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RESEARCH ARTICLE
Predictors of intensive care unit admission in
adult cancer patients presenting to the
emergency department with COVID-19
infection: A retrospective study
Tharwat El ZahranID
1
, Nour Kalot
2
, Rola Cheaito
2
, Malak Khalifeh
1
, Natalie Estelly
3
,
Imad El MajzoubID
4
*
1Department of Emergency Medicine, American University of Beirut Medical Center, Beirut, Lebanon,
2Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon, 3Faculty
of Medicine, American University of Beirut, Beirut, Lebanon, 4Sheikh Shakhbout Medical City, Abu Dhabi,
United Arab Emirates
*imajzoub@ssmc.ae
Abstract
Background
Adult cancer patients with COVID-19 were shown to be at higher risk of Intensive Care Unit
(ICU) admission. Previously published prediction models showed controversy and enforced
the importance of heterogeneity among different populations studied. Therefore, this study
aimed to identify predictors of ICU admission (demographic, clinical, and COVID-19 tar-
geted medications) in cancer patients with active COVID-19 infection presenting to the
Emergency Department (ED).
Methods
This is a retrospective cohort study. It was conducted on adult cancer patients older than 18
years who presented to the American University of Beirut Medical Center ED from February
21, 2020, till February 21, 2021, and were found to have COVID-19 infection. Relevant data
were extracted from electronic medical records. The association between different variables
and ICU admission was tested. Logistic regression was done to adjust for confounding vari-
ables. A p-value less than 0.05 was considered significant.
Results
Eighty-nine distinct patients were included. About 37% were admitted to the ICU (n = 33).
Higher ICU admission was seen in patients who had received chemotherapy within one
month, had a respiratory rate at triage above 22 breaths per minute, oxygen saturation less
than 95%, and a higher c-reactive protein upon presentation to the ED. After adjusting for
confounding variables, only recent chemotherapy and higher respiratory rate at triage were
significantly associated with ICU admission.
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OPEN ACCESS
Citation: El Zahran T, Kalot N, Cheaito R, Khalifeh
M, Estelly N, El Majzoub I (2023) Predictors of
intensive care unit admission in adult cancer
patients presenting to the emergency department
with COVID-19 infection: A retrospective study.
PLoS ONE 18(8): e0287649. https://doi.org/
10.1371/journal.pone.0287649
Editor: Robert Jeenchen Chen, Stanford University
School of Medicine, UNITED STATES
Received: March 8, 2023
Accepted: June 12, 2023
Published: August 29, 2023
Copyright: ©2023 El Zahran et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: The author(s) received no specific
funding for this work.
Competing interests: The authors have declared
that no competing interests exist.
Conclusion
Physicians need to be vigilant when taking care of COVID-19 infected cancer patients.
Patients who are tachypneic at presentation and those who have had chemotherapy within
one month are at high risk for ICU admission.
Background
One of the most vulnerable groups of patients to critical illness from respiratory viral infec-
tions are cancer patients [1]. It is postulated that patients with cancer who are infected with the
SARS-CoV-2 Coronavirus may have worse outcomes than others [2]. Published work reported
higher morbidity and mortality rates from COVID-19 among cancer patients compared to
their cancer-free counterparts [2–6].
Admission to the Intensive Care Units (ICU) plays a significant role in the management of
COVID-19 patients, with some reports showing a reduced mortality rate among those admit-
ted to critical care units [7–9]. As a result, several studies developed prediction models and
risk scores for ICU admission in COVID-19. Nevertheless, these studies have shown various
results that were sometimes controversial in terms of the effect of the type of cancer and its
therapies on the prognosis of infected patients [10]. This controversy might be due to a com-
posite of causes, including methodological differences, regional care differences, SARS-CoV-2
variants, heterogeneity of the evaluated population, as well as the large heterogeneity embed-
ded within the cancer and COVID-19 diseases [10].
