Could we predict the prognosis of the COVID‐19 disease?

Abstract

Objectives
Coronavirus 2019 disease (COVID‐19) lead to one of the pandemics of the last century. We aimed to predict poor prognosis among severe patients to lead early intervention.

Methods
The data of 534 hospitalized patients were assessed retrospectively. Risk factors and laboratory tests that might enable the prediction of prognosis defined as being transferred to the intensive care unit and/or exitus have been investigated.

Results
At the admission, 398 of 534 patients (74.5%) were mild‐moderate ill. It was determined that the male gender, advanced age, comorbidity were risk factors for severity. In order to estimate the severity of the disease, ROC analysis revealed that the areas under the curve (AUC) which were determined based on the optimal cut off values that were calculated for the variables of values of neutrophil to lymphocyte ratio (NLR>3.69), C‐reactive protein (CRP >46 mg/L), troponin I (>5.3 ng/L), lactate dehydrogenase LDH (>325 U/L), ferritin (>303 ug/L), D‐dimer (>574 ug/L), neutrophil NE (> 4.99 x10 ^ 9/L), lymphocyte (LE <1.04 x10^9/L), SO2 (<%92) were 0.762, 0.757,0.742, 0.705, 0.698, 0.694,0.688, 0.678, 0.66, respectively. To predict mortality, AUC of values for optimal cut off troponin I (>7.4 ng/L), age (>62), SO2(<%89), urea (>40 mg/dL), procalcitonin (>0.21 ug/L), CKMB (>2.6 ng/L) were 0.715, 0.685, 0.644, 0.632, 0.627, 0.617, respectively.

Conclusions
The clinical progress could be severe if the baseline values of NLR, CRP, troponin I, LDH, are above, LE is below the specified cut‐off point. We found that the troponin I, elder age and SO2 values could predict mortality.
This article is protected by copyright. All rights reserved.

Full text

Received: 8 October 2020
|
Revised: 9 December 2020
|
Accepted: 16 December 2020
DOI: 10.1002/jmv.26751
RESEARCH ARTICLE
Could we predict the prognosis of the COVID‐19 disease?
Ceren A. Tahtasakal
1
|Ahsen Oncul
1
|Dilek Yıldız Sevgi
1
|Emine Celik
1
|
Murat Ocal
2
|HakkıM. Turkkan
1
|Banu Bayraktar
2
|Sibel Oba
3
|
Ilyas Dokmetas
1
1
Department of Clinical Microbiology and
Infectious Diseases, Sisli Hamidiye Etfal
Training and Research Hospital, University of
Health Sciences, Istanbul, Turkey
2
Department of Microbiology, Sisli Hamidiye
Etfal Training and Research Hospital,
University of Health Sciences, Istanbul,
Turkey
3
Department of Anesthesia and Reanimation
Clinic, Sisli Hamidiye Etfal Training and
Research Hospital, University of Health
Sciences, Istanbul, Turkey
Correspondence
Ceren A. Tahtasakal, Merkez M. Günebakan S.
Bila Apt. No: 12/14 Kağıthane, İstanbul,
Turkey.
Email: cerenatasoy.i@gmail.com
Abstract
Objectives: Coronavirus 2019 disease (COVID‐19) lead to one of the pandemics of
the last century. We aimed to predict poor prognosis among severe patients to lead
early intervention.
Methods: The data of 534 hospitalized patients were assessed retrospectively. Risk
factors and laboratory tests that might enable the prediction of prognosis defined as
being transferred to the intensive care unit and/or exitus have been investigated.
Results: At the admission, 398 of 534 patients (74.5%) were mild‐moderate ill. It
was determined that the male gender, advanced age, and comorbidity were risk
factors for severity. To estimate the severity of the disease, receiver operating
characteristic analysis revealed that the areas under the curve which were de-
termined based on the optimal cut off values that were calculated for the variables
of values of neutrophil to lymphocyte ratio (NLR > 3.69), C‐reactive protein
(CRP > 46 mg/L), troponin I ( > 5.3 ng/L), lactate dehydrogenase (LDH > 325 U/L),
ferritin ( > 303 ug/L), D‐dimer ( > 574 μg/L), neutrophil NE ( > 4.99 × 10
9
/L), lym-
phocyte (LE < 1.04 × 10
9
/L), SO
2
( < %92) were 0.762, 0.757,0.742, 0.705, 0.698,
0.694,0.688, 0.678, and 0.66, respectively. To predict mortality, AUC of values for
optimal cutoff troponin I ( > 7.4 ng/L), age ( > 62), SO
2
( < %89), urea ( > 40 mg/dL),
procalcitonin ( > 0.21 ug/L), CKMB ( > 2.6 ng/L) were 0.715, 0.685, 0.644, 0.632,
0.627, and 0.617, respectively.
