: AUC ¼ 0.78 (CI 0.72–0.84). * ROX index > 3.67, 84.1.% sensitivity, 49.4% specificity, PPV
71.5%, NPV 57.1% † ROX index > 4.57, 72.4% sensitivity, 75.9% specificty, PPV 82.1%, NPV 64.6%.
HFNC FOR COVID-19 RESPIRATORY FAILURE
914 RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6
endotracheal intubation, we noted high overall mortality
(45.4%), significant use of ECMO (13.9%), and a longer me-
dian stay in the ICU of 14 d (IQR 8–21).
HFNC has previously been reported to have several posi-
tive physiologic and clinical advantages in the treatment of
acute respiratory failure. HFNC can enhance patient comfort
through a reduction of important subjective patient-reported
symptoms, including dyspnea and oral dryness, compared to
conventional oxygen delivery.4 Additionally, HFNC may
provide physiologic benefit from a reduction in patient work
of breathing and a decrease in physiologic dead space though
high air flows.19 HFNC has been used successfully in the
management of respiratory distress related to other viral ill-
nesses, and data suggest that the use of HFNC in COVID-19
has the potential to decrease the need for mechanical ventila-
tion.6,20 Avoidance of intubation may allow for a reduction
in complications commonly associated with endotracheal
intubation such as pneumonia, ventilator-associated lung
injury, or secondary infections. Furthermore, avoidance of
mechanical ventilation through the use of HFNC may help
conserve this valuable resource in the event of ventilator
shortages.
However, despite these advantages, there is concern that
poor patient selection or prolonged trials of HFNC may
Table 2. Baseline Characteristics of Subjects Intubated After HFNC Failure
All Subjects
(n ¼ 108)
Early HFNC Failure
(n ¼ 61)
Late HFNC Failure
(n ¼47) P
Age, y 60 6 13 58 6 13 62 6 11 .07
Female 33 (3.6) 18 (29.5) 15 (31.9) .84
Race, non-White 94 (87.0) 55 (9.2) 39 (83.0) .39
Body mass index, kg/m2 28.7 (24.9–33.6) 3.2 (26.3–35.7) 27.9 (23.5–32.9) .08
HFNC duration, d 2 (1, 4) 1 (0, 1) 4 (3, 8) < .001
Comorbid diseases
No comorbid disease 23 (21.3) 17 (27.9) 6 (12.8) .063
Hypertension 52 (48.1) 25 (41.0) 27 (57.4) .12
Diabetes mellitus 45 (41.7) 23 (37.7) 22 (46.8) .43
Chronic kidney disease 12 (11.1) 7 (11.5) 5 (1.6) > .99
End-stage renal disease 4 (3.7) 3 (4.9) 1 (2.1) .63
Coronary artery disease 4 (3.7) 2 (3.3) 2 (4.3) > .99
Hyperlipidemia 34 (31.5) 16 (26.2) 18 (38.3) .21
Asthma 4 (3.7) 2 (3.3) 2 (4.3) > .99
COPD 1 (.9) 1 (1.6) 0 (0) > .99
Active cancer 6 (5.6) 5 (8.2) 1 (2.1) .23
HFrEF 2 (1.9) 0 (0) 2 (4.3) .19
Systemic anticoagulation 1 (.9) 1 (1.6) 0 (0) > .99
Clinical data at HFNC initiation
Heart rate, beats/min 95 (82–104) 99 (85–104) 93 (80–100) .22
Mean arterial pressure, mm Hg 9.3 6 13.2 90.4 6 13.6 9.1 6 12.9 .91
Breathing frequency, breaths/min 30 (26–37) 30 (25.5–37) 31 (26–37) .65
Oxygen saturation 93 (89–95) 93 (88–94) 93 (90–96) .42
SOFA score 4 (2–7) 5 (2–8) 4 (2–5) .02
White blood cells, �109 per mL 8.9 (6.1–11.6) 9.2 (6.1–11.5) 8.4 (6.1–11.9) .93
Neutrophil to lymphocyte ratio 8.1 (4.9–12.0) 9.0 (4.3–12.9) 7.4 (5.6–11.6) .80
Lactate, mmol/L 1.9 (1.4–2.8) 1.8 (1.3–2.8) 2.0 (1.5–3.0) .41
C-reactive protein, mg/L 17.2 (1.8–26.3) 18.0 (11.1–28.2) 16.7 (9.7–23.3) .47
D-dimer, mg/mL 1.3 (0.9–2.7) 1.5 (0.9–2.5) 1.2 (0.8–2.9) .97
Procalcitonin, ng/mL 0.3 (0.1–1.0) 0.3 (0.1–1.2) 0.3 (0.1–0.6) .13
Adjunctive measures prior to intubation
Self-proning 58 (53.7) 24 (39.3) 34 (72.3) < .001
Inhaled nitric oxide 29 (26.9) 9 (14.8) 20 (42.6) < .002
Remdesivir 31 (28.7) 12 (19.7) 19 (40.4) .031
Systemic …
Value of Bedside Lung Ultrasound in Severe and Critical COVID-19
Pneumonia
Shuangshuang Kong, Jing Wang, Yuman Li, Ying Tian, Cheng Yu, Danqing Zhang, Hong Li,
Li Zhang, Xueqin Pang, and Mingxing Xie
BACKGROUND: Lung ultrasound (LUS) is an effective imaging modality that can differentiate
pathological lung from non-diseased lung. We aimed to explore the value of bedside LUS in
patients with severe and critical coronavirus disease 2019 (COVID-19)-associated lung injury.
