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ORIGINAL STUDIES
THYROID FUNCTION AND DYSFUNCTION
Thyroid Hormone Levels During Hospital Admission Inform
Disease Severity and Mortality in COVID-19 Patients
Fabyan Esberard de Lima Beltra˜o,
1–3
Daniele Carvalhal de Almeida Beltra˜o,
3
Giulia Carvalhal,
4,i
Fabricia Elizabeth de Lima Beltra˜o,
3
Amanda da Silva Brito,
1
Kamilla Helen Rodrigues da Capistrano,
2
Isis Henriques de Almeida Bastos,
5
Fabio Hecht,
6
Carla Hila´ rio da Cunha Daltro,
5,7
Antonio Carlos Bianco,
8,ii
Maria da Conceic¸a˜ o Rodrigues Gonc¸ alves,
2
and Helton Estrela Ramos
5,9,10,iii
Background: Illness severity in patients infected with COVID-19 is variable.
Methods: Here, we conducted an observational, longitudinal, and prospective cohort study to investigate serum
thyroid hormone (TH) levels in adult COVID-19 patients, admitted between June and August 2020, and to de-
termine whether they reflect the severity or mortality associated with the disease.
Results: Two hundred forty-five patients [median age: 62 (49–75) years] were stratified into non-critical (181)
and critically ill (64) groups. Fifty-eight patients (23.6%) were admitted to the intensive care unit, and 41 (16.7%)
died. Sixteen (6.5%) exhibited isolated low levels of free triiodothyronine (fT3). fT3 levels were lower in crit-
ically ill compared with non-critical patients [fT3: 2.82 (2.46–3.29) pg/mL vs. 3.09 (2.67–3.63) pg/mL,
p=0.007]. Serum reverse triiodothyronine (rT3) was mostly elevated but less so in critically ill compared with
non-critical patients [rT3: 0.36 (0.28–0.56) ng/mL vs. 0.51 (0.31–0.67) ng/mL, p=0.001]. The univariate
logistic regression revealed correlation between in-hospital mortality and serum fT3 levels (odds ratio [OR]:
0.47; 95% confidence interval [CI 0.29–0.74]; p=0.0019), rT3 levels (OR: 0.09; [CI 0.01–0.49]; p=0.006) and
the product fT3 ·rT3 (OR: 0.47; [CI 0.28–0.74]; p=0.0026). Serum thyrotropin, free thyroxine, and fT3/rT3
values were not significantly associated with mortality and severity of the disease. A serum cutoff level of fT3
(£2.6 pg/mL) and rT3 (£0.38 ng/mL) was associated with 3.46 and 5.94 OR of mortality, respectively. We
found three COVID-19 mortality predictors using the area under the receiver operating characteristic (ROC)
curve (AUC score): serum fT3 (AUC =0.66), rT3 (AUC =0.64), and the product of serum fT3 ·rT3 (AUC =
0.70). Non-thyroidal illness syndrome (fT3 <2.0 pg/mL) was associated with a 7.05 OR of mortality ([CI 1.78–
28.3], p=0.005) and the product rT3 ·fT3 £1.29 with an 8.08 OR of mortality ([CI 3.14–24.2], p<0.0001).
Conclusions: This prospective study reports data on the largest number of hospitalized moderate-to-severe
COVID-19 patients and correlates serum TH levels with illness severity, mortality, and other biomarkers to
critical illness. The data revealed the importance of early assessment of thyroid function in hospitalized patients
with COVID-19, given the good prognostic value of serum fT3, rT3, and fT3·rT3 product. Further studies are
necessary to confirm these observations.
Keywords: COVID-19, free T3, reverse T3, SARS-CoV-2, thyroid, thyroid hormones
1
Department of Endocrinology, Lauro Wanderley University Hospital, Federal University of Paraı
´ba, Joa
˜o Pessoa, Brazil.
2
Post-Graduation Program in Nutritional Sciences, Department of Nutrition, Center for Health Sciences, Federal University of Paraı
´ba,
Joa
˜o Pessoa, Brazil.
3
Department of Medicine, Faculty of Medical Sciences, Joa
˜o Pessoa, Brazil.
4
Center for Biological and Health Sciences, Federal University of Campina Grande, Campina Grande, Brazil.
5
Post-Graduate Program in Medicine and Health, Medical School of Medicine;
7
Department of Nutrition Sciences;
9
Postgraduate
Program in Interactive Processes of Organs and Systems, Health & Science Institute;
10
Bioregulation Department, Health and Science
Institute; Federal University of Bahia, Salvador, Brazil.
6
The Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
8
Section of Endocrinology and Metabolism, Division of the Biological Sciences, University of Chicago, Chicago, Illinois, USA.
i
ORCID ID (https://orcid.org/0000-0003-3386-5855).
ii
ORCID ID (https://orcid.org/0000-0001-7737-6813).
iii
ORCID ID (https://orcid.org/0000-0002-2900-2099).
THYROID
Volume 31, Number 11, 2021
ªMary Ann Liebert, Inc.