Conclusions: The clinical progress could be severe if the baseline values of NLR,
CRP, troponin I, LDH, are above, and LE is below the specified cut‐off point. We
found that the troponin I, elder age, and SO
2
values could predict mortality.
KEYWORDS
COVID‐19, SARS‐CoV 2, pandemic, novel coronavirus, prognosis
1|INTRODUCTION
Coronavirus 2019 disease (COVID‐19) started as an infectious dis-
ease concomitant with pneumonia and acute respiratory distress
syndrome (ARDS) of unknown cause in Wuhan, China, in December
2019.
1
It was detected through performing the real‐time reverse‐
transcription polymerase chain reaction (RT‐PCR) test, which is
studied from respiratory tract samples, that the virus from the cor-
onavirus family, namely severe acute respiratory syndrome‐
coronavirus 2 (SARS‐CoV 2), has caused the disease.
2
The World
Health Organization (WHO) declared it as a “Public Health Emer-
gency of International Concern”on January 30, 2019, and as a
pandemic on March 11, 2020.
3
The COVID‐19 disease has been
detected in 5,017,897 people in 215 countries as of May 20, 2020,
J Med Virol. 2020;1–11. wileyonlinelibrary.com/journal/jmv © 2020 Wiley Periodicals LLC
|
1

and caused 325,624 deaths.
4
On the same date, 152,587 cases have
been detected in Turkey, and 4222 of them ended up with the death.
Even though the transmission rate and mortality rate varies among
countries, studies on the prognosis of COVID‐19 disease, which has
caused one of the worst pandemics of the last century, have become
clinically crucial.
COVID‐19 has a wide range of clinical manifestations, from
asymptomatic infection to severe acute respiratory failure that can
end up with death.
5
Severe clinic manifestations might also develop
in infected patients who initially have only mild symptoms. It leads to
deaths, though the mortality rate differs among the regions.
Apart from its affinity to the respiratory tract, it leads to the
failure of other systems and organs by causing endothelial damage
and cytokine storm. A great majority of those infected with SARS‐
CoV 2 have a mild course of the disease. The mortality rate is higher
among severely and critically ill patients. In this respect, it is crucial
to determine the factors that impact the prognosis of the disease. If
risk factors are identified, then early identification of severely ill
patients and potential progression could enable early intervention
and management through a closer follow‐up of these patients.
2|METHOD
2.1 |Study design and participants
Inpatients who were followed up with the pre‐diagnosis of COVID‐19
in Sisli Hamidiye Etfal Training and Research Hospital between March
12, 2020, when the first COVID‐19 case was detected in Turkey, and
April 21, 2020, were analyzed retrospectively. Data of 570 hospita-
lized patients were analyzed retrospectively in our single‐centered
trial and 36 patients were excluded from the study. Patients aged over
18, and who were detected with SARS‐CoV2 RT‐PCR (+) and/or
SARS‐CoV2 Ig M/IgG (+) or who have the symptoms that are radi-
ologically compatible with COVID‐19 but could not be explained by
other factors were included in the study. Patients who were not
compatible with the clinical manifestations or who were radiologically
incompatible, and who had RT‐PCR (−) were excluded from the study.
Epidemiological, clinical, laboratory, radiology, and treatment data
were obtained from the discharge reports of the patients and the
Picture Archiving and Communication System.
2.2 |Definitions
The patients were divided into two groups, categorized as mild‐
moderate and severe‐critical, based on the first clinical manifestation
at the onset of the hospitalization. (Mild: without pneumonia; mod-
erate: the presence of pneumonia with respiratory symptoms and
without hypoxia; severe: dyspnea, respiratory rate > 30/min, oxygen
saturation < 94%, PaO2/FiO2 <300, and pulmonary infiltration
> 50%; critical: mechanical ventilation requiring respiratory failure,
septic shock, and multiorgan failure).