METHODS: Sixty-three severe and 33 critical hospitalized subjects with COVID-19 were en-
rolled in this study. Bedside LUS was performed in all subjects; chest computed tomography
was performed on the same day as bedside LUS in 23 cases. The LUS protocol consisted of 12
scanning zones. LUS score based on B-lines and lung consolidation was evaluated. RESULTS:
The most common abnormality of LUS was the various forms of B-lines, detected in 93 (96.9%)
subjects; as the second most frequent abnormality, 80 (83.3%) subjects exhibited lung consolida-
tion, mainly located in the posterior lung region. Twenty-four (25.0%) subjects had pleural line
abnormalities, and 16 (16.7%) had pleural effusion; 78 (81.3%) subjects had 6 2 abnormal LUS
patterns, and 93 (96.9%) had bilateral lung involvement. The proportion of bilateral or unilat-
eral lung consolidation and pleural effusion in the critical COVID-19 group were higher than
that in the severe group (P < .05). The lung consolidation of critical subjects showed a marked
increase in most lung areas, including bilateral lateral lung, posterior lung, and left anterior-in-
ferior lung area. The median (interquartile range) LUS scores of critical cases were higher than
those of severe cases: left: 14 (12–17) vs 7 (5–12); right: 14 (10–16) vs 8 (3–12); bilateral: 28 (23–
31) vs 15 (8–22) (P < .001 for all). There was a good correlation between the LUS score and the
chest computed tomography score (r 5 0.887, P < .001). CONCLUSIONS: The most common
abnormal LUS pattern in subjects with severe and critical COVID-19 pneumonia was B-lines, fol-
lowed by lung consolidation. Bedside LUS can provide important information for pulmonary involve-
ment in patients with COVID-19. Key words: lung; ultrasound; diagnostic imaging; COVID-19;
pneumonia; computed tomography. [Respir Care 2021;66(6):920–927. © 2021 Daedalus Enterprises]
Introduction
The coronavirus disease 2019 (COVID-19) caused by
severe acute respiratory syndrome coronavirus 2 (SARS-
CoV-2) has spread worldwide, resulting in lung and other
multiple organ damage and seriously threatening human
life and health.1-4 Severe and critical COVID-19 patients
may have hypoxemia or respiratory failure, as well as shock
or multiple organ failure, which require mechanical ventila-
tion and monitoring. Chest computed tomography (CT) has
The authors are affiliated with the Department of Ultrasound, Union
Hospital, Tongji Medical College, Huazhong University of Science and
Technology, Wuhan, China. The authors are also affiliated with the
Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
Drs Kong, Wang, Li, and Tian are co-first authors.
This work was supported by the National Natural Science Foundation of
China (Grant Nos. 81771851, 81727805, 81922033). The authors have
disclosed no conflicts of interest.
Supplementary material related to this paper is available at http://www.
rcjournal.com.
Correspondence: Mingxing Xie MD PhD, Department of Ultrasound,
Union Hospital, Tongji Medical College, Huazhong University of
Science and Technology, 1277# Jiefang Ave, Wuhan 430022, China.