DOI: 10.1089/thy.2021.0225
1639
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Introduction
SARS-CoV-2is the etiologic agent of a syndrome
that mostly affects the respiratory system, first detected
in Wuhan, China, in December 2019 (1). Patients with
COVID-19, particularly those with advanced age, diabetes,
and/or hypertension, exhibited overcritical health status at
admission, with death occurring within two to three weeks
after disease onset (2–6).While most patients developed non-
thyroidal illness syndrome (NTIS), and some subacute thy-
roiditis (SAT), it is not clear whether serum thyroid hormone
(TH) reflects or impacts the severity or mortality associated
with the disease (7–10).
The SARS-CoV-2 spike protein uses the angiotensin-
converting enzyme 2 (ACE-2) as a receptor and thyroid sur-
gical specimens have a high level of ACE-2 mRNA, making
it a potential target for the SARS-COV-2 (11). In May 2020,
the first SAT case after a SARS-CoV-2 infection was repor-
ted (12). A subsequent study that analyzed fifty COVID-19
patients’ records found that 56% had low thyrotropin (TSH)
serum levels and that the decreases in TSH and total triio-
dothyronine levels correlated positively with the severity of
the disease. These abnormal thyroid function parameters are
suggestive of NTIS (13). In another study, 85 COVID-19
patients admitted to the intensive care unit (ICU) had clinical
SAT sign, and 15% had suppressed serum TSH and elevated
free thyroxine (fT4) levels (14).
Just as with any other severe illness, TH levels may be
abnormal in COVID-19 patients, with predominantly a re-
duction in serum triiodothyronine (T3) (serum thyroxine
[T4], may be decreased as well) and an elevation in reverse
triiodothyronine (rT3) levels (15–19). This combination in
the setting of a life-threatening disorder that depends on the
support of vital organ function is known as NTIS. The re-
duction in serum T3 levels is due to decreased thyroidal
secretion and slower conversion of T4 to T3, whereas the
elevation in rT3 levels is usually caused by a slower clearance
rate and, in some cases, accelerated inner ring deiodination
of T4 (16). These changes in TH economy might have a
decisive role in the earliest phase of critical illness and rou-
tinely reflect the illness’ severity (7,8,10,15). In the case of
COVID-19 patients, the drop in serum T3 could also have
prognostic function given that T3 modulates lung function
and alveolar drainage (20–22), and cellular immunity (17,23).
In the specific case of COVID-19 patients, the increased
levels of cytokines and glucocorticoids, from either endog-
enous or exogenous sources, are potential mediators of thy-
roid axis suppression (24). Indeed, it has been reported that in
COVID-19 patients there is an association between low free
triiodothyronine (fT3) and disease severity, 28-day mortality
rate, and hospitalization expenses in ICU (8–10). However,
these studies were limited by the small cohort size, criteria
definition for NTIS, for being retrospective analyses, and
inconsistency as to when thyroid function tests were obtained
(25–27).
While the COVID-19 epidemic in Brazil grows, details
of its clinical characteristics remain poorly understood. Early
recognition of patients at a high risk of developing serious
illness is essential to improve disease outcomes (28,29).
Here, we investigated changes in TH economy and the inci-
dence of NTIS in SARS-CoV-2 patients admitted to a tertiary
hospital and whether there is an association between TH lev-
els with serum pro-inflammatory biomarkers and COVID-19
severity and mortality.
Methods
Subjects and data collection
An observational, longitudinal, and prospective cohort
study was conducted between June and August 2020, and we
enrolled 245 consecutive patients with confirmed COVID-19
admitted to the Metropolitan Hospital Dom Jose
´Maria Pires,
a tertiary referral hospital in Joa
˜o Pessoa, Paraı
´ba, Brazil
(Fig. 1). A written consent form was obtained from the par-
ticipants or legal representative. The study was approved by
the Human Research Ethics Committee of the Lauro Wan-
derley University Hospital (CAAE:31562720.9.0000.5183).
FIG. 1. Flowchart of the study.
1640 BELTRA
˜O ET AL.
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Inclusion and exclusion criteria
All patients tested positive for SARS-CoV-2 using the
quantitative real-time reverse-transcriptase-polymerase chain
reaction (rRT-qPCR) with samples from the respiratory tract
and, in cases of negative rRT-qPCR, using clinical, radio-
logical (ground-glass opacities, with or without consolida-
tion, located near visceral pleural surfaces, and multifocal
bilateral distribution—CO-RADS 5) (30), and serological
(IgG positive for SARS-CoV-2) criteria. The rRT-PCR kit
used Biomol OneStep/COVID-19, IBMP, Parana
´, Brazil.
Patients with a history of thyroid disease, diagnosis of preg-
nancy, and who used iodinated contrast in the past six months
or drugs that interfere with thyroid metabolism were excluded.
Outcomes
The primary goal of the study was to determine the inci-
dence of NTIS (serum fT3 levels <2.0 pg/mL, fT4 and TSH
levels within or below the normal reference ranges) in con-
secutive SARS-CoV-2 patients admitted to a tertiary hospital
specialized in COVID-19. Additional exploratory analyses to
study the predictive value of NTIS and serum TH levels were
collected during the first 48 hours of admission, for disease
severity and patient mortality.
Procedures
The detailed clinical information of each patient was
obtained by physicians using a standard questionnaire. Two
severity scoring systems were used on admission: (i) the
quick Sepsis-related Organ Failure Assessment, (ii) the
National Early Warning Score 2. Patients underwent chest
computed tomography (CT) at hospital admission to inves-
tigate a suspected SARS-CoV-2 pneumonia. In all cases, a
semi-quantitative CT severity score proposed by Pan et al.
(31) was calculated for each of the five lobes, considering the
extent of anatomical involvement.
All cases were divided into two clinical classifications:
severe and critical. Severe (non-critical) cases were classified
for patients who met any of the following criteria: respiratory
rate >30 cycles/min, oxygen saturation <93% at rest, partial
arterial pressure of oxygen (PaO2)/concentration of oxygen
(FiO2) <300 mmHg (1 mmHg =0.133 kPa), and extent of
lung injury (ground-glass opacity) estimated >50%. Critical
cases were considered for patients who meet any of the fol-
lowing criteria: manifestation of respiratory failure requiring
mechanical ventilation, presence of shock, and other organic
failures that need follow-up and treatment in an ICU. For
patients who met the inclusion criteria, blood samples were
collected before interventions or therapy that could poten-
tially interfere or alter TH or cytokines serum levels, always
performed within the first 48 hours of admission.
Serum biochemistry
The complete blood cells count, and measurement of the
lymphocyte and neutrophils subpopulations were measu-
red by using a hematological analyzer MEK-7300 (Nihon
Kohden
, Tokyo, Japan). Alanine transaminase (ALT), as-
partate aminotransferase, creatinine, high-sensitive C-
reactive protein (CRP), D-dimer and lactate dehydrogenase
(LDH), thyroid function (fT3, fT4, rT3, TSH), thyroglobulin,
anti-thyroid peroxidase antibodies, interleukin 6 (IL-6), and
ferritin were measured by chemiluminescence immunoassay
(MAGLUMI-2000-PLUS; Shenzhen New Industries Bio-
medical Engineering Co., Shenzhen, China) according to the
manufacturer’s protocol.
Statistical analyses
A statistical power analysis was performed for sample size
estimation. The effect size in this study was conservatively
selected at the f2 =0.10. With an alpha =0.05 and power =
0.95, the projected sample size needed with this effect size
using GPower 3.1.9.7 is approximately N=158 for a linear
regression analysis with two predictors. Thus, our sample
size of 245 was more than adequate for the primary outcome
of this study and should also allow for expected attrition. The
data were expressed as median –interquartile range. Mann–
Whitney, Chi-square, or Fisher’s test were used for non-
parametric variables. To assess the relative risk of mortality,
we used univariate and multivariate logistic regression. We
evaluated each variable as a potential biomarker by using re-
ceiver operating characteristic (ROC) curves. The significance
level of p<0.05 was accepted as statistically significant. The
statistical program GraphPad Prism, v.7.00 (2016), was used
to perform statistical tests.
Results
Two hundred seventy-four adult patients consecutively
admitted with COVID-19 were considered for potential en-
rollment in the study, and after assessment of inclusion and
exclusion criteria, 245 were enrolled (Fig. 1). The median
age was 62 (49–74.5) years, and 145 patients (59.1%) were
males. The average hospital stay was 8.3 days. Fifty-eight
patients (23.6%) were admitted to the ICU, of whom 41
(16.7%) later died. Table 1 summarizes baseline sociodemo-
graphic and clinical characteristics.
TH levels
On admission (first 48 hours), 54 (22.0%) patients pre-
sented with normal serum TSH, fT3, fT4 and rT3 levels. The
remaining 191 patients exhibited multiple alterations in TH
levels, which could be stratified in two major groups: (i) 154
(62.8%) patients with elevated serum rT3 levels, of whom
31 and 18 also had elevated or reduced serum fT4 levels,
respectively; (ii) 18 individuals with isolated high serum fT4
levels (Fig. 2A, B). A smaller number of individuals (n=16)
exhibited low serum fT3 levels associated with fT4 and
TSH levels within or lower than normal range, which were
in most cases (n=11) associated with high serum rT3 lev-
els. Lastly, there were 15 individuals with suppressed serum
TSH and elevated serum rT3 levels (Fig. 2). None of the
patients enrolled exhibited clinical signs of hypothyroidism
or thyrotoxicosis.
The utilization of clinical and biochemical criteria led us
to stratify all 245 patients, within the first 48 hours, into 181
non-critical and 64 critically ill patients (Table 2). Whereas
serum TSH and fT4 serum levels were similar in both groups,
critically ill patients exhibited lower serum fT3 and high-
normal rT3 levels, which, although elevated, were not as high
as compared with non-critical patients (Fig. 3 and Table 2).
THYROID HORMONE LEVELS AND MORTALITY IN COVID-19 1641
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Table 1. Demographic and Clinical Characteristics of the Cohort in Patients Non-Critical
and Critical and Their Association with Mortality
Variable
Total
(n=245)
Severity Mortality
Non-critical
(n=181)
Critical
(n=64) p
Survivor
(n=204)
Non-survivor
(n=41) p
Age (years),
median (IQR)
62 (49–74.5) 62 (49–74) 63.5 (50–75) 0.2981 62 (49–73.7) 63 (49–76.5) 0.298
Age >60 years, n(%) 133 (54.3) 94 (52) 39 (60.9) 0.2441 109 (53.4) 24 (58.5) 0.6084
Sex male, n(%) 145 (59.1) 109 (60) 36 (56.2) 0.6574 122 (59.8) 23 (56.1) 0.7285
Comorbidities, n(%)
Hypertension 163 (66.5) 116 (64) 47 (73.4) 0.2177 135 (66.1) 28 (68.3) 0.857
Diabetes mellitus 107 (44.6) 76 (41.9) 31 (48.4) 0.3829 87 (42.6) 20 (48.7) 0.4939
Cardiopathy 34 (13.8) 27 (14.9) 7 (10.9) 0.5305 32 (15.7) 2 (4.8) 0.0828
Neoplasia 2 (0.8) 1 (0.5) 1 (1.5) 0.4550 1 (0.5) 1 (2.4) 0.3073
Chronic pneumopathy 11 (4.4) 10 (5.5) 1 (1.5) 0.2970 10 (4.9) 1 (2.4) 0.6964
Positivity for TPOAb 28 (11) 19 (10.5) 8 (12.5) 0.6473 22 (10.8) 5 (12.2) 0.7860
Complications
Use of vasoactive
drugs, n(%)
30 (12.2) 1 (0.5) 29 (45.3) <0.0001 5 (2.4) 25 (61) <0.0001
Length of hospital stay
(days), median (IQR)
6 (4–10) 5 (4–7) 11 (7.25–17) <0.0001 6 (4–8) 13 (8–17) <0.0001
ICU admission, n(%) 58 (23.6) 0 (0) 59 (90.6) <0.0001 23 (11.2) 35 (85.3) <0.0001
Scores systems, median (IQR)
NEWS2 score 6 (5–7) 6 (4–7) 5 (5–7) 0.3610 6 (4–7) 6 (5–7.5) 0.3122
qSOFA score 1 (1–1) 1 (1–1) 1 (1–1) 0.3547 1 (1–1) 1 (1–1) 0.1716
CT COVID score 20 (15–20) 20 (15–20) 20 (15–20) 0.1051 20 (15–20) 20 (15–20) 0.0619
Thyroid function tests, n(%)
Low TSH and/or
high fT4
67 (27.3) 52 (28.7) 15 (23.4) 0.5143 57 (27.9) 10 (24.4) 0.7050
High thyroglobulin 13 (5.3) 11 (6.1) 2 (3.1) 0.5232 12 (5.9) 1 (2.4) 0.7013
NTIS 16 (6.5) 9 (5) 7 (10.9) 0.136 9 (4.4) 7 (17) 0.008
High rT3 154 (62.8) 121 (66.8) 33 (51.5) 0.035 131 (64.2) 12 (29.2) <0.0001
Low fT3+high rT3 12 (4.9) 7 (3.8) 5 (7.8) 0.3085 7 (3.4) 5 (12.2) 0.033
Low TSH =TSH <0.4 mIU/L; high fT4 =fT4 >1.7 ng/dL; high thyroglobulin =thyroglobulin >59.9 ng/mL; NTIS =serum fT3 levels
<2.0 pg/mL, fT4, and TSH levels within or lower than the normal ranges at diagnosis; high rT3 =rT3 >0.35 ng/mL. Mann–Whitney test was
performed for continuous variables (age, NEWS2, qSOFA and CT COVID score) while Fisher’s exact test was performed for all other variables.
CT, computed tomography; fT3, free triiodothyronine; fT4, free thyroxine; ICU, intensive care unit; IQR, interquartile range; NEWS2,
National Early Warning Score 2; NTIS, non-thyroidal illness syndrome; qSOFA, quick Sepsis Related Organ Failure Assessment; rT3,
reverse triiodothyronine; TPOAb, thyroperoxidase antibodies; TSH, thyrotropin.
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9718
Mortality rate:
Not evaluated due
to small number of
patients
50%
30%
40%
20%
10%
0%
BA
FIG. 2. Venn diagram with the main TH levels alterations distribution observed in 191 COVID-19 hospitalized patients
with abnormal results at admission and relationship with disease mortality rate. (A) With low fT4, low TSH, high rT3
and low fT3; (B) With high fT4, low TSH, high rT3 and Low fT3. Low TSH, TSH <0.4 mIU/L; high fT4, low fT4,
fT4 <0.89 ng/dL; low fT3, fT3 <2.0 pg/mL; high rT3, rT3 >0.35 ng/mL. fT3, free triiodothyronine; fT4, free thyroxine; rT3,
reverse triiodothyronine; TH, thyroid hormone; TSH, thyrotropin.
1642
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Table 2. Variables Measured in Non-Critical and Critical and Their Association with Mortality
Parameters (normal range)
Mann–Whitney test severity
Univariate logistic
regression mortality
Total Non-critical Critical
pOR [CI] pN Median (IQR) NMedian (IQR) NMedian (IQR)
TSH (0.4–5.8 lIU/mL) 245 1.69 (0.97–3.00) 181 1.62 (0.90–3.00) 64 1.76 (1–2.50) 0.863 0.958 [0.776–1.156] 0.676
fT4 (0.89–1.72 ng/dL) 245 1.34 (1.05–1.68) 181 1.34 (1.05–1.70) 64 1.34 (1.01–1.55) 0.371 0.855 [0.435–1.619] 0.641
fT3 (2.0–4.2 pg/mL) 245 2.98 (2.64–3.53) 181 3.09 (2.67–3.63) 64 2.82 (2.46–3.29) 0.007 0.476 [0.293–0.749] 0.0019
rT3 (0.1–0.35 ng/mL) 245 0.49 (0.30–0.66) 181 0.51 (0.31–0.67) 64 0.36 (0.28–0.56) 0.001 0.099 [0.017–0.492] 0.0068
fT3 ·rT3 (0.2–1.47) 245 1.32 (0.82–2.13) 181 1.46 (0.86–2.26) 64 0.99 (0.70–1.65) 0.003 0.475 [0.281–0.744] 0.0026
fT3/rT3 ratio (5.7–42) 245 6.61 (4.70–9.84) 181 6.35 (4.70–9.72) 64 6.92 (4.73–10.38) 0.402 1.016 [0.964–1.063] 0.5039
Thyroglobulin (1.59–59.9 ng/mL) 245 15.2 (6.4–28.4) 181 16 (6.5–27.6) 64 13.3 (5.35–31.3) 0.565 0.995 [0.980–1.006] 0.5037
IL-6 (<3.4 pg/mL) 244 49.1 (21.3–93.2) 180 48.2 (19.8–84.2) 64 56.4 (32.7–124.2) 0.145 0.999 [0.998–1.000] 0.7624
D-dimer (<500 ng/mL) 241 785.4 (497–1628) 179 760.2 (488.5–1339) 64 1038 (536–3529) 0.025 1.000 [0.999–1.000] 0.0111
LDH (207–414 U/L) 234 743 (549–1013) 172 715.5 (548–973) 62 839 (559–1253) 0.011 1.001 [1.000–1.002] 0.0023
Albumin (3.5–5.5 g/dL) 245 3.3 (2.9–3.6) 181 3.3 (3–3.7) 64 3.3 (2.7–3.6) 0.020 0.387 [0.195–0.744] 0.0052
CRP (<5.0 mg/dL) 223 85.2 (37.6–151) 162 68.3 (34.7–139.1) 61 139.7 (45.7–178.5) 0.007 1.010 [1.005–1.016] 0.0004
ALT (8–42 U/L) 238 61.0 (39–101.3) 175 67.0 (42.0–105.0) 63 49.0 (32.0–94.0) 0.019 0.994 [0.987–1.000] 0.1204
AST (8–42 U/L) 238 54.0 (38.7–81.2) 175 54.0 (39.0–81.0) 63 52.0 (38.0–84.0) 0.839 0.997 [0.989–1.003] 0.4375
Creatinine (0.7–1.2 mg/dL) 237 1.1 (0.89–1.37) 177 1.1 (0.9–1.36) 60 1.09 (0.86–1.41) 0.834 1.025 [0.777–1.207] 0.7732
Neutrophil (1935–6700 ·10
3
cells/lL) 245 7371 (5221–9561) 181 6768 (5057–8977) 64 8740 (6399–11199) 0.0004 1.000 [1.000–1.000] 0.060
N/L ratio (1–3) 245 9.11 (6.04–14.5) 181 8.5 (5.28–13.7) 64 10.8 (8.23–17.6) 0.001 1.064 [1.018–1.114] 0.0059
Hemoglobin (13.5–18 g/dL) 245 13.4 (12.3–14.4) 181 13.5 (12.4–14.5) 66 13.1 (11.7–14.1) 0.077 0.799 [0.667–0.955] 0.0136
ALT, alanine transaminase; AST, aspartate transaminase; 95% CI, confidence interval; CRP, C-reactive protein; IL-6, interleukin 6; N/L ratio, neutrophil-lymphocyte ratio; OR, odds ratio.
1643
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Clinical outcome
Of the 245 enrolled patients, 41 patients died of COVID-19
complications about 13 days later. This is in contrast with the
group of survivors who were discharged about six days after
admission (Table 1). Based on these numbers, we asked how
well different clinical and biochemical parameters obtained
in the first 48 hours of admission predicted the clinical out-
come. The parameters included length-of-stay, ICU admission,
CT COVID score, use of vasoactive drugs, and unspecific
markers of inflammation (Tables 1 and 2). We used univar-
iate logistic regression analysis and found that among the 11
markers of inflammation, tissue damage, or blood count pa-
rameters, 8 were predictors of disease severity and prognosis
of mortality: IL-6, D-dimer, LDH, albumin, CRP, neutro-
phils, neutrophil-lymphocyte ratio, and hemoglobin ( p<0.05)
(Fig. 3). The Fisher’s exact test confirmed higher mortality
risk for all these same markers (Tables 2 and 3).
Next, we asked whether TH levels obtained on admission
could predict clinical outcomes and, if so, how well they
compared with the classical predictors assessed above. Using
the univariate logistic regression, serum levels of fT3, rT3 and
the product fT3 ·rT3 showed strong correlation with disease
severity and prognosis of mortality (Table 2). Unexpectedly,
the fT3/rT3 ratio did not yield statistically significant predictive
power (Table 2). Figure 4A shows TSH, fT4, fT3, rT3, and
fT3 ·rT3 results among survivor and non-survivor patients.
We also plotted an ROC curve, to calculate the mortality pre-
dictive power of each parameter. The top parameters based on
the area under the curve (AUC >0.65) were the product fT3 ·
rT3, followed by N/L ratio, CRP, neutrophil count, and serum
fT3 (Table 3 and Fig. 4B). Next, using the cutoff value for each
parameter we calculated the odds ratio (OR) of mortality using
the Fisher’s exact test. The parameters with top ORs included
the product fT3 ·rT3, followed by CRP, neutrophil count, se-
rum fT3 and N/L ratio (Table 3). Notably, some parameters
with a low ROC AUC exhibited a significant OR of mortality,
that is, serum rT3, IL-6, albumin, and D-dimer (Table 3).
We next used univariate and multivariate regression analy-
sis to calculate the mortality OR by using cutoff values ob-
tained from the ROC curve (Table 4). Whereas serum TSH,
fT4, and fT3/rT3 values did not yield a significant OR, we
observed that serum fT3, rT3, and fT3 ·rT3 yielded highly
significant ORs (Table 4). We noticed that the calculated
cutoff value for serum fT3—based on the ROC curve—was
2.6 pg/mL, which is within the normal reference range of the
method used. Thus, we recalculated the univariate regression
analysis by using 2.0 pg/mL (the lower limit of normal), and
we obtained an even higher OR for mortality. These analyses
were followed by a multivariate logistic regression analysis,
which corrects the OR based on eight co-variates (Table 4).
The resulting ORs were higher and followed the same pattern
observed for the univariate analysis.
Next, the mortality rates was bubble plotted considering the
rT3 and fT3 serum levels. It is notable that survival and shorter
length of stay segregated with normal serum T3 and rT3 levels,
whereas mortality and longer length of stay segregated with
high serum rT3 levels (Fig. 4C). A bar graph of the same data
also illustrates these points (Fig. 4D). In addition, Figure 4E–I
show differences in TSH, fT4, fT3, rT3, and fT3·rT3 values
among survivor and non-survivor patients.
Discussion
To our knowledge, this is the largest prospective study
of hospitalized patients with COVID-19 whose TH serum
levels were assessed, including serum TSH, fT4, fT3, rT3,
and Tg levels. An elevation in serum rT3 levels was the
most frequent alteration observed in these patients
(*63%),followedbyhighserumfT4(*21%) and low
serum TSH levels (*7.3%). Unexpectedly, NTIS were
only observed in *6.5% patients. No patients exhibited
clinical signs or symptoms of SAT, despite that 5.3% of
patients exhibited an elevation in serum Tg levels. Re-
markably, serum fT3, rT3 and the product fT3 ·rT3 ex-
hibited substantial predictive value for disease severity and
mortality, with the product fT3 ·rT3 performing slightly
better than classical parameters such as D-dimer, LDH,
albumin, CRP, ALT, neutrophil count, neutrophil/lym-
phocyte (N/L) ratio, and hemoglobin levels.
Only two studies (total of 482 patients) (10,32) prospec-
tively investigated the hypothesis that serum TH levels in
COVID-19 patients could serve as biomarkers of maladap-
tive response and unfavorable outcomes. In one study, a co-
hort of 367 Chinese mild-to-moderate COVID-19 patients
revealed that 16.9% of patients had abnormal thyroid func-
tion test. Serum rT3 was not evaluated, but serum fT3 was
obtained in 367 patients and NTIS was identified in 27 (7.4%)
patients, although 75.2% had mild disease (10). More recen-
tly, an Italian longitudinal prospective observation study of
severely ill COVID-19 patients found that 20 of 115 patients
(9%) had low serum fT3 levels (32). Notably, both studies
concluded that reduced fT3 serum levels are associated with
adverse outcomes, for example, inflammatory response, but
the impact of the studies was limited by the small sample size,
the lack of statistical power, the predominance of mild or
severe-illness, and the presence of confounders such as treat-
ment drugs (Table 5) (10,32).
Indeed, Chen et al. retrospectively observed that COVID-19
patients who died had lower serum fT3 levels on admission
(33). Guo et al. recently reported fT3 serum levels as a possible
prognostic marker of mortality with AUC =0.863 in 121 crit-
ically ill patients with COVID-19 (27). Another retrospective
study of 287 patients identified a 20.2% prevalence of TSH
below the reference range (<0.33 mU/L) and an inverse cor-
relation between TSH and IL-6 (r=-0.41; p<0.001). How-
ever, fT3 and fT4 levels were measured only in 73 patients
among the 287 included (34). Recently, in a retrospective
study, Lang et al. (35) evaluated 127 hospitalized patients and
low T3 levels (<3.1 pmol/L) in the univariate Cox regression
‰
FIG. 3. TH levels, biochemical and hemocromocytometric parameters in 245 critically and non-critically ill COVID-19
hospitalized patients during the first 48 hours of admission. Gray areas in plots represent normal reference ranges. Statistics
used: Mann–Whitney test. ALT, alanine transaminase; Anti-TPO, anti-thyroid peroxidase; AST, aspartate transaminase;
CRP, C-reactive protein; fT3 ·rT3, the product of fT3 and rT3; IL-6, interleukin 6; LDH, lactate dehydrogenase; N/L ratio,
neutrophil-lymphocyte ratio.
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1645
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analysis, showing a strong association with in-hospital mor-
tality (Hazard Ratio [HR] 14,607, 95% confidence interval [CI]
[3873–55,081], p<0.001).
NTIS is considered an adaptive response of the
hypothalamus-pituitary-thyroid axis to severe illness, includ-
ing in patients with COVID-19 (8,10,15,27,28,36). Previous
studies have demonstrated that blood levels of pro-
inflammatory and anti-inflammatory cytokines correlate with
disease’s severity and mortality (32). The release of high levels
of pro-inflammatory cytokines during the acute response of
critical illness could contribute to TH alterations, including the
reported drop in serum fT3 (15,25). In our study, the rapid
decline in the circulating fT3 serum levels (below the lower
limit of the reference range) was observed in only a small
percentage of patients, whereas an elevation in serum rT3
levels was frequent; it was the most common alteration in
serum TH levels among hospitalized COVID-19 patients.
We found that both, the combination of low fT3 and el-
evated rT3 serum levels, were robustly associated with in-
flammatory response, disease severity, and mortality.
Serum fT3 levels had good specificity reflecting low false-
positive rates, indicating that it might be of practical pre-
dictive value once it can be obtained up to two to three hours
after hospital entrance. Notwithstanding, the usefulness of
fT3 serum levels as a biomarker needs to be further explored
given that its alteration might be affected by the degree and
phase of inflammatory response, by reduced levels of TH
binding proteins and accelerated hormone clearance caused
on SARS-COV-2 infection (8,10,27,36,37).
Progressive defect in the T4 to T3 conversion and increment
in T4-binding globulin have been previously associated with
low levels of serum T3 at admission and disease severity re-
lated to human immunodeficiency virus infection. Indeed, rT3
decline was associated with in-hospital mortality (38,39). To
our knowledge, the prognostic value of rT3 serum levels in
COVID-19 patients has not been investigated in previous
studies. Although frequently elevated, patients who ultimately
did not survive presented with not as high serum rT3 levels
when compared with patients who survived. Consequently,
here we made the novel observation that the fT3 ·rT3 product
exhibited the highest prognostic value of all parameters ex-
amined, including inflammation biomarkers, with a sensitivity
of 80% and specificity of 57%. The mortality predictive values
for serum fT3, rT3, and the fT3 ·rT3 product exhibited strong
agreement among univariate, multivariate, and sensitivity an-
alyses (Chi-square, Fisher’s exact and Mann-Whitney test).
However, the predictive capacity of these variables was still
modest (area under the ROC curve between 0.6 and 0.7),
probably secondary to the homogeneity of the studied popu-
lation, mainly composed of moderate-to-severe COVID-19
cases referred to a specialized COVID-19 center.
The fact that TSH serum levels remained within normal
range in most patients suggests that thyroidal T4 and T3 pro-
duction might not have been greatly reduced. Whereas the
changes in TH serum levels have been interpreted as largely
adaptive, it is conceivable that in this situation they might play
an expanded role. For example, TH has multiple effects on
lung physiology, including alveolar type II cells function and
control of in vivo alveolar fluid clearance (AFC) (20,40). It has
been proposed that T3 directly instilled into lungs could raise
AFC, supporting oxygenation and dribbling the exigency for
expanded mechanical ventilation (20,21). Therefore, lower T3
availability in the acute respiratory distress syndrome context
could have a negative impact in the diaphragm muscle con-
traction physiology and impair ventilation (41).
Pos-mortem examination in ICU patients has found that se-
rum rT3 values correlate with reduced liver D1 and increased D3
activities (42). Notably, D3 is inducible by hypoxia-inducible
factor (HIF1a), but little is known about the role of HIF in
COVID-19 (43). Whereas the elevation in serum rT3 typically
noted in NTIS patients is generally interpreted as the result of
impaired D1-mediate clearance of rT3, D3 reactivation could be
playing a role as well. The worse outcomes observed in patients
with less robust elevation in rT3 levels are puzzling and could
indicate a failure of D3 reactivation and/or normal D1 activity.
The limitations of this study include, first, that the analysis was
limited to a hospitalized moderate-to-severe COVID-19 patients
and these results may not apply to individuals with COVID-19
who are not hospitalized. Second, it is unclear whether a decrease
in caloric intake, a weight loss, or a combination of these factors
are the cause of decreased fT3 levels in COVID-19 critically ill
patients.
Table 3. Variables Analyzed as Potential Biomarkers for Mortality:
Receiver Operating Characteristic Curve
Variable
ROC curve Risk factor cutoff characterization Fisher’s exact test
AUC [CI] Cutoff Sensitivity Specificity pOR [CI] p
TSH (lIU/mL) 0.50 [0.41–0.59] ‡1.91 0.51 0.53 0.98 1.20 [0.62–2.33] 0.61
fT4 (ng/dL) 0.51 [0.41–0.60] £1.27 0.46 0.56 0.95 1.11 [0.56–2.14] 0.86
fT3 (pg/mL) 0.66 [0.56–0.75] £2.6 0.46 0.80 0.0013 3.54 [1.69–7.24] 0.0006
rT3 (ng/mL) 0.64 [0.55–0.73] £0.38 0.71 0.64 0.0045 4.43 [2.18–9.05] <0.0001
fT3 ·rT3 0.69 [0.60–0. 78] £1.29 0.80 0.57 <0.0001 5.43 [2.41–11.6] <0.0001
fT3/rT3 ratio 0.54 [0.44–0.64] ‡7.52 0.53 0.62 0.51 1.95 [1.01–3.85] 0.056
IL-6 (pg/mL) 0.60 [0.51–0.70] ‡130 0.34 0.87 0.03 3.55 [1.70–7.44] 0.0019
D-dimer (ng/mL) 0.59 [0.49–0.70] ‡1230 0.52 0.70 0.057 2.59 [1.30–5.26] 0.0095
CRP (mg/dL) 0.67 [0.58–0.77] ‡120 0.70 0.65 0.0004 4.41 [2.13–9.15] <0.0001
LDH (U/L) 0.63 [0.53–0.74] ‡714 0.74 0.48 0.006 2.69 [1.26–5.57] 0.0128
Albumin (g/dL) 0.62 [0.52–0.72] £2.85 0.42 0.83 0.0147 3.77 [1.89–7.87] 0.0006
Neutrophil ( ·10
3
cells/lL) 0.67 [0.58–0.76] ‡8.185 0.68 0.65 0.0003 4.03 [2.02–7.95] <0.0001
N/L ratio 0.68 [0.59–0.77] ‡10.5 0.63 0.63 0.0002 2.98 [1.53–5.93] 0.002
AUC, area under the curve; LDH, lactate dehydrogenase; ROC, receiver operating characteristic.
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FIG. 4. TH levels of 245 COVID-19 hospitalized patients collected during the first 48 hours of admission. (A)
Heatmap showing serum levels (TSH, fT4, fT3, and rT3) classification below, within, and above normal range in
patients with COVID-19 (survivors vs. non-survivors). And a heatmap showing the presence or absence of parameter
below cutoff (fT3 £2.6pg/ml, rT3 £0.38ng/ml, fT3 ·rT3 £1.29) in patients with COVID-19 (survivors vs. non-survivors).
Each row indicates a single parameter and each column indicates a patient. (B) Mortality risk ROC curve and AUC score
with parameters of fT3, rT3, and fT3 ·rT3. (C) Bubble plot displaying the rT3 level against the fT3 level in patients with
COVID-19 (survivors vs. non-survivors). The normal reference range is illustrated. (D) Bar chart depicting sample number
with (+) and without (-) the parameter below the cutoff (fT3 £2.6pg/ml, rT3 £0.38ng/ml) in patients with COVID-19
(survivors vs. non-survivors) and highlighting the proportion of non-survivor. (E–I) Bar chart showing TH levels (TSHlUl/
mL, fT4ng/dL, fT3pg/mL, rT3ng/ml, fT3 ·rT3) of COVID-19 patients (survivor vs. non-survivor) and the p-value. The
columns represent the parameter median, the gray areas represent the normal reference ranges, the bubbles represent the
samples. Statistics used: Mann-Whitney test and ROC curve. AUC, area under the curve; fT3, free tri-iodothyronine; fT4,
free tetraiodothyronine; ROC, receiver operating characteristic; rT3, reverse tri-iodothyronine; TH, thyroid hormone.
Table 4. Univariate and Multivariable Regression Analyses Between Thyroid Function and Variables
Variable
Univariate logistic regression mortality Multiunivariate logistic regression mortality
a
OR [CI] pOR [CI] p
TSH ‡1.91 lIU/mL 1.20 [0.61–2.37] 0.58 1.32 [0.60–2.90] 0.47
fT4 £1.27 ng/dL 1.11 [0.56–2.18] 0.74 1.04 [0.46–2.35] 0.90
fT3 £2.6 pg/mL 3.54 [1.74–7.18] 0.0004 3.48 [1.51–8.12] 0.0033
rT3 £0.38 ng/mL 4.43 [2.17–9.51] <0.0001 5.94 [2.52–15.3] <0.0001
fT3 ·rT3 £1.29 5.43 [2.50–13.18] <0.0001 8.08 [3.14–24.2] <0.0001
fT3/rT3 ‡7.52 ratio 1.95 [0.99–3.86] 0.052 1.92 [0.88–4.26] 0.10
NTIS (fT3 <2.0 pg/mL) 4.46 [1.5–12.79] 0.005 7.05 [1.78–28.3] 0.005
a
Adjusted for age, neutrophil ( ·10
3
cells/lL), N/L ratio, albumin, high-sensitivity CRP, LDH, D-dimer and IL-6.
1647
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In summary, this prospective study reports data on the
largest number of hospitalized moderate-to-severe COVID-
19 patients and correlates serum TH levels with illness se-
verity, mortality, and other biomarkers to critical illness. The
data revealed the importance of early assessment of thyroid
function in hospitalized patients with COVID-19, given the
good prognostic value of serum fT3, rT3, and fT3 ·rT3 prod-
uct. Further studies are necessary to confirm these observations.
Author Disclosure Statement
A.C.B. is a consultant for Synthonics, BLA technology,
and Allergan. The other authors declare no conflicts of interest.
Funding Information
No funding was received.
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(no. of
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Mild (75.2%)
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Severe (3.8%)
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[(0.5%)
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[(1.4%)
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[(0.5%)
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performed
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[(0.0%)
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Cutoff levels were
determined
Y, reduced serum levels; [, elevated serum levels.
a
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b
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Address correspondence to:
Helton Estrela Ramos, MD, PhD
Bioregulation Department
Health and Science Institute
Federal University of Bahia
Avenida Reitor Miguel Calmon,
S/N. Vale do Canela, Room 325
Salvador 40110-102
Brazil
E-mail: ramoshelton@gmail.com
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