6
Differences between the two
patient groups, regarding age, gender, occupation, comorbidities,
administration of antihypertensive drugs, smoking, alcohol, and
substance use were examined. The duration of application to hospital
and complaints were compared with the findings of physical ex-
amination. The effectiveness of the laboratory tests (hemogram,
C‐reactive protein [CRP], procalcitonin [PCT], ferritin, liver and kid-
ney function tests, D‐dimer, arterial blood gas [in room air], and
cardiac enzyme results), which are requested at the time of admis-
sion and the thoracic computed tomography (CT) in determining the
severity and course of the disease were examined. As the treatment
options are classified specifically for mildly and severely ill patients in
the guideline of the Ministry of Health scientific committee, they
were not used to determine the impact on the progress.
Severely critically ill patients were subdivided into two sub-
groups as exitus and survival. Poor prognosis was defined as being
transferred to the intensive care unit and/or exitus. Disease outcome
was considered as either being discharged with full recovery or
exitus.
2.3 |Ethics approval
Approval of the Sisli Hamidiye Etfal Training and Research Hospital
ethics committee was obtained on April 22, 2020, with the decision
number of 2731/1481.
2.4 |Statistical analysis
Statistical analysis of the data was performed through the software
of IBM SPSS Statistics, Version 24. Pearson's χ
2
and Fisher's Exact
tests were used to comparing categorical data between groups, and
Mann–Whitney U‐test was used for comparisons between
groups as continuous data were not normally distributed
(Kolmogorov–Smirnov p< .05). The prognosis power of age and
570 hospitalized
paent with
COVID-19 pre-diagnosis
Mild-moderate
398 paents
534 paents included
Severe-crical
136 paents
Exitus
48 paents
Survival
88 paents
36 paents excluded
-Clinically incompable
-SARSCoV-2 PCR (-) and Thorax CT(-)
FIGURE 1 Flowchart of hospitalized patients with coronavirus
disease 2019
2
|
TAHTASAKAL ET AL.

TABLE 1 Epidemiologic, demoghrafic, and clinical characteristic of hospitalized patients with COVID‐19
Total Mild‐moderate Severe‐critical
n= 534 n= 398 n= 136 p
Age ≥65 194 (36.3) 123 (30.9) 71 (52.2) .001
Gender Female 233 (43.6) 191 (48) 42 (30.9) .001
Male 301 (56.4) 207 (52) 94 (69.1)
Comorbidity 335 (62.7) 242 (60.8) 93 (68.4) .115
Chronic obstructive pulmonary disease 34 (6.4) 21 (5.3) 13 (9.6) .077
Asthma 40 (7.5) 30 (7.5) 10 (7.4) .944
Hypertension 240 (44.9) 168 (42.2) 72 (52.9) .030
Coronary heart disease 111 (20.8) 75 (18.8) 36 (26.5) .058
Diabetes 132 (24.7) 88 (22.1) 44 (32.4) .017
İmmunsupression 12 (2.2) 6 (1.5) 6 (4.4) .085
Malignancy 19 (3.6) 8 (2) 11 (8.1) .002
Chronic hepatitis 17 (3.2) 9 (2.3) 8 (5.9) .048
Chronic kidney diseases 33 (6.2) 21 (5.3) 12 (8.8) .138
Heart failure 13 (2.4) 9 (2.3) 4 (2.9) .747
Cerebrovascular diiseases 19 (3.6) 7 (1.8) 12 (8.8) .000
Tuberculosis (previous) 2 (0.4) 1 (0.3) 1 (0.7) .445
Pneumonia (previous) 12 (2.2) 8 (2) 4 (2.9) .512
Hypotiroidism 16 (3) 16 (4) 0 (0) .016
Antipyretic use 124 (23.8) 86 (22.2) 38 (28.8) .123
Antihypertensive use 234 (43.8) 162 (40.7) 72 (52.9) .013
ACEi 78 (14.6) 55 (13.8) 23 (16.9) .378
ARB 61 (11.4) 38 (9.5) 23 (16.9) .020
B blocker 111 (20.8) 76 (19.1) 35 (25.7) .099
Ca canal blocker 107 (20) 69 (17.3) 38 (27.9) .008
Diuretic 98 (18.4) 65 (16.3) 33 (24.3) .039
Alfa blocker 12 (2.2) 7 (1.8) 5 (3.7) .193
Habits 118 (29,6) 90 (29,6) 28 (29.8) .973
Current smoker 52 (13.1) 44 (14.5) 8 (8.5) .134
Ex smoker 60 (15.1) 41 (13.5) 19 (20.2) .111
Alcohol 17 (4.3) 14 (4.6) 3 (3.2) .772
Symptoms
Fever 266 (50.7) 183 (46.9) 83 (61.5) .004
Cough 333 (63.4) 244 (62.6) 89 (65.9) .485
Dyspnea 197 (37.5) 117 (30) 80 (59.3) <.001
Vomiting 74 (14.1) 50 (12.8) 24 (17.8) .154
Diarrhea 46 (8.8) 35 (9) 11 (8.1) .770
Myalgia 148 (28.2) 122 (31.3) 26 (19.3) .007
Headache 77 (14.7) 67 (17.2) 10 (7.4) .006
Fatigue 305 (58.1) 235 (60.3) 70 (51.9) .088
Runny nose 4 (0.8) 4 (1) 0 (0) .577
Sore throat 45 (8.6) 40 (10.3) 5 (3.7) .019
Rash 1 (0.2) 1 (0.3) 0 (0) 1.000
Sputum 26 (5) 15 (3.8) 11 (8.1) .047
Abdominal pain 20 (3.8) 15 (3.8) 5 (3.7) .941
Lack of apetite 58 (11) 39 (10) 19 (14.1) .193
Duration symptoms >5 day 277 (55.1) 212 (55.9) 65 (52.4) .494
(Continues)
TAHTASAKAL ET AL.