E-mail: [email protected]
DOI: 10.4187/respcare.08382
920 RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6
http://www.rcjournal.com
http://www.rcjournal.com
mailto:[email protected]
been recommended for the diagnosis of COVID-19,5,6 but
it is limited when there is no bedside CT capability due to
the high risk of transporting patients with COVID-19.7
Lung ultrasound (LUS) identifies ultrasonic artifacts origi-
nating from the pleural line and can accurately differentiate
pathological lung from non-diseased lung.8 LUS has the
advantages of being fast, noninvasive, convenient (ie, bed-
side availability),8-11 and safe with no radiation exposure,
all of which are especially suitable for the evaluation and
serial observation of patients with severe and critical
COVID-19.
The purposes of this study were to summarize the char-
acteristics of LUS in patients with severe and critical
COVID-19 in isolation wards, and to provide a reliable
method to assess COVID-19–associated lung injury.
Methods
Subjects
We included 96 adult subjects who were diagnosed with
severe or critical COVID-19 between January 25 and March
20, 2020, in the west branch of Union Hospital, Tongji
Medical College, Huazhong University of Science and
Technology. COVID-19 was confirmed in these 96 subjects
with nucleic acid testing for the diagnosis of SARS-CoV-2
infection, referring to the diagnostic criteria from the National
Health Commission of the People’s Republic of China guide-
lines for COVID-19.12 Of these subjects, 63 with severe
COVID-19 were included on the basis of exhibiting any of
the following: dyspnea, breathing frequency $ 30 brea-
ths/min, SpO2 # 93% at rest, PaO2=FIO2 # 300 mm Hg, and
lung infiltrates > 50% within 24–48 h. Thirty-three subjects
with critical COVID-19 had respiratory failure requiring inva-
sive mechanical ventilation, shock, or multisystem organ failure.
Clinical data for the present analysis were obtained from
the medical record system of our hospital, which included
clinical findings, medical history, and pathophysiologic
findings such as vital signs and laboratory test results. This
study was approved by the ethics committee of Union
Hospital, Tongji Medical College of Huazhong University
of Science and Technology, and informed consent was
waived for this retrospective study.
LUS Image Acquisition and Score
Bedside LUS scans were ordered for subjects with severe
and critical COVID-19 who presented with dyspnea after oxy-
gen therapy through nasal cannula or mask. LUS was per-
formed by 2 experienced sonographers who had completed
LUS training (SK and YT). The images were assessed by
these physicians (SK and YT), and they reached consensus on
their findings. All subjects underwent bedside LUS examina-
tions on the first day of hospitalization and before mechanical
ventilation with the M9 Doppler ultrasonic diagnostic appara-
tus (Mindray Biomed Electronics, Shenzhen, China) with
1.0–5.0 MHz transducer or the GE LOGIQ E9 (GE
Healthcare, Milwaukee, Wisconsin) with 1.0–6.0 MHz trans-
ducer. For each hemithorax, 6 regions were scanned: anterior,
lateral, and posterior regions were delimited by anatomical
landmarks of anterior and posterior axillary lines. Each area
was divided in half, including superior and inferior region.13-15
In each subject, anterior and lateral lung regions were scanned
with the subject in the supine position, and the posterior
region was scanned with the subject in a lateral or sitting posi-
tion. All adjacent intercostal spaces must be explored parallel
and perpendicular to ribs. For each explored region, the worst
finding and the LUS score were recorded according to the fol-
lowing rating: the presence of lung sliding with A-lines or <
3 isolated B-lines, 0; multiple well-separated B-lines, 1; multi-
ple coalescent B-lines, 2; and consolidation, 3.15,16 The cumu-
lative LUS score corresponded to the sum of each region
score, with totals ranging from 0 to 36.
Chest CT Assessment and Simplified Score
Twenty-three of 96 subjects with COVID-19, including 2
critically ill subjects and 21 severely ill subjects, underwent
thin-section chest CT scans on the same day as LUS exami-
nations. CT scans were performed during full inspiration and
expiration, with a section collimation of 0.5 mm. All subjects
were scanned in a helical CT scanner (SOMATOM Force,
Siemens Healthineers, Erlangen, Germany) in the supine
position. Major CT findings, including ground-glass opac-
ities and consolidations, were recorded.5,17 To quantify the
extent of pulmonary abnormalities, a CT score was assigned
QUICK LOOK
Current knowledge
The coronavirus disease 2019 (COVID-19) can result
in serious lung damage and complications. The high
risk of transporting patients with COVID-19 limits
chest computed tomography for critical patients. It is
necessary to explore a different imaging tool, such as
lung ultrasound (LUS), to evaluate associated lung
involvement in pneumonia due to COVID-19.
What this paper contributes to our knowledge
The most common abnormal LUS pattern was B-lines,
followed by lung consolidation in severe and critical
pneumonia due to COVID-19. A strong correlation
between LUS score and computed tomography score
was observed, suggesting that bedside LUS is a reliable
method to assess COVID-19-associated lung injury.
BEDSIDE LUNG ULTRASOUND IN COVID-19
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 921
for each lobe of bilateral lung: absent, 0; < 5% of lobe, 1; 5–
25% of lobe, 2; 26–49% of lobe, 3; 50–75% of lobe, 4; and
76–100% of lobe, 5.18 The CT score was calculated by sum-
ming the scores from all 5 lung lobes, with totals ranging
from 0 to 25.
Statistical Analyses
Statistical analyses were performed with SPSS 25.0
(IBM, Armonk, New York). Continuous normally distrib-
uted data are expressed as mean 6 SD, and non-normally
distributed data are expressed as median (interquartile
range [IQR]). Comparison between severe and critical
groups was performed with the 2-sample t test or the Mann-
Whitney test for continuous variables. Categorical variables
are expressed as percentage (%) and were compared using
the chi-square test or the Fisher exact test. Correlations
between LUS score and CT score and clinical data were
evaluated with the Spearman correlation coefficient. A 2-
tailed P value < .05 was considered statistically significant.
Results
Clinical Characteristics
The clinical characteristics of subjects with severe and
critical COVID-19 are summarized in Table 1. Forty-five
subjects were male, and 51 were female, with ages ranging
from 32 to 97 y (mean 65 6 13 y). The most common clini-
cal symptoms were fever and cough. Compared with sub-
jects with severe COVID-19, critically ill subjects were
more likely to be older and had lower SpO2, lower lympho-
cyte count, higher levels of oxygen flow, and higher levels
of D-dimer and B-type natriuretic peptide, as well as higher
incidence of ARDS, acute kidney injury, acute heart injury,
deep vein thrombosis, septic shock, pneumothorax, and mor-
tality. There were no significant differences in gender, body
mass index, body temperature, smokers, C-reactive protein,
erythrocyte sedimentation rate, alanine aminotransferase, se-
rum creatinine, clinical symptoms, and comorbidities
between subjects with severe or critical COVID-19.
LUS Features
The median (IQR) time from the onset of the disease to
LUS measurement in severe and critical subjects was 7 (6–
10) d. All 96 subjects with COVID-19 had LUS abnormal-
ities, which mainly manifested as patterns of B-lines (93 of
96, 96.9%) and different extent of consolidations (80 of 96,
83.3%). In addition, 24 of 96 (25.0%) subjects had a thick-
ened and irregular pleural line. Pleural effusion was found
in 16 of 96 (16.7%) subjects, including 11 cases with a
small amount of effusion and 5 with a large amount of effu-
sion. Of the 96 subjects, 78 (81.3%) had $ 2 abnormal
LUS patterns, while 14 (14.6%) had all abnormal LUS pat-
terns. The LUS characteristics of all 96 subjects with severe
and critical COVID-19 are shown in the supplementary
materials (available at http://www.rcjournal.com). The
LUS features are presented in Figure 1.
The distribution of common LUS features, including B-
lines and consolidation in all lung regions of subjects with
severe and critical COVID-19, are described in Table 2. The
incidences of consolidation in the bilateral lateral lung, pos-
terior lung area, and left anterior-inferior lung of the crit-
ically ill group were higher than those of the severe group
(P < .05 for all). The proportions of B-lines in the left infe-
rior-lateral lung (P ¼ .02) and right posterior-superior lung
area (P ¼ .005) of the group with severe COVID-19 were
higher than those of the group with critical COVID-19.
In addition, 93 (96.9%) subjects had bilateral lung
involvement. The distribution of LUS abnormalities in uni-
lateral or bilateral lung are shown in Table 3. Compared with
the group with severe COVID-19, the group with critical
COVID-19 had a higher proportion of bilateral or unilateral
lung consolidation and pleural effusion (P < .05 for all).
Eleven (11.5%) cases underwent serial bedside LUS mea-
surement, and 2 cases progressed from the severe to criti-
cal stage (see the supplementary materials at http://www.
rcjournal.com). One case was a 71-y-old woman with clini-
cally diagnosed severe COVID-19 infection. A bedside LUS
performed on admission showed abnormal B-lines pattern in
all lung regions with no consolidations. On day 30, the subject
suffered from respiratory failure, with an inability to maintain
SpO2 > 90% on high-flow oxygen via mask. When a ventila-
tor was needed, the repeat bedside LUS revealed subpleural
consolidations in bilateral lateral and posterior lung regions.
The other confirmed case was a 76-y-old man who was admit-
ted with symptoms of fever (up to 38.7�C), cough, fatigue,
and dyspnea. Bedside LUS examination showed multiple B-
lines and right pleural effusion, and no consolidation was
observed. After 28 d of treatment, the subject’s condition had
not improved. A repeat LUS demonstrated increased pleural
effusion, and consolidations had appeared in all lung areas.
LUS and Chest CT Score
The median (IQR) left, right, and bilateral LUS scores
of critical COVID-19 cases were higher than those of
severe COVID-19 cases: left: 14 (12–17) vs 7 (5–12);
right: 14 (10–16) vs 8 (3–12); bilateral: 28 (23–31) vs 15
(8–22) (P < .001 for all) (Fig. 2). In this study, 23 subjects
with COVID-19 underwent chest CT scan, with a median
(IQR) CT score of 9 (5–14) and a median (IQR) LUS
score of 12 (8–22). There was a good correlation between
the LUS and CT scores (r ¼ 0.887, P < .001) (Fig. 3A).
The clinical and LUS characteristics of these 23 subjects
with COVID-19 are shown in the supplementary materials
(available at http://www.rcjournal.com).
BEDSIDE LUNG ULTRASOUND IN COVID-19
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LUS Score and Clinical Data
LUS score had a weak correlation with oxygen flow (r ¼
0.363, P ¼ .003) and SpO2 (r ¼ –0.340, P ¼ .001) (Fig. 3B,
C). However, LUS score was not associated with breathing
frequency (r ¼ 0.244, P ¼ .056).
Discussion
Our results indicate that fever and cough were the most
common clinical symptoms in subjects with severe and criti-
cal COVID-19, which is consistent with prior studies.2,3
Subjects with COVID-19 were also likely to have numerous
Table 1. Clinical Characteristics of Subjects With Severe and Critical COVID-19
Total Severe COVID–19 Critical COVID–19 P
Subjects, n (male/female) 96 (45/51) 63 (25/38) 33 (20/13) .057
Age, y 65.4 6 12.7 63.4 6 12.2 69.2 6 12.7 .031
Body mass index, kg/m2 24.2 6 2.8 24.5 6 3.1 23.8 6 1.9 .29
Body temperature, �C 38.0 (37.5–38.9) 38.0 (37.6–38.8) 38.0 (37.3–39.0) .71
Breathing frequency, breaths/min 20 (19–25) 20 (19–22) 24 (21–27) < .001
Oxygen flow, L/min 5 (3–10) 4 (3–6) 10 (6–40) < .001
SpO2 , % 91 (89–92) 91 (90–92) 89 (88–90) < .001
Smokers 5 (5.2) 2 (3.2) 3 (9.1) .34
Clinical symptoms
Fever 77 (80.2) 51 (81.0) 26 (78.8) .79
Cough 63 (65.6) 43 (68.3) 20 (6.6) .50
Expectoration 28 (29.2) 16 (25.4) 12 (36.4) .35
Dyspnea 23 (24.0) 18 (28.6) 5 (15.2) .21
Shortness of breath 37 (38.5) 22 (34.9) 15 (45.5) .38
Chills 10 (10.4) 7 (11.1) 3 (9.1) > .99
Chest tightness 31 (32.3) 21 (33.3) 10 (30.3) .82
Fatigue 27 (28.1) 20 (31.7) 7 (21.2) .34
Poor appetite 17 (17.7) 12 (19.0) 5 (15.2) .78
Dizzy 7 (7.3) 5 (7.9) 2 (6.1) > .99
Diarrhea 17 (17.7) 14 (22.2) 3 (9.1) .16
Vomit 5 (5.2) 4 (6.3) 1 (3.0) .66
Muscle soreness 13 (13.5) 11 (17.5) 2 (6.1) .21
Laboratory results
Lymphocyte count, �109/L 0.80 (0.55–1.27) 1.00 (0.59–1.40) 0.70 (0.52–1.08) .039
C-reactive protein, mg/L 2.9 (5.2–68.6) 15.1 (4.2–66.8) 37.3 (9.1–71.1) .63
Erythrocyte sedimentation rate, mm/h 49.0 (28.5–76.0) 46.0 (25.0–79.0) 53.0 (38.0–70.0) .40
Alanine aminotransferase, U/L 32.5 (22.8–51.0) 60.0 (21.5–47.5) 33.0 (26.0–64.0) .25
Serum creatinine, mmol/L 65.0 (54.4–80.7) 12.1 (54.0–79.0) 69.0 (55.0–85.0) .41
B-type natriuretic peptide, pg/mL 65.4 (24.0–146.9) 48.4 (14.1–120.1) 108.1 (50.4–263.8) .007
D-dimers, mg/mL 2.2 (0.9–4.8) 1.6 (0.6–4.0) 3.9 (2.1–7.1) < .001
Comorbidities
Cardiovascular disease 51 (53.1) 29 (46.0) 22 (66.7) .08
Diabetes 10 (10.4) 7 (11.1) 3 (9.1) > .99
COPD 7 (7.3) 4 (6.3) 3 (9.1) .69
Pulmonary tuberculosis 2 (2.1) 0 2 (6.1) .12
Malignant tumor 8 (8.3) 5 (7.9) 3 (9.1) > .99
Complications
ARDS 19 (19.8) 2 (6.1) 17 (27.0) < .001
Acute kidney injury 3 (3.1) 0 3 (4.8) .038
Acute heart injury 5 (5.2) 1 (3.0) 4 (6.3) .046
Deep vein thrombosis 21 (21.9) 7 (21.2) 14 (22.2) .001
Septic shock 8 (8.3) 0 8 (12.7) < .001
Pneumothorax 3 (3.1) 0 3 (4.8) .038
Prognosis
Discharge 85 (88.5) 63 (100) 22 (66.7) < .001
Death 11 (11.8) 0 11 (33.3) < .001
Data are presented as n (%), median (interquartile range), or mean 6 SD.
BEDSIDE LUNG ULTRASOUND IN COVID-19
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 923
changes in laboratory findings, underlying comorbidities,
and complications, which are also in keeping with previous
studies.2-4 Compared with subjects with severe COVID-19,
critical subjects had lymphopenia, high levels of D-dimer,
higher incidence of complications, and higher mortality.
These findings are similar to those previously observed
A B C
D E F
Fig. 1. Lung ultrasound (LUS) features of subjects with COVID-19. A and B: Multiple hyperechoic B-lines (red arrows) arise from the thickened
and irregular pleural line (white arrows). C: Small consolidation is visualized as local subpleural hypoechoic with irregular boundary. D and E: Air
bronchograms (white arrows) are identified by a linear hyperechoic within lung consolidations (red arrows). F: Pleural effusion is observed in the
posterior lower lung region.
Table 2. B-Lines and Consolidation in All Lung Regions of Subjects With Severe and Critical COVID-19
Multiple B-Lines Consolidation
Severe
(n ¼ 63)
Critical
(n ¼ 33) P
Severe
(n ¼ 63)
Critical
(n ¼ 33) P
L1 Left anterior-superior lung 32 (50.8) 17 (51.5) > .99 10 (15.9) 10 (30.3) .12
L2 Left anterior-inferior lung 31 (49.2) 18 (54.5) .67 10 (15.9) 13 (39.4) .01
L3 Left superior-lateral lung 33 (52.4) 16 (48.5) .83 13 (2.6) 15 (45.5) .02
L4 Left inferior-lateral lung 32 (50.8) 8 (24.2) .02 18 (28.6) 23 (69.7) < .001
L5 Left posterior-superior lung 19 (30.2) 5 (15.2) .14 30 (47.6) 28 (84.8) < .001
L6 Left posterior-inferior lung 18 (28.6) 4 (12.1) .08 31 (49.2) 29 (87.9) < .001
R1 Right anterior-superior lung 34 (54.0) 21 (63.6) .39 5 (7.9) 8 (24.2) .055
R2 Right anterior-inferior lung 36 (57.1) 19 (57.6) > .99 9 (14.3) 9 (27.3) .17
R3 Right superior-lateral lung 32 (50.8) 10 (30.3) .08 16 (25.4) 20 (6.6) < .001
R4 Right inferior-lateral lung 24 (38.1) 9 (27.3) .37 21 (33.3) 23 (69.7) .001
R5 Right posterior-superior lung 20 (31.7) 2 (6.1) .005 31 (49.2) 31 (93.9) < .001
R6 Right posterior-inferior lung 17 (27.0) 3 (9.1) .06 28 (44.4) 30 (9.9) < .001
Data are presented as n (%).
BEDSIDE LUNG ULTRASOUND IN COVID-19
924 RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6
between ICU and non-ICU subjects with COVID-19.2,4 The
differences in the characteristics of inflammatory markers,
complications, and prognosis between the critical and severe
groups may indicate that critically ill patients are more seri-
ously injured.
In this study, all subjects with severe and critical
COVID-19 had abnormal LUS findings, including B-lines,
consolidations, abnormal pleural lines, and pleural effu-
sions. Fourteen (14.6%) of the 96 subjects had all abnormal
LUS patterns. The different degrees of lung injury and
imbalance of air-liquid ratio results in multiple sonogra-
phic features. In 78 (81.3%) cases, various manifestations
appeared in different lung regions, indicating that varying
degrees of lung involvement can occur at the same time.
In our cohort, the most frequent LUS abnormality was
multiple B-lines, which was detected in 93 (96.9%) subjects.
B-lines are known as ultrasonic artifacts and present as
hyperechoic vertical lines arising from the pleural line and
spreading up to the edge of the screen, relating to the abnor-
mal interlobular septa or alveoli edema.19-21 Various patterns
of B-lines are observed in the inflammatory exudation of
pulmonary interstitium or alveoli. Multiple well-spaced B-
lines and coalescent B-lines reflect pulmonary interstitial
and alveolar edema, respectively. In addition, the second
most common LUS pattern was consolidation, noted in 80
0
5
10
15
20
0
5
10
15
20
0
10
20
30
40
Le
ft
LU
S
s
co
re
R
ig
ht
L
U
S
s
co
re
B
ila
te
ra
l L
U
S
s
co
re
Severe Critical Severe Critical Severe Critical
A B C
Fig. 2. Comparisons of left (A), right (B), and bilateral (C) LUS score between severe and critical COVID-19 cases. P <.001 for each. LUS ¼ lung
ultrasound.
0
0
10
10
20
20
30
30
40
LU
S
s
co
re
r = 0.887
P < .001
0
0
10
20
20
40
30
60
40
0
10
20
30
40
LU
S
s
co
re
LU
S
s
co
re
r = 0.363
P = .003
r = −0.340
P = .001
Oxygen flow (L/min)CT score Oxygen saturation (%)
84 86 88 90 92 94
A B C
Fig. 3. Correlations between lung ultrasound (LUS) score and computed tomography (CT) score (A), oxygen flow (B), and oxygen saturation (C).
Table 3. LUS Signs and Scores of Subjects With Severe and Critical
COVID-19
Severe
(n ¼ 63)
Critical
(n ¼ 33) P
Left lung
Abnormal pleural line 12 (19.0) 6 (18.2) > .99
Multiple B-lines 59 (93.7) 28 (84.8) .27
Consolidation 39 (61.9) 29 (87.9) .004
Pleural effusion 3 (4.8) 9 (27.3) .003
LUS score 7 (5–12) 14 (12–17) < .001
Right lung
Abnormal pleural line 13 (2.6) 7 (21.2) > .99
Multiple B-lines 57 (9.5) 29 (87.9) .73
Consolidation 40 (63.5) 33 (100.0) < .001
Pleural effusion 3 (4.8) 11 (33.3) < .001
LUS score 8 (3–12) 14 (10–16) < .001
Bilateral lung
Abnormal pleural line 6 (9.5) 4 (12.1) .73
Multiple B-lines 54 (85.7) 27 (81.8) .77
Consolidation 31 (49.2) 30 (9.9) < .001
Pleural effusion 2 (3.1) 8 (24.2) .003
LUS score 15 (8–22) 28 (22–31) < .001
Data are presented as n (%) or median (interquartile range).
LUS ¼ lung ultrasound
BEDSIDE LUNG ULTRASOUND IN COVID-19
RESPIRATORY CARE � JUNE 2021 VOL 66 NO 6 925
(83.3%) subjects with COVID-19 who had various extent of
consolidation, which is caused by loss of air in alveoli, filling
with exudates or even collapsing progressively. The propor-
tion of consolidation in this cohort was higher than that
reported in previous studies.22-24 This discrepancy might be
due to our study population of subjects with severe and criti-
cal COVID-19. Our findings indicate that lung pathology
may evolve to consolidation as the disease progresses to the
severe or critical stages.
The ultrasonic sign of a small consolidation is a local sub-
pleural hypoechoic signal, while a large consolidation has a
characteristic hepatization. Air bronchogram presented with
penetration of gas through the bronchus into consolidation
during inspiration.25 There was no gas between the subpleural
lung consolidation and chest wall, thus providing a good
acoustic window for LUS examination of subjects with
COVID-19. Moreover, we observed that 12 (12.6%) subjects
displayed pleural effusions, which was caused by the accu-
mulation of exudate in the chest with the progress of pneumo-
nia. Until now, limited pathological reports from postmortem
biopsies showed pulmonary edema, diffuse alveolar dam-
age, desquamation of pneumocytes, and hyaline mem-
brane formation in subjects with severe COVID-19.26
The LUS findings of subjects with severe and critical
COVID-19 in this study are in accordance with other
recent pathological results.
In our study, 93 (96.9%) subjects had bilateral lung
involvement. The incidence of bilateral or unilateral lung
consolidation and pleural effusion in the group with critical
COVID-19 was higher than that in the severe group. These
results indicate that lung consolidation and pleural effusion
are more likely to exist in critically ill patients with COVID-
19. The consolidation in critically ill subjects showed a
marked increase in prevalence in most lung regions, including
bilateral lateral lung, bilateral posterior lung area, and left an-
terior-inferior lung. In these regions, the proportion of B-lines
in the left inferior-lateral and right posterior-superior lung
region of the critically ill group was lower than that in the
group with severe COVID-19. These findings might be due
to the progress of the disease, as the ultrasonic signs evolved
from B-lines to consolidation, even with pleural effusion.
In the 11 subjects who had repeat LUS, 2 progressed from
the severe stage to the critical stage; this was accompanied by
changes in the LUS patterns. In these 2 subjects, the major
change of LUS abnormalities at follow-up was the progression
of consolidation. This finding indicates that lung pathology
could develop to consolidation with lesion progression, and
different LUS features may correlate with the severity of the
lung injury in subjects with COVID-19. The changes of LUS
features on repeated LUS suggests that bedside LUS may be a
useful follow-up tool for the serial assessment of lung involve-
ment in subjects with confirmed COVID-19.
The LUS score depends mainly on the involved lung
regions and ultrasonic features, such as B-lines and
consolidation, which can quantify the extent of lung
lesions. In our cohort, the LUS scores of critical COVID-19
cases were higher than those of severe cases. These results
suggest more severe lung injury in critically ill patients, and
the LUS score may reflect the progression of lung lesions.
In addition, we noted a weaker correlation between LUS
score and oxygen flow and oxygen saturation in this study,
which may also indicate that LUS reflects the degree of dis-
ease to some extent. Previous studies have reported good
correlation between the total number of B-lines score and
the high-resolution CT simplified score in subjects with in-
terstitial lung disease.27 Similarly, there was also a strong
correlation between the LUS score and the chest CT score,
which was used as a semi-quantitative approach to assess
the extent and severity of infectious lung disease.27,28 Our
results demonstrate the value of LUS for the assessment of
COVID-19 compared to the use of chest CT, which had
been recommended as the first-line imaging test for identi-
fying pneumonia. In addition, CT imaging studies have
reported that early-stage lung lesions in subjects with
COVID-19 are mainly located peripherally and subpleur-
ally, and the distribution diffuses with the progress of the
disease.17 Because lung ultrasonic signs originate from the
pleura line, the characteristics of subpleural region involve-
ment can improve the accuracy of the LUS examination in
patients with COVID-19.
Our data indicate that lung consolidations are mainly
located in the posterior lung regions, followed by the lateral
and anterior areas, which may be related to the gravity
effect in supine position. It is worth noting that patients
with COVID-19 often take the original supine position for
bedside LUS examinations, and the dorsal lung region had
a greater tendency to be involved with consolidation.
Therefore, patients with COVID-19 need to be assisted in
prone or lateral decubitus positions to fully expose the chest
wall and expand the scope of the scan, which helps compre-
hensively assess the extent of lung injury.
There are several limitations in this study. First, this was
a retrospective analysis, so extrapolation of our results
could be affected by local bias; a prospective study using
LUS would have greater scientific value. Second, because
our center was a designated hospital to treat severe and crit-
ically ill patients with COVID-19 pneumonia in China, we
could not obtain data from milder cases of COVID-19.
Accordingly, our findings may not be applicable to the
entire COVID-19 population. Third, this is a single-center
study and is limited by the small sample size in our hospi-
tal. Therefore, multicenter studies with larger sample sizes
are needed to confirm our findings. …
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