During the COVID-19 pandemic, emergency departments (EDs) have been on the fron-
tlines, playing an essential role in detecting infected patients, providing urgent medical care
[11], and deciding on the proper disposition of patients. These departments have been chal-
lenged and overwhelmed by the increasing number of COVID-19 cases worldwide. Conse-
quently, it has been of utmost importance in ED settings to be able to predict which cancer
patients with COVID-19 are at risk of deteriorating and having worse outcomes. The knowl-
edge of these predictors can be used to assure a proper and timely risk stratification, adjust
management accordingly, avoid ICU admission delay [12], and prioritize the admission of
high-risk patients.
To date, no studies have been conducted in Lebanon to determine the predictors of ICU
admission in cancer patient population with COVID-19 in Lebanon. The objective of the pres-
ent study is to identify predictors of ICU admission (e.g., demographic, clinical, and COVID-
19 targeted medications) in cancer patients with active COVID-19 infection presenting to the
ED. This will contribute to risk stratification of this population, optimize the medical manage-
ment, and potentially help in developing a predictive tool to identify COVID19-positive cancer
patients who are at a higher risk of complications leading to mortality.
Methodology
Study design and setting
This is a retrospective cohort study conducted at the American University of Beirut Medical
Center (AUBMC), a tertiary care academic hospital in Lebanon. The study enrolled all cancer
patients who presented from February 21, 2020, till February 21, 2021, to the ED of AUBMC
and were diagnosed with COVID-19 infection. The ED is run as a closed unit by onsite cover-
age of emergency medicine specialists 24 hours a day, seven days a week. The study was
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approved by the Institutional Review Board (IRB) at AUBMC under the protocol number
(BIO-2021-0015). Informed consent was waived given the retrospective nature of the study. In
order to protect patients’ information and confidentiality, subjects’ names were not collected.
Each patient was anonymously assigned a study ID in the data collection sheet. The patient’s
study ID were kept on a separate log sheet and were only accessible by the primary investigator
and the research coordinator.
Study population
Patients included were adult (>18 years old) cancer patients who presented to the ED of
AUBMC from February 21, 2020, till February 21, 2021, and were positive for COVID-19
infection. We defined COVID-19 infection as a positive result of the SARS-COV-2 nucleic
acid RT-PCR test using the nasal swab samples.
Patients not fitting any of the above criteria, as well as those who presented dead on arrival
to the ED, were excluded.
Data collection and sampling
Eligible patients were identified through the electronic health system (Epic Systems, Verona,
WI, USA). Following an IRB-approved unified data collection manual adjusted after a pilot
data collection, the two team members who retrieved the data used the same nomenclature,
definitions, and workflow. Study data were collected and managed using REDCap (Research
Electronic Data Capture) a secure web-based application designed to support data capture for
research studies that is Health Insurance Portability and Accountability Act compliant [13,14]
A quality control was reviewed by one team member down the line.
The data collection form was divided into multiple sections (S1 Dataset). The first section
encompassed the demographic and medical history (smoking status, medication, and comor-
bidities) of the patients. It also included a subsection about the cancer history of the patient
(type of cancer, its spread, and treatment modalities, including chemotherapy and immuno-
therapy). The second section was about the details of the ED visit where the patient was con-
firmed to be COVID-19 infected. In addition, we collected information about vital signs,
treatment given in the ED, and ED disposition. Finally, the third section was about the
patients’ hospital stay, which included all complications (sepsis, acute kidney injury (AKI), car-
diac and respiratory complications (e.g., acute respiratory distress syndrome, ARDS and pul-
monary embolism, PE)) along with the procedures done (central line or chest tube insertion,
dialysis, tracheostomy) and hospital discharge date, and disposition.
Statistical analysis
Statistical analysis was performed using SPSS version 25.0 (Armonk, NY: IBM Corp). Categor-
ical variables were described using frequencies and percentages. Continuous variables were
reported using means, and standard deviations.
The dependent variable was ICU admission versus no ICU admission. The association
between different variables and ICU admission was tested using Pearson’s Chi-square or Fish-
er’s exact test, Student’s t-test and Mann Whitney U where appropriate.
Later, logistic regression was done to adjust for confounding variables and identify factors
that were associated with ICU admissions in these patients. We included variables with p-
value less than 0.2. Variable(s) entered in step 1: Vasopressors, Remdesivir, Tocilizumab, Ste-
roid, Antibiotics, Anticoagulant, CRP, RR at triage (reference 22), O2 at triage
(reference 95 mmHg), Chemotherapywithin1monthofpresentation. A p-value less than 0.05
was considered significant.
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Results
1. Demographics and clinical characteristics of COVID-19 cancer patients
A total of 89 cancer COVID-19 infected patients were included in the study. Their average age
was 66 years (±13.6). The majority were males (64%) and with solid cancer (74.2%). About
half of them were smokers (52.8%) and underwent chemotherapy within 1 month of presenta-
tion (52.8%). Only 6 patients did bone marrow transplants (BMT) within 1 year of presenta-
tion. Hypertension was the main comorbidity among patients (39.3%), followed by
cardiovascular diseases (25.8%), dyslipidemia (23.6%), and diabetes mellitus (14.6%). Only 4
of the patients were on baseline steroids before the ED visit. More than a third of the patients
in our sample were admitted to the ICU (n = 33). Their mean age was 67 years (±11.2) and
were mainly males (69.7%). (Table 1)
Most of the patients had tachycardia (n = 79, 89.8%) and 40.4% had low oxygen saturation
at triage inferior to 95mmHg (n = 36, 40.4%). (Table 2)
Patients with liquid or solid tumors were homogenous in terms of age, smoking status, and
presence of comorbidities. However, patients with liquid tumors were mainly males (95.7%,
p<0.001) and had more moderate to severe kidney diseases (34.8%, p = 0.021).
2. Treatments and health-related complications of COVID-19 cancer patients
In the ED, patients were treated mainly with steroids (56.2%), antibiotics (48.3%), and antico-
agulants (47.2%). They were also treated with Remdesivir (19.1%), Ivermectin (14.6%),
Table 1. Association of baseline characteristics of oncology COVID-19 patients with ICU admission.
Characteristics Total N = 89 No ICU n = 56 (63%) ICU n = 33 (37%) p-value OR 95% CI
Age (years) 66.3 (13.6) 65.9 (14.8) 67 (11.2) 0.711
Sex Female 32 (36%) 22 (39.3%) 10 (30.3%) 0.394 Ref
Male 57 (64%) 34 (60.7%) 23 (69.7%) 1.488 0.596–3.719
History of smoking 47 (52.8%) 28 (50%) 19 (57.6%) 0.489 1.357 0.571–3.228
Type of Cancer Liquid 23 (26.7%) 14 (25.5%) 9 (29%) 0.801 Ref
Solid 63 (73.3%) 41 (74.5%) 22 (71%) 0.835 0.312–2.234
Metastatic tumor 34 (52.3%) 20 (47.6%) 14 (60.9%) 0.306 1.711 0.609–4.809
Bone Marrow Transplant within 1 year 6 (6.8%) 3 (5.4%) 3 (9.4%) 0.664 1.828 0.346–9.642
Chemotherapy within 1 month 47 (52.8%) 26 (46.4%) 21 (63.6%) 0.116 2.019 0.835–4.88
Immunotherapy 19 (21.3%) 12 (21.4%) 7 (21.2%) 0.981 0.987 0.345–2.823
Comorbidities Cardiovascular Diseases 23 (25.8%) 17 (30.4%) 6 (18.2%) 0.205 0.51 0.178–1.46
Diabetes Mellitus 13 (14.6%) 6 (10.7%) 7 (21.2%) 0.219 2.244 0.683–7.367
Hypertension 35 (39.3%) 22 (39.3%) 13 (39.4%) 0.992 1.005 0.416–2.423
Dyslipidemia 21 (23.6%) 14 (25%) 7 (21.2%) 0.684 0.808 0.288–2.264
Cerebrovascular accident/TIA 2 (2.2%) 1 (1.8%) 1 (3%) 1 1.719 0.104–28.43
Chronic Obstructive Pulmonary Disease 8 (9%) 7 (12.5%) 1 (3%) 0.249 0.219 0.026–1.863
Chronic Kidney Disease 16 (18%) 10 (17.9%) 6 (18.2%) 0.969 1.022 0.334–3.127
Hemiplegia 1 (1.1%) 1 (1.8%) 0 (0%) 1
Peptic ulcer disease 2 (2.2%) 1 (1.8%) 1 (3%) 1 1.719 0.104–28.43
Liver Disease 3 (3.4%) 1 (1.8%) 2 (6.1%) 0.552 3.548 0.309–40.73
Other*58 (65.2%) 40 (71.4%) 18 (54.5%) 0.106 0.48 0.196–1.178
Data are presented as numbers with percentages.
The P-value for the difference between two adjacent columns is calculated by chi-square or Fisher’s exact test where appropriate.
Abbreviations: OR: odds ratio, 95%CI: 95% Confidence Interval, Ref = Reference, ICU = intensive care unit, ED = emergency department
*Other comorbidities are thyroid disease, psychiatric disorders, and rheumatologic diseases.
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Tocilizumab (9%), or convalescent plasma (6.7%). Only 7.9% of patients were treated with
vasopressors (n = 7). (Table 2)
During their hospital stay, patients faced complications whom 33.7% developed respiratory
complications, including ARDS, pneumothorax, or respiratory failure, while 15.7% had septic
shock, and 7.9% developed cardiovascular complications. Only 9% of patients required dialysis
(n = 8). About 28.1% required endotracheal intubation either in the ED or during their hospi-
tal stay (n = 25). The average length of hospital stay was 30.7 days.
2.1 Characteristics of patients who required intubation in the ED. Eleven patients were
intubated in the ED (12.4%). There was no significant difference in gender, age, smoking sta-
tus, and presence of comorbidities between patients who were endotracheal intubated in the
ED and those who were not. The average age of intubated patients was 66.7 years (±10.2) and
were mainly males (81.8%).
For vital signs, patients who were intubated in the ED more frequently had an oxygen
saturation <95%, tachypnea with a RR >22 breaths/minute (72.7% vs. 8%, p <.001), or
tachycardia (Heart Rate>100 beats/minute) (81.8% vs. 43.6%, p = 0.018).
Patients who were intubated were more on Ivermectin (36.4% vs. 11.5%, p = 0.051), vaso-
pressors (54.5% vs. 1.3%, p<0.001), or anticoagulants (81.8% vs. 42.3%, p = 0.014). Intubated
patients were less on antibiotics (9.1% vs. 53.8%, p = 0.005). The c-reactive protein (CRP) level
was significantly higher in intubated patients (187.5 ±93.3 vs. 85.5±74.6, p<0.001).
Table 2. Association of vital signs and ED treatment of COVID-19 oncology patients with ICU admission.
Total n = 89 No ICU n = 56 (63%) ICU n = 33 (37%) p value OR 95%CI
ED treatment
Mechanical Ventilation in ED 11 (12.4%) 0 11 (33.3%) <.001
Vasopressors 7 (7.9%) 1 (1.8%) 6 (18.2%) 0.01 12.222 1.4–106.674
Steroids 50 (56.2%) 26 (46.4%) 24 (72.7%) 0.016 3.077 1.215–7.789
Antibiotics 43 (48.3%) 31 (55.4%) 12 (36.4%) 0.083 0.461 0.19–1.115
Anticoagulants 42 (47.2%) 22 (39.3%) 20 (60.6%) 0.052 2.378 0.986–5.735
Plasma 6 (6.7%) 4 (7.1%) 2 (6.1%) 1 0.839 0.145–4.849
Remdesivir 17 (19.1%) 13 (2 3.2%) 4 (12.1%) 0.198 0.456 0.135–1.539
Ivermectin 13 (14.6%) 7 (12.5%) 6 (18.2%) 0.54 1.556 0.475–5.099
Tocilizumab 8 (9%) 2 (3.6%) 6 (18.2%) 0.048 6 1.134–31.735
Baricitinib 3 (3.4%) 1 (1.8%) 2 (6.1%) 0.552 3.548 0.309–40.73
Vital Signs
Heart rate at triage <= 100 46 (51.7%) 32 (57.1%) 14(42.4%) 0.180 Ref
>100 43(48.3%) 24(42.9%) 19(57.6%) 1.180 0.758–4.319
Systolic blood pressure at triage <= 100 9 (10.2%) 7 (12.5%) 2 (6.3%) 0.478 Ref
>100 79 (89.8%) 49 (87.5%) 30 (93.8%) 2.143 0.417–11.001
Respiratory rate at triage <= 22 72 (83.7%) 53 (94.6%) 19 (63.3%) 0.001 0.098 0.025–0.389
>22 14 (16.3%) 3 (5.4%) 11 (36.7%) Ref
Temperature (˚C) at triage <37.5 50 (57.5%) 30 (53.6%) 20 (64.5%) 0.323 Ref
>= 37.5 37 (42.5%) 26 (46.4%) 11 (35.5%) 0.635 0.257–1.567
Oxygen Saturation level (mmHg) SpO2 <95 36 (40.4%) 16 (28.6%) 20 (60.6%) 0.003 3.846 1.552–9.523
SpO2 >= 95 53 (59.6%) 40 (71.4%) 13 (39.4%) Ref 0.105–0.644
Data are presented as numbers with percentages.
The p-value for the difference between two adjacent columns is calculated by chi-square or Fisher’s exact test where appropriate.
Abbreviations: OR: odds ratio, 95%CI: 95% Confidence Interval, Ref = Reference, SpO2 = Oxygen saturation, ICU = intensive care unit, ED = emergency department
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2.2 Characteristics of patients who had respiratory complications. About 30 patients
developed respiratory complications (33.7%), including pneumothorax, acute respiratory dis-
tress syndrome, and respiratory failure. However, the presence of respiratory complications
was not significantly impacted by gender, age, smoking status, or presence of comorbidities.
For vital signs, patients with respiratory complications had significantly lower oxygen satu-
ration level at triage less than 95 mmHg (56.7% vs. 32.2%, p = 0.026) or tachypnea RR superior
to 22 (35.7% vs. 6.9%, p = 0.001).
Patients with respiratory complications were using significantly more Tocilizumab (20% vs.
3.4%, p = .016), steroids (76.7% vs. 45.8%, p = 0.005) or anticoagulants (66.7% vs. 37.3%,
p = 0.009). They had significantly elevated CRP level (132.8 vs. 82.6 p = 0.011). They were also
more admitted to the ICU (75.8% vs. 13.6%, p<0.001), with a higher mortality (23.3% vs.
1.7%, p = 0.002).
3. Predictors of ICU admission in COVID-19 cancer patients
None of the baseline characteristics, including gender, age, smoking status, and presence of
comorbidities significantly associated with ICU admission (p >0.05). (Table 1)
Patients in ICU were significantly using more vasopressors (18.2% vs. 1.8%, p = 0.01) and
were more mechanically ventilated in the ED (p<0.001) than patients who were not admitted
to the ICU. They were also significantly 6 times more on Tocilizumab (18.2% vs. 12.5%,
p = 0.048) and 3 times more on steroids (72.7% vs. 46.4%, p = 0.016). (Table 2)
For vital signs, low oxygen saturation level at triage <95 mmHg (60.6% vs. 28.6%, p = .003)
and elevated respiratory rate (>22 breaths/min) (36.7% vs. 5.4%, p = 0.001) were significantly
associated with ICU admission. However, there was no significant difference in systolic blood
pressure and temperature of patients who were admitted to the ICU compared to patients who
were not admitted to the ICU (p >0.05). (Table 2)
The CRP level upon ED presentation was significantly higher in patients admitted to ICU
than in patients who did not require an ICU admission (140.8 ±98.2 vs. 76.1 ±65.9, p = 0.003).
(Table 3)
Additionally, patients admitted to ICU significantly develop more respiratory complica-
tions (75.8% vs. 8.9%, p <0.001), AKI (42.4% vs. 7.1%, p<0.001), PE (p = 0.048), septic shock
(p<0.001). They were significantly more on dialysis (21.2% vs. 1.8%, p = 0.004) and more died
(p<0.001).
Table 3. Association of ED laboratory data of COVID-19 oncology with ICU admission.
Laboratory Data Total N = 89 No ICU n = 56 (63%) ICU n = 33 (37%) p-value
White blood cells. count 8735.830 (11719.0215) 7548.5 (7071.2) 10714.7 (16808.96) 0.31
Absolute Neutrophil Count 5720.476 (4285.4441) 5558.5 (4160.7) 5997.4 (4547.26) 0.653
Hemoglobin 11 (1.9456) 11.1 (1.9) 10.8 (2.1) 0.393
Platelets 184323.864 (92905.1327) 178514.55 (86596.1) 194006.1 (103234.996) 0.452
Lactate Dehydrogenase 568.77 (560.581) 658.8 (738.7) 465.3 (204.2) 0.239
Lactic acid Venous 1.9024 (1.39752) 1.8 (1.7) 2.1 (0.82) 0.445
C-Reactive Protein 99.5 (84.5) 76.1 (65.9) 140.8 (98.2) 0.003
d-dimer 1379.9 (3418.1) 944 (1061.9) 2142.7 (5482.1) 0.3
Procalcitonin 1 (2.9) 0.8 (3.5) 1.2 (1.8) 0.552
Troponin T 0 (0.1) 0 (0.1) 0 (0) 0.539
Data are presented as mean with standard deviation.
The p-value for the difference between two adjacent columns is calculated by the T-test.
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3.1 Predictors Of ICU admission in COVID-19 cancer patients using logistic regression
(Table 4). After adjusting for confounding variables using logistic regression, Remdesivir
(aOR = 0.05, 95%, CI = 0.005–0.463) and antibiotics (aOR = 0.15, 95%, CI = 0.031–0.73) were
found to reduce the risk of ICU admission. RR >22 in triage was significantly associated with
ICU admission (aOR = 17.431, 95%CI = 2.4–125.1). Patients admitted to ICU were more on
steroids (aOR = 13.4, 95%CI = 2.3–78.2) and more on Tocilizumab (aOR = 18.5, 95%CI = 1.9–
179.6). They had also significantly received more chemotherapy within 1 month of presenta-
tion (aOR = 5.5, 95%CI = 1.2–25.8). (Table 3)
Discussion
The present study aims to detect the predictors of ICU admission for adult COVID-19 patients
with cancer who present to the ED. ICU admission risk for cancer patients who presented to
the ED with COVID-19 infection was significantly associated with chemotherapy within one
month, a respiratory rate at triage above 22 breaths per minute, oxygen saturation less than
95%, and a higher CRP. Out of these, after multivariate analysis, only high respiratory rate and
recent chemotherapy were top predictors of ICU admission. Of note, ICU admission risk in
ED for cancer patients infected with COVID-19 was not significantly associated with the
included sample’s demographic variables.
Our study focuses on cancer outpatients who present to the ED for COVID-19 infection,
aiming to aid the ED staff in establishing a better specific assessment and management of
patients. Furthermore, this is the first study done in Lebanon to evaluate the morbidity of
COVID-19 in cancer patients.
Studies, including ours, which evaluated the role of recent chemotherapy on COVID-19
outcomes, have shown controversial results. Zhang et al. showed that rates of severe respira-
tory COVID-19 were associated with recent chemotherapy [15]. On the contrary, Jee et al.
found that cytotoxic chemotherapy administered between 90 and 14 days before testing posi-
tive for COVID-19 has no increased rate for ICU admission [16], which is consistent with pre-
vious data. Such controversy in results may be explained by the high heterogeneity of
chemotherapy drugs that differ in their mechanisms. Interestingly, some agents were found to
have anti-cytokine storm effects, which have shown promise in patients with COVID-19 (e.g.,
the Janus kinase (JAK) inhibitors and Bruton’s tyrosine kinase (BTK) inhibitors) [17,18].
These antineoplastic drugs revealed the ability to prevent the cytokine storm generation thus
suppressing the immune system response along with multiple organ failure [19]. Noteworthy,
none of our patients were receiving these drugs. Another explanation for the contradictory
Table 4. Logistic regression: Factors associated with mortality in COVID-19 ICU patients.
p-value aOR 95% C.I.
Remdesivir 0.008 0.05 0.005 0.463
Tocilizumab 0.012 18.481 1.902 179.595
Steroids 0.004 13.399 2.297 78.159
Antibiotics 0.019 0.15 0.031 0.73
RR at triage 0.004 17.431 2.429 125.111
Chemotherapy within 1 month of presentation 0.029 5.545 1.193 25.78
Variable(s) entered in step 1: Vasopressors, Remdesivir, Tocilizumab, Steroid, Antibiotics, Anticoagulant, CRP, RR at triage (reference 22), O2 at triage
(reference 95 mmHg), Chemotherapywithin1monthofpresentation.
Omnibus <.001, R2 = .577, Hosmer = 0.918
95%C.I.: 95% Confidence Interval, aOR: adjusted Odds Ratio
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results regarding chemotherapy could be due to different study models that have not
accounted for factors that may affect the results [16].
Patients presenting to the ED with a respiratory rate exceeding 22 breaths per minute
(tachypnea) was a top predictor for ICU admission. Respiratory rate changes are an important
marker often preceding major complications, including respiratory depression, and failure
[20]. Since COVID-19 has the potential to affect the respiratory system [21], changes in resting
respiratory rate might occur in the early stages of infection [22]. High respiratory rates dis-
played the ability to predict most in-hospital cardiac arrests as well as admission to the ICU
[23]. When compared to heart rate, respiratory rate is found to be a better indicator of the
patient’s stability [24]. Furthermore, Subbe et. al showed that respiratory rate is superior not
only to pulse rate but also to both blood pressure in detecting high-risk patient groups [25].
In addition, vital signs are essential to monitor the patient overall status. Oxygen saturation,
compared to the invasive arterial blood-gas measurement, serves as a more accessible indicator
of the oxygenation for triage purposes [26]. The univariate analysis of this study showed that
an oxygen saturation less than 95% at presentation to ED was significantly associated with
ICU admission. Akhavan et al. found that lower ambulatory oxygen saturation was strongly
correlated with requiring high oxygen supplementation and mechanical ventilation among
admitted ED COVID-19 patients [27]. Severe respiratory failure and death associated with
coronavirus infection may be the result of damaged alveoli and edema formation, which hinders
the lung’s ability to oxygenate the blood, as reflected in reduced oxygen saturation [28,29].
The CRP level was significantly higher in COVID-19 cancer patients admitted to ICU
which is consistent with Wang et al. findings. Higher CRP levels were associated with aggra-
vated COVID-19 cases, and these levels occurred before disease progression [30]. C-reactive
protein is a well-known marker of systemic inflammation and severe infection [31]. In
COVID-19 infection, CRP was established as an independent outcome predictor as well as an
independent discriminator of the severity of the disease [32–35]. High levels of CRP were con-
sidered the most important predictor of COVID-19 severity in cancer patients [36]. Of note,
especially when looking at the multivariate analysis of our study, high CRP does commonly
occur in cancer patients, which implies that it might be questionable whether or not it should
be considered to be an independent prognostic factor in cancer COVID-19 patients [37].
As in other studies, we found that Remdesivir displayed potential benefits in terms of
reducing the risk of ICU admission. When prescribed alone to cancer patients with COVID-
19, this drug was associated with a reduced 30-day all-cause mortality (aOR, 0.41; 95% CI:
0.17–0.99) [38]. This nucleotide analog ribonucleic acid (RNA) polymerase inhibitor has
shown promising results. In a cohort of severe COVID-19 patients, clinical improvement was
observed in 68% of 53 patients [39]. In a double-blind, randomized, placebo-controlled trial in
hospitalized adults with COVID-19, intravenous Remdesivir was shown to significantly speed
the time to improvement versus placebo (p <0.001) [40]. Moreover, Remdesivir usage in
treating outpatients with mild to moderate COVID-19 was approved by the US Food and
Drug Administration which also supports its efficacy [41].
While the literature suggests that early antibiotic administration in COVID-19 cases has no
impact on mortality rates [42] and can increase the risk of adverse outcomes [43], we found
that it is significantly associated with a lower risk of ICU admission of infected cancer patients.
Large multi-centric studies are urgently required to better assess this association [44].
Large multi-centered studies are also needed to investigate the impact of other treatments,
including Tocilizumab and steroids on the morbidity and mortality of cancer patients with
COVID-19. While limited evidence is available on treatment with Tocilizumab for COVID-19
[45], data on steroids’ impact is conflicting [38,46]. In our study population, these drugs were
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Predictors of ICU admission in adult covid cancer patients
PLOS ONE | https://doi.org/10.1371/journal.pone.0287649 August 29, 2023 8 / 12
given by ED physicians to patients who were considered to have a more severe status. This
may account for treatment options being associated with increased ICU admission.
Limitations
The present study had several limitations. First, the included sample size was small, and the
study was retrospectively done in a single tertiary care center. However, AUBMC has the larg-
est cancer center in Lebanon for cancer patients and treats patients from all over the Middle
East and North Africa (MENA) region. Another limitation is the evolving nature of the
COVID-19 virus and its variants and the discovery of new effective treatment methods along
with vaccination that would affect our observations.
Conclusion
In conclusion, we found that patients who have received chemotherapy within one month of
the infection or whose RR at triage exceeds 22 breaths per minute are significantly at greater
risk of requiring ICU admission. Higher CRP level, requiring increased use of steroids and
Tocilizumab were associated with aggravated COVID-19 cases. Remdesivir displayed potential
benefits in terms of reducing the risk of ICU admission. Finally, early antibiotic administration
was significantly associated with a lower risk of ICU admission of infected cancer patients. ED
physicians should be vigilant when treating cancer patients with COVID-19 and look for pre-
dictors of worsening and start prompt therapy early on.
Supporting information
S1 Checklist. STROBE-checklist cancer icu study.
(DOC)
S1 Dataset. Covid oncology master dataset.
(XLSX)
Author Contributions
Conceptualization: Tharwat El Zahran, Nour Kalot, Rola Cheaito, Imad El Majzoub.
Data curation: Nour Kalot, Rola Cheaito, Natalie Estelly.
Formal analysis: Tharwat El Zahran, Nour Kalot, Malak Khalifeh, Imad El Majzoub.
Funding acquisition: Imad El Majzoub.
Investigation: Rola Cheaito, Imad El Majzoub.
Methodology: Tharwat El Zahran, Rola Cheaito, Imad El Majzoub.
Project administration: Tharwat El Zahran, Imad El Majzoub.
Resources: Imad El Majzoub.
Software: Tharwat El Zahran.
Supervision: Tharwat El Zahran, Rola Cheaito, Imad El Majzoub.
Validation: Tharwat El Zahran, Imad El Majzoub.
Visualization: Tharwat El Zahran, Imad El Majzoub.
Writing – original draft: Tharwat El Zahran, Nour Kalot, Malak Khalifeh, Natalie Estelly.
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Predictors of ICU admission in adult covid cancer patients
PLOS ONE | https://doi.org/10.1371/journal.pone.0287649 August 29, 2023 9 / 12
Writing – review & editing: Tharwat El Zahran, Imad El Majzoub.
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