|
3

laboratory values to predict severe‐critical status in all patients and
exitus in severe‐critical cases were assessed based on the analysis of
the receiver operating characteristic (ROC) curve. A cox regression
analysis (univariate and multivariate) was performed to investigate
the effect of age and laboratory tests on mortality. Results were
considered statistically significant at p< .05.
3|RESULTS
3.1 |Demographic characteristics
A total of 534 patients were included in the study, 398 (74.5%) had
mild‐moderate clinical manifestations, and 136 (25.5%) had severe‐
critical clinical manifestations, during the onset of the admission
(Figure 1). Demographic and clinical characteristics are presented
comparatively between the two groups in Table 1. Of the patients,
301 (56.4%) were male, while 233 (43.6%) were female. The rate of
admission and mortality (67.9%, n= 36) was significantly more pre-
valent (p= .001) among the severely critically ill male. The mean age
was 58.8 and the median value was 59 (interquartile range
[IQR] = 19–97), while it was 66 in the group of severely ill patients
(IQR = 19–94); and it was found out to be a statistically significant
difference between the two groups. About 36.3% (n= 194) of the
patients were aged over 65 and their admissions with the severe
clinical presentation were more prevalent. Approximately 66.3%
(n= 35) of the patients who died were over 65 years old. Mortality
was 9.92% throughout the hospital follow‐up and it was 35.3% in the
severely ill patient group, whereas it was 1.3% in the mild‐moderate
group; and a significant difference was determined between both
groups.
3.2 |Comorbidity, habits, and clinical features
Upon examining the data of the patients with regard to the presence
of chronic diseases, it was found that the disease progressed with a
severe clinical course among patients with hypertension (HT), dia-
betes mellitus (DM), malignancy, chronic viral hepatitis, and medical
history of cerebrovascular accident. It was determined to have a mild
course among patients with hypothyroid (p= .016). There was no
significant difference in the clinical severity of the patients with a
medical history of chronic lung disease or pneumonia/tuberculosis
(p> .05). It was found out that receiving antihypertensive drugs was
significantly more prevalent among patients who presented with
severe‐critical clinical manifestations (p= .013). It was determined
that severe‐critical clinical manifestations were significantly more
common in the patients who received angiotensin receptor blocker
(ARB), calcium channel blocker and diuretic among antihypertensive
agents, compared with those who did not receive any anti-
hypertensive drug. The clinical picture of those receiving ACE in-
hibitors and alpha‐blockers was comparable to those who did not
receive any antihypertensive drug.
No significant difference was identified between the clinical
manifestations of the patients who smoke and who have quit
smoking.
The most prevalent complaints were cough, weakness, fever,
shortness of breath, common muscle aches, headache, nausea, and
vomiting, respectively. It was found out that fever and shortness of
breath were significantly common among patients with severe and
critical clinical manifestations, while widespread myalgia, headache,
and sore throat were statistically more frequent in patients with
mild‐moderate clinical manifestations. No difference was detected
between the other application complaints (Table 1).
TABLE 1 (Continued)
Total Mild‐moderate Severe‐critical
n= 534 n= 398 n= 136 p
Physicial examination
Fever 146 (44.5) 99 (45.8) 47 (42) .504
Tachycardia 91 (27.7) 43 (19.9) 48 (42.9) <.001
Hypotensive 63 (19.2) 34 (15.7) 29 (25.9) .027
Tachypnea 115 (35.1) 38 (17.6) 77 (68.8) <.001
Rales 165 (50.3) 103 (47.7) 62 (55.4) .188
Murmur, additional sound 1 (0.3) 1 (0.5) 0 (0) 1.000
Conjunctivitis, pharengeal hyperemia 5 (1.5) 2 (0.9) 3 (2,7) .342
Rash 1 (0.3) 1 (0.5) 0 (0) 1.000
Desaturation 93 (28.4) 23 (10.6) 70 (62.5) <.001
ICU transfer 79 (14.8) 7 (1.8) 72 (52.9) <.001
MV 57 (10.7) 6 (1.5) 51 (37.5) <.001
In hospital death 53 (9.9) 5 (1.3) 48 (35.3) <.001
Rehospitalization 21 (4) 16 (4) 5 (3.7) .878
Note: Pearson's χ
2
, Fisher's Exact test. Bold and italic values are statistically significant.
Abbreviations: ACEi, angiotensin converting enzyme inhibitors; ARB, angiotensin receptor blocker; ICU, intensive care unit; MV, mechanical ventilation.
4
|
TAHTASAKAL ET AL.

In the study, PCR testing of SARS‐CoV2 was positive in the
combined throat‐nasopharynx swab of 296 (55.5%) patients; and no
difference was determined between the mild‐moderate and severe‐
critical groups. Thorax CT was compatible with COVID‐19 pneu-
monia in 460 patients, but there was no difference between groups.
The rates of transfer to the intensive care unit (ICU; 52.9%),
mechanical ventilation requirement (37.5%), and mortality (35.5%)
were significantly higher in the serious‐critical group (p< .001).
When the habits, application complaints, duration of complaints,
and physical examination findings of severely critically ill patients are
analyzed based on the disease outcome (discharged with full re-
covery/exitus), it was determined that there was a statistically sig-
nificant difference between the groups regarding diarrhea findings at
admission, duration of complaints, and hypotension findings during
physical examination (p< .05). The recovery rate was higher in those
with a complaint duration longer than 5 days and those who pre-
sented with diarrhea. There was no statistically significant difference
between the groups, regarding other variables (p> .05).
3.3 |Examinations
Based on the disease severity classification of the patients, values of
white blood cell (WBC), neutrophil (NE), CRP, alanine transaminase
(ALT), aspartate transaminase (AST), urea, creatinine, lactate dehy-
drogenase (LDH), ferritin, D‐dimer, lactate, cardiac enzymes, and partial
carbondioxide pressure (PCO
2
) were determined to be statistically sig-
nificantly higher and lymphocyte count was lower among severely cri-
tically ill patients (p< .05). The duration of hospital stay was significantly
longer in the group of severely critically ill patients (p< .001; Table 2).
TABLE 2 Age, duration of hospitalization and distribution of laboratory values according to the disease category of patients
Total Mild‐moderate Severe‐critical
Median (Min.–Max.) Median (Min.–Max.) Median (Min.–Max.) p
Age 59 (19–97) 56 (21–97) 66 (19–94) <.001
Duration of hospitalization 8 (1–59) 7 (1–38) 12 (2–59) <.001
WBC (10
9
/L) 6.05 (0–158) 5.77 (1.85–50) 7.24 (0–158) <.001
NE 4.2 (0.67–33.52) 3.86 (0.67–17.03) 5.36 (1.14–33.52) <.001
LE 1.16 (0.2–146.5) 1.28 (0.27–5.54) 0.89 (0.2–146.5) <.001
NLR 3.41 (0.06–83.8) 2.85 (0.55–31.56) 6.26 (0.06–83.8) .911
Plt 187 (15–585) 187 (19.9–546) 186 (15–585) .206
Hgb 13.5 (5.8–17.6) 13.5 (5.8–17.6) 13.4 (7.6–17.5) <.001
CRP 41 (0.5–322) 28 (0.5–322) 100 (1.5–303) <.001
Procalsitonin 0.12 (0.12–6.1) 0.12 (0.12–3.8) 0.17 (0.12–6.1) .154
ALT 23 (3–724) 23 (3–279) 25 (5–724) <.001
AST 30 (2–1364) 28 (2–161) 36 (8–1364) <.001
Urea 31 (8–195) 30 (8–195) 35 (13–176) <.001
Creatinine 0.86 (0.3–14.4) 0.81 (0.3–14.4) 0.95 (0.5–10.45) <.001
LDH 257.5 (1.09–2226) 245 (1.09–921) 331 (26–2226) <.001
Ferritin 189 (4–44,052) 152.5 (4–44,052) 408 (14.5–7142) <.001
D‐Dimer 619 (43–44,400) 549 (93–44,400) 872 (43–32,800) <.001
Troponin I 5.3 (1.3–57,228) 4 (1.3–57,228) 11.4 (2.3–42,844) <.001
CK‐MB 1.2 (0.1–138) 1 (0.1–138) 1.7 (0.18–59.4) .001
PaO
2
(without O
2
) 69.6 (1.08–178) 79.5 (46–114) 65 (1.08–178) 1.000
PaCO
2
33 (16–97) 33 (16–97) 33 (17–91) .001
SO
2
92 (68–100) 94 (70–100) 91 (68–99) .181
Lactate 1.41 (−0.93 to 7.91) 1.4 (−0.93 to 4.41) 1.5 (0.54–7.91) <.001
Note: Mann–Whitney U analysis. Bold and italic values are statistically significant.
Abbreviations: ALT, alanine transaminase; AST, aspartate transaminase; CK‐MB, creatinin kinase‐myocardial band; CRP, C‐reactive protein; Hgb,
hemoglobin; LDH, lactate dehydrogenase; LE, lymphocyte; NE, neutrophil; NLR, neutrophil/lymphocyte ratio; Plt, platelet; PaCO
2
, partial carbondioxide
pressure; PaO
2
, partial oxygen pressure; WBC, white blood cell.
TAHTASAKAL ET AL.
|
5

When the age, duration of hospital stay and the distribution of
laboratory values of seriously critically ill patients are examined, a
statistically significant difference was found between the groups,
regarding the values of age, CRP, AST, D‐dimer, troponin, and
PCO
2
(p< .05). It was found out that the values of patients whose
disease outcomes resulted in death were significantly higher
(Table 3).
When the results of ROC analysis for the diagnosis power of age
and laboratory values in the prognosis of the disease severity among
all patients were examined.
The area under the curve (AUC) values, which were determined
based on the optimal cut off values that were calculated for the
variables of age ( > 57), WBC ( > 7.79 × 10
9
/L), NE ( > 4.99 × 10
9
/L),
LE ( < 1.04 × 10
9
/L), neutrophil/lymphocyte ratio (NLR > 3.69), CRP
( > 46 mg/L), procalcitonin ( > 0.13 μg/L), AST ( > 40 U/L), urea
( > 24 mg/dL), creatinine ( > 0.76 mg/dL), LDH ( > 325 U/L), ferritin
( > 303 μg/L), D‐dimer ( > 574 μg/L), troponin I ( > 5.3 ng/L), CK‐MB
( > 1.4 ng/L), and SO
2
( < 92), were found to be statistically significant
(p< .05). To predict the severity of the disease, ROC analysis
demonstrated that the AUC of NLR, CRP, troponin I, LDH, ferritin,
D‐dimer, NE, LE, and SO
2
were 0.762, 0.757, 0.742, 0.705, 0.698,
0.694, 0.688, 0.678, and 0.66, respectively. The most effective was
the NLR, the second most effective one was CRP, whereas the least
effective was urea (0.62; Table 4).
When the results of the ROC analysis for the diagnostic power
of age and laboratory values in predicting mortality in severely cri-
tically ill patients are examined, the AUC values, which were de-
termined based on the optimal cut off values that were calculated for
the variables of age ( > 62), procalcitonin ( > 0.21 μg/L), urea
( > 40 mg/dL), troponin ( > 7.4 ng/L), CK‐MB ( > 2.6 ng/L), and SO
2
TABLE 3 Age, duration of hospitalization and laboratory values distribution of severe‐critical cases according to the outcome of the disease
Total (n= 136) Survivor (n= 88) Ex (n= 48)
Median (Min.–Max.) Median (Min.–Max.) Median (Min.–Max.) p
Age 66 (19–94) 61 (19–91) 70.5 (43–94) <.001
Duration of hospitalization 12 (2–59) 13 (2–44) 11 (2–59) .416
WBC 7.24 (0–158) 6.95 (0–158) 8.09 (1.73–35.17) .300
NE 5.36 (1.14–33.52) 5.28 (1.61–18.76) 6.47 (1.14–33.52) .071
LE 0.89 (0.2–146.5) 0.97 (0.24–146.5) 0.77 (0.2–2.12) .084
NLR 6.26 (0.06–83.8) 5.63 (0.06–22.58) 7.25 (1.52–83.8) .454
Plt 186 (15–585) 189 (15–585) 185 (27–467) .189
HGB 13.4 (7.6–17.5) 13.45 (7.6–17.5) 13.2 (7.6–15.7) .166
CRP 100 (1.5–303) 82.5 (1.5–303) 112 (10–302) .012
Procalsitonin 0.17 (0.12–6.1) 0.14 (0.12–1) 0.25 (0.12–6.1) .489
ALT 25 (5–724) 27 (5–127) 24 (9–724) .786
AST 36 (8–1364) 35.5 (8–163) 38.5 (10–1364) .011
Ürea 35 (13–176) 33 (13–176) 43.5 (19–127) .137
Creatinine 0.95 (0.5–10.45) 0.91 (0.5–10.45) 1.01 (0.58–6.19) .646
LDH 331 (26–2226) 331 (26–990) 324.5 (155–2226) .092
Ferritin 408 (14.5–7142) 371 (14.5–7142) 482 (15.4–2768) .086
D‐Dimer 872 (43–32,800) 780.5 (43–21,200) 1240 (388–32,800) <.001
Troponin I 11.4 (2.3‐42,844) 8.5 (2.3–3940) 25.05 (2.9–42,844) .023
CK‐MB 1.7 (0.18–59.4) 1.55 (0.18–26) 2.2 (0.3–59.4) .223
PaO
2
(without O
2
) 65 (1.08–178) 67 (41–142) 63.5 (1.08–178) .765
PaCO
2
33 (17–91) 32.3 (19–91) 33 (17–87) .014
SO
2
91 (68–99) 92 (80–99) 89.45 (68–99) .800
Lactate 1.5 (0.54–7.91) 1.5 (0.54–5.04) 1.5 (0.67–7.91) .099
Note: Mann–Whitney U analysis. Bold and italic values are statistically significant.
Abbreviations: ALT, alanine transaminase; AST, aspartate transaminase; CK‐MB, creatinin kinase‐myocardial band; CRP, C‐reactive protein; Hgb,
hemoglobin; LDH, lactate dehydrogenase; LE, lymphocyte; NE, neutrophil; NLR, neutrophil/lymphocyte ratio; Plt, platelet; PaCO
2
, partial carbondioxide
pressure; PaO
2
, partial oxygen pressure; WBC, white blood cell.
6
|
TAHTASAKAL ET AL.

( < 89), were found to be statistically significant (p< .05). To predict
mortality, ROC analysis revealed that the area under the curves of
troponin I, age, SO
2
, PCT, and CK‐MB were 0.715, 0.685, 0.644,
0.632, 0.627, and 0.617, respectively. The area under the curve
(AUC) values, which were determined based on the optimal cut off
values that were calculated for the other variables, were not found
to be statistically significant (p> .05; Table 5).
According to the univariate analysis performed to investigate
the effect of age and laboratory tests on mortality; respectively
changesofage,WBC,NE,LE,NLR,CRP,procalcitonin,ALT,AST,
LDH, SO
2
,andlactatevalues0.029,0.019,0.098,−0.925, 0.050,
0.006, 0.589, 0.005, 0.003, 0.002, −0.071, and 0.478; showed
1,030, 1,019, 1,103, 0.396, 1.051, 1.007, 1.803, 1.005, 1.003,
1.002, 0.931, and 1.613‐fold increase in mortality (Table 6). In the
multivariate analysis performed with the model created with sig-
nificant variables in the univariate analysis, the prediction of
mortality increase values of NLR (B: 0.043, exp B: 1.044, p:0.000),
CRP (B: 0.004, exp B: 1.004, p:0.024), AST (B: 0.003, exp B: 1.003,
p:0.002), and lactate (B: 0.373, exp B: 1.453, p:0.017) was found to
be significant (Table 7).
4|DISCUSSION
The factors, which impact the prognosis of COVID‐19, were in-
vestigated in our study. It is considered that early prognosis of the
severity and mortality could have positive impacts on the patient.
7
Even the fact that the patient is categorized as mildly moderately
and severely critically ill at the onset of the admission gives an idea
about the prognosis of the disease. As was determined in our study,
ICU transfer was 1.8% and mortality was 1.3% in the mild‐moderate
group, whereas it was 52.2% and 35.8%, respectively in the severe‐
critical group. Similar to other studies, both disease and severe
clinical manifestations were encountered more commonly among
males compared with females.
8,9
It is considered that comorbidities
(male = 133 and female = 54), which was associated with poor prog-
nosis in males, could be related to the significantly higher frequency.
It has been revealed in the previous studies that advanced age is
a determining factor in the severe course of the disease. Pulmonary
insufficiency, lack of remodeling, and the presence of im-
munosuppression, which is concomitant with comorbid diseases, are
the potential culprits for patients aged over 65.
7
The results of our
TABLE 4 ROC analysis results for the
diagnostic powers of age and laboratory
values in predicting the severe‐critical
power of the disease in all cases
Cutoff Sensitivity Specificity +PV −PV AUC %95 CI p
Age >57 72.06 53.02 34.4 84.7 0.654 0.612–0.694 <.001
WBC >7.79 46.32 77.14 40.9 80.8 0.638 0.595–0.679 <.001
NE >4.99 58.09 70.1 39.9 83 0.688 0.647–0.727 <.001
LE ≤1.04 63.24 67.34 39.8 84.3 0,678 0.636–0.717 <.001
NLR >3.69 78.68 66.08 44.2 90.1 0.762 0.723–0.797 <.001
Plt >232 31.62 76,.13 31.2 76.5 0.503 0.460–0.546 .916
HGB ≤11.8 32.59 80.86 36.7 77.9 0.536 0.493–0.579 .223
CRP >46 79.41 63.22 42.5 90 0.757 0.718–0.793 <.001
Procalsitonin >0.13 58.21 78.31 48.7 84.1 0.7 0.658–0.739 <.001
ALT >26 48.53 59.55 29.1 77.2 0.541 0.498–0.584 .159
AST >40 47.06 76.34 40.8 80.6 0.637 0.594–0.678 <.001
Urea >24 88.97 29.97 30.3 88.8 0.622 0.579–0.663 <.001
Creatinine >0.76 80.88 38.54 31.1 85.5 0.63 0.587–0.671 <.001
LDH >325 52.34 81.65 49.3 83.4 0.705 0.63–0.744 <.001
Ferritin >303 61.48 76.94 48.3 85.1 0.698 0.657–0.737 <.001
D‐Dimer >574 76.92 52.44 37.6 85.9 0.694 0.651–0.735 <.001
Troponin I >5.3 78.52 60.96 42.1 88.7 0.742 0.702–0.780 <.001
CK‐MB >1.4 57.46 64.89 36.8 81.1 0.629 0.585–0.671 <.001
SO
2
≤92 64.65 68.97 78 53.3 0.66 0.580–0.734 .001
Lactate >2.18 24.81 86.72 41.2 75.4 0.539 0.494–0.584 .197
Note: Bold and italic values are statistically significant.
Abbreviations: ALT, alanine transaminase; AST, aspartate transaminase; AUC, area under the curves;
CI, confidence interval; CK‐MB, creatinin kinase‐myocardial band; CRP, C‐reactive protein; Hgb,
hemoglobin; LDH, lactate dehydrogenase; LE, lymphocyte; NE, neutrophil; NLR, neutrophil/
lymphocyte ratio; Plt, platelet; ROC, receiver operating characteristic; WBC, white blood cell.
TAHTASAKAL ET AL.
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7

study are also in line with the previous research works. Patients aged
over 65 constituted 36.3% of the total number of patients and 52.2%
of the severely ill patients' group. It was found out to be a con-
siderable factor in the prognosis of a severe course of the disease. It
could be predicted based on the ROC analysis that the disease could
progress severely and the mortality risk could increase above the
specified age values, due to the fact that when the cut‐off point of
age is specified as more than 57, the severity of the disease and
when the cut off point of age is specified as more than 62, the power
to predict the exitus, were found to be significant.
As previous studies have predicted, the presence of hyperten-
sion, DM, and malignancy leads to COVID‐19 to progress severely.
9
It was determined in our study that a medical history of chronic viral
hepatitis and cerebrovasculer diseases (CVD), in addition to HT, DM,
malignancy, and also caused a poor prognosis. However, it was found
through the subgroup analysis that it was not associated with the
exitus.
9
On the other hand, the disease has a mild to moderate se-
verity among patients with hypothyroid. Upon the literature review,
similar results were not detected in other studies.
A severe‐critical course of the disease was observed more
commonly in antihypertensive drug receