Keywords
brachial plexus injury - phrenic nerve transfer - COVID-19 acute infection - respiratory
symptoms
Introduction
The phrenic nerve as donor for nerve reconstruction in traumatic brachial plexus injuries
(BPI) is commonly used in several specialized centers worldwide.[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13] It is a convenient donor that can be easily harvested at the supraclavicular region
during brachial plexus exploration and can reach important target nerves, such as
the branches of the upper trunk with nerve transfer, or to the musculocutaneous nerve
via nerve graft.[14] Including the phrenic nerve in the arsenal of donor nerves could be essential in
brachial plexus reconstruction, especially in severe BPI like panplexus or C5–C8 injuries
when the scarcity of donors renders reconstruction of multiple functions nearly impossible.
Contraindications include obese patients, age < 3 years old, previous thoracic trauma,
and arguably those with chronic lung disease and old age. It has been reported that
the respiratory function meliorates after this nerve transfer in a certain period
of time.[10]
[11]
[12]
[13]
[14]
However, the coronavirus disease 2019 (COVID-19) pandemic has arisen in the world,
and multiple studies have found permanent respiratory deficits after severe bouts
of pneumonia[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24] and also directly affecting the phrenic nerve, producing its palsy, thus potentially
exacerbating the respiratory insufficiency in those cases where the phrenic nerve
was used as the donor.[7]
[18]
[25]
To analyze the effects that the infection by coronavirus might have produced on them,
we studied two populations of different ethnicities who, prior to March 2020, underwent
a phrenic nerve transfer to restore a lost function during a traumatic BPI. Two experienced
nerve centers localized in different countries—Taiwan and Argentina—were enrolled.
The reason for including these two countries was to analyze the results of two experienced
centers that frequently use the phrenic nerve as a donor in BPIs, studying different
ethnicities, geographies, and morphology of the COVID-19 pandemic. The objectives
of the present work were: (1) to identify the rate of COVID in patients with a history
of phrenic nerve transfer for treatment of palsy; (2) to identify the overall symptom
profile and rate of significant respiratory symptoms in patients after phrenic nerve
transfer who develop COVID-19; (3) to compare the Argentinian versus the Taiwanese
patients; and (4) to compare COVID cases who report significant respiratory symptoms
(other than cough) versus those who do not, to determine if any phrenic nerve transfer
patients are at particular risk of more severe COVID. The rationale of this study
was to answer an important question: did the previous medical history of complete
sectioning of the phrenic nerve—and its potential negative effect on the respiratory
function—really affect the course of the acute phase of a COVID-19 infection?
Materials and Methods
Materials
The total of patients who underwent phrenic nerve transfer to treat brachial plexus
palsy at the two participating centers was included. Inclusion criteria were BPI patients
who were operated before the COVID-19 pandemic and underwent a complete phrenic nerve
section and suture to a distal nerve target to reinnervate one or more paralyzed muscles.
Exclusion criteria for phrenic nerve harvesting were the same in both countries: age
less than 3 years old or more than 50, obesity, chronic lung diseases such as chronic
obstructive pulmonary disease or interstitial lung disease. A telephonic survey that
included data regarding the number of episodes of acute COVID-19 infection, the symptoms
it caused, the presence or not of potential or life-threatening complications, and
the status of COVID-19 vaccination at the moment of the acute infections was studied
([Table 1]). Exclusion criteria for being considered to be part of the present series are patients
who were operated on after the COVID-19 pandemic, who were lost to follow-up, or who
have a history of chronic lung diseases. The study was performed in full accordance
with the Declaration of Helsinki II and both institution's ethics committees.
Table 1
Telephonic survey
1- Do you have any medical comorbidity?
|
2- Did you have COVID-19?
|
3- What number of episodes?
|
4- How was diagnosticated?
|
5- Which were the symptoms in each episode?
|
6- Had you ever been admitted to the hospital during the acute phase of the COVID/19
infection? In which episode/episodes? In which part of the hospital were you admitted?
(ICU, normal room)
|
7- Were you intubated during any of the episodes?
|
8- Had you presented dyspnea during any acute episode of COVID-19?
|
9- Did you receive any vaccine for COVID-19? When and how many?
|
Abbreviations: COVID-19, coronavirus disease 2019; ICU, intensive care unit.
Statistical Analysis
All continuous variables are expressed as means with ranges, with categorical variables
summarized as absolute numbers and percentages. Since all the continuous variables
(e.g., patient age) were found to have non-normal distributions using the Shapiro–Wilk
test, intergroup comparisons were conducted using the nonparametric Mann–Whitney U
test, with intergroup comparisons of categorical variables conducted using either
the Pearson χ2 analysis or the Fisher's exact test, as appropriate. Since we considered
the study exploratory, a two-tailed, unadjusted p ≤ 0.05 was used as the criterion for statistical significance. Given the minimal
number of COVID-19 patients with respiratory symptoms beyond cough (N = 4), multivariable analysis to identify predictors of respiratory dysfunction was
considered inappropriate. SPSS version 28.0 (IBM Corp., Armonk, New York, United States)
was the statistical software package used for all analyses.
Results
A total of 77 patients or their families of a total of 168 completed the survey, 40
from Taiwan and 37 from Argentina. The earliest operative date included in this cohort
was in January 2005, and the latest in February 2020, all before the beginning of
the COVID-19 pandemic. Patients referred to have undergone the acute/s infection in
a period ranging from March 2020 to January 2023, at the latest. As seen in the characteristics
of the sample ([Table 2]), patients were relatively young: almost 80% were under 40 years old, and predominantly
(84.4%) were males, with Argentina and Taiwan reasonably equally represented. Of the
77 patients, 55 (71.4%) developed a diagnosis of COVID. However, among these, only
four had any level of dyspnea reported (4/55 = 7.3%), all mild. There also were no
admissions to hospital or an intensive care unit (ICU), no intubations, and no deaths.
All 55 patients isolated themselves at home.
Table 2
Characteristics of the sample
Characteristics
|
N
|
%
|
Total number, N
|
77
|
|
Age, (y)
|
|
|
Mean (SD)
|
29.5 (11.6)
|
|
Range
|
10–63
|
|
Age group
|
|
|
Under 20 y old
|
15
|
19.5
|
20–39 y old
|
46
|
59.7
|
40 y and over
|
16
|
20.8
|
Sex
|
|
|
Females
|
12
|
15.6
|
Males
|
65
|
84.4
|
Country
|
|
|
Argentina
|
37
|
48.1
|
Taiwan
|
40
|
51.9
|
Years (surgery to pandemic)
|
|
|
<5
|
56
|
72.7
|
5–9
|
16
|
20.8
|
10+
|
5
|
6.5
|
Mean (SD)
|
3.71 (2.91)
|
|
Range
|
0–15
|
|
Diabetes
|
3
|
3.9
|
Hypertension (requiring treatment)
|
2
|
2.6
|
Any currently active comorbid condition
|
6
|
7.8
|
COVID
|
|
|
Confirmed by nasal swab
|
41
|
53.2
|
Suspected due to close contact
|
14
|
18.2
|
Total number of COVID cases
|
55
|
71.4
|
Argentina (N = 37 surgery patients)
|
25
|
67.6[a]
|
Taiwan (N = 40 surgery patients)
|
30
|
75.0[b]
|
Swab test +
|
|
|
Argentina (N = 25 COVID cases)
|
11
|
44.0[c]
|
Taiwan (N = 30 COVID cases)
|
30
|
100.0[d]
|
Symptoms (N = 55 cases)
|
|
|
Asymptomatic
|
9
|
16.4
|
Nonrespiratory symptoms
|
9
|
16.4
|
Cough but no dyspnea
|
33
|
60.0
|
Mild dyspnea
|
4
|
7.3
|
More severe dyspnea
|
0
|
0.0
|
Admitted to a hospital
|
0
|
0.0
|
Admitted to an ICU
|
0
|
0.0
|
Intubated
|
0
|
0.0
|
Died from COVID or any other cause
|
0
|
0.0
|
Abbreviations: COVID-19, coronavirus disease 2019; ICU, intensive care unit; SD, standard
deviation.
a Out of 37 Argentinian patients.
b Out of 40 Taiwanese patients.
c Out of 27 Argentinian patients with COVID.
d Out of 30 Taiwanese patients with COVID.
In [Table 3], note that Taiwanese and Argentinian patients were quite different in several measures,
with Taiwanese patients being younger, more likely to be female, almost all having
developed COVID after at least one coronavirus vaccination (96.7 vs. 60.0%), and all
having had COVID confirmed by nasal swab test (vs. just 44.4% among Argentinian patients).
They also had undergone much more recent phrenic nerve transfers. Despite these differences,
the two countries did not differ in the rate of COVID, number of episodes, or percentage
of patients with respiratory symptoms (10% or less in both countries).
Table 3
Taiwanese versus Argentinian sample
Characteristics
|
Argentina
|
Taiwan
|
Test statistic (df)
|
Significance, p
|
Odds ratio (95% CI)
|
N
|
37
|
40
|
|
|
|
Age, mean
|
32.9
|
26.40
|
MWU = 341.5 (1)
|
p < 0.001
|
NA
|
Range
|
15–51
|
10–63
|
|
|
NA
|
% under 20 y old
|
2.7%
|
35.0%
|
χ2 = 12.95 (2)
|
p = 0.002
|
NA
|
% 20–39 y old
|
70.3%
|
50.0%
|
|
|
|
% 40 y and over
|
37.0%
|
15.0%
|
|
|
|
% Female
|
5.4%
|
15.0%
|
χ2 = 5.61 (1)
|
p = 0.018
|
OR = 5.85 (1.83, 28.57)
|
Diabetes
|
0.0%
|
7.5%
|
FE
|
p = 0.24
|
NA
|
Hypertension (requiring treatment)
|
0.0%
|
5.0%
|
FE
|
p = 0.49
|
NA
|
Any currently active comorbid condition
|
2.7%
|
12.5%
|
χ2 = 2.57 (1)
|
p = 0.11
|
OR = 0.19 (0.02, 1.75)
|
% 5–9 y
|
2.5%
|
40.5%
|
|
|
|
% ≥ 10 y
|
0.0%
|
13.5%
|
|
|
|
Diagnosed with COVID-19, yes
|
67.6%
|
75.0%
|
χ2 = 0.52 (1)
|
p = 0.47
|
OR = 1.44 (0.53, 3.89)
|
When COVID diagnosed, before COVID vaccination
|
40.0%
|
3.3%
|
χ2 = 11.46 (1)
|
p < 0.001
|
OR = 19.23 (2.26, 165.7)
|
After COVID vaccination
|
60.0%
|
96.7%
|
|
|
|
COVID confirmed by nasal swab
|
44.0%
|
100.0%
|
χ2 = 22.54 (1)
|
p < 0.001
|
OR = 3.73 (2.25, 6.18)
|
Number of episodes, mean
|
0.78
|
0.88
|
MWU = 810.0
|
p = 0.41
|
NA
|
Range
|
0–3
|
0–2
|
|
|
|
0 episodes
|
32.4%
|
25.0%
|
χ2 = 2.55 (3)
|
p = 0.47
|
NA
|
1 episode
|
59.5%
|
62.5%
|
|
|
|
2 episodes
|
5.4%
|
12.5%
|
|
|
|
3 episodes
|
2.7%
|
0.0%
|
|
|
|
COVID cases with COVID-related dyspnea
|
10.0%
|
4.0%
|
χ2 = 0.73
|
p = 0.39
|
OR = 2.67 (0.26, 27.38)
|
Abbreviations: COVID-19, coronavirus disease 2019; df, degrees of statistical freedom;
FE, Fisher's exact test; MWU, nonparametric Mann–Whitney U test; NA, not applicable;
OR, odds ratio.
In [Table 4], note that both a history of diabetes mellitus (p < 0.001) and a history of any comorbidity (p = 0.003) were associated with increased odds of having respiratory symptoms in the
55 patients who developed COVID. No other factors were predictors.
Table 4
Comparing coronavirus disease cases experiencing coronavirus disease-related respiratory
dysfunction (other than cough or sore throat)
Characteristics
|
Nonrespiratory Sx
|
Respiratory Sx
|
Test statistic (df)
|
Significance, p
|
Odds ratio (95% CI)
|
N
|
51
|
4
|
|
|
|
Age, mean
|
27.7
|
30.0
|
MWU = 127.0 (1)
|
p = 0.58
|
NA
|
Range
|
10–59
|
21–38
|
|
|
|
% under 20 y old
|
21.6%
|
0.0%
|
χ2 =2.47 (2)
|
p = 0.29
|
NA
|
% 20–39 y old
|
60.8%
|
100.0%
|
|
|
|
% 40 y and over
|
17.6%
|
0.0%
|
|
|
|
% Female
|
13.7%
|
25.0%
|
χ2 = 0.38 (1)
|
p = 0.54
|
OR = 2.10 (0.19, 2.13)
|
Diabetes
|
2.0%
|
50.0%
|
FE
|
p = 0.049
|
OR = 50.0 (3.09, 810.5)
|
Hypertension (requiring treatment)
|
3.9%
|
0.0%
|
FE
|
p = 1.00
|
NA
|
Any currently active comorbid condition
|
5.9%
|
50.0%
|
FE
|
p = 0.037
|
OR = 16.0 (1.64, 156.6)
|
Years from surgery to pandemic, mean
|
3.86
|
3.00
|
MWU = 80.0 (1)
|
p = 0.60
|
|
Range
|
1–15
|
1–6
|
|
|
|
% under 5 y
|
70.6%
|
75.0%
|
χ2 = 0.25 (2)
|
p = 0.88
|
|
% 5–9 y
|
23.5%
|
25.0%
|
|
|
|
% ≥ 10 y
|
5.9%
|
0.0%
|
|
|
|
When COVID diagnosed Before COVID vaccination
|
21.6%
|
0.0%
|
FE[b]
|
p = 0.53
|
NA[a]
|
After COVID vaccination
|
78.4%
|
100.0%
|
|
|
|
COVID confirmed by nasal swab
|
90.2%
|
100.0%
|
χ2 = 1.47 (1)
|
p = 0.23
|
NA[a]
|
Number of episodes, mean
|
1.14
|
1.50
|
MWU = 140.0
|
p = 0.18
|
|
Range
|
1–3
|
1–2
|
|
|
|
1 episode
|
88.2%
|
50.0%
|
χ2 = 5.42 (2)
|
p = 0.066
|
NA
|
2 episodes
|
9.8%
|
50.0%
|
|
|
|
3 episodes
|
2.0%
|
0.0%
|
|
|
|
Abbreviations: df, degrees of statistical freedom; FE, Fisher's exact test; MWU, nonparametric
Mann–Whitney U test; NA, not applicable; OR, odds ratio; Sx, symptoms.
a 0.48.
b 0.56.
Discussion
As mentioned, one of the most significant potential drawbacks of using the phrenic
nerve as an axon donor in severe BPI is the potential risk of respiratory impairment.
This argument was heightened in the COVID era. Due to the severe lung disease that
this pandemic produced in many patients with acute infections, the idea that a patient
with a phrenic nerve transfer performed before the infection could have a respiratory
problem was conceivable. Undoubtedly, the most important finding of this article is
that none of the extensive series of patients analyzed herein (n = 77) was admitted to the ICU or even to the hospital, intubated, or died in the
acute setting of a COVID-19 infection ([Table 2]). Of note, most patients (n = 55 out of 77; 25 of 37 in Argentina vs. 30 out of 40 in the Taiwanese counterparts)
underwent one or more than one acute COVID infection. The worst symptom that our patients
showed was mild dyspnea, and this finding was not frequent (n = 4, 7.3%). This percentage is similar to what similar populations—regarding age,
sex, and clinical history—showed.[16]
[20]
[26]
[27]
[28]
[29]
[30]
[31]
[32]
Indeed, the absence of complications in our population is biased by our patient selection
process: to be selected for using a unilateral phrenic nerve transfer (end to end)
for a brachial plexus reinnervation, the candidates have to be older than 3, not too
elderly, have good respiratory function, and not obese. These patients typically did
not exhibit intolerable complications during an acute COVID-19 infection.[22]
[33]
[34]
[35]
[36] However, the alleged selection bias is a protection circumstance accepted extensively
in the centers where this type of nerve transfer is usually performed, and the findings
demonstrate that this exclusion criterion worked well in our population.
When compared, the patients from the two countries involved didn't show statistically
significant differences ([Table 3]). Nevertheless, the rate of medical comorbidities (hypertension or diabetes, among
others) was higher in Taiwanese patients than in Argentinians (12.5 vs. 2.7%, respectively).
Patients from Argentina were younger (26.4 years old vs. 32.9 in Taiwan) and were
more likely to be males (5.4% of females vs. 15% in Taiwan). Remarkably, two statistically
significant geographical differences were found between the two countries: all patients
in Taiwan were diagnosed with nasal swabs, a percentage that diminishes to 44% in
Argentina, and most of the former group of patients had the first or subsequent COVID-19
acute episode after vaccination (60%), adversely to Argentinians (40%). The well-study
phenomena of the COVID-19 pandemic hitting the isle of Taiwan later than in other
continental countries (starting in 2021 vs. a rude start in 2020 in South and North
America and in Europe)[37]
[38]
[39]
[40]
[41] can explain why most of the Taiwanese were already vaccinated when they experienced
the first COVID-19 infection. The difference in access to nasal swabs in suspected
cases between the two countries can not only explain the differences in diagnosis
between the two groups but also the mildly higher tendency—yet not significant—verified
in Taiwan to undergo more episodes of COVID-19.
When comparing COVID cases experiencing COVID-related respiratory dysfunction other
than cough or sore throat ([Table 4]), we found that diabetic patients, or those who showed any comorbidity at the moment
of suffering an acute COVID-19 infection, evidence a higher percentage of respiratory
symptoms (50 vs. less than 6%). Again, these data are unsurprising and align with
what could be expected to happen in persons with a specific clinical report who are
affected by a respiratory virus such as COVID-19.
The most significant limitation of statistical analysis was the small number of patients
with respiratory symptoms, which markedly reduced the study's statistical power and
eliminated the potential to perform regression analysis. Another limitation is the
lack of a control group. However, indeed, it can be assumed that the risk of presenting
an acute COVID-19 infection is similar in patients having a traumatic BPI when compared
with another population matched accordingly in demographic terms.
Conclusions
Although COVID was common in the studied patients, it was notable that the analyzed
groups presented a very low rate of respiratory symptoms (just 4 of 77 patients) and
lacked any need for hospitalization (all patients recovering at home), so no deaths
were reported. Also, two predictors of increased odds of respiratory symptoms identified
on bivariable analysis were a history of diabetes and a history of any severe medical
comorbidity. It can be concluded that an acute COVID-19 infection was very well tolerated
in our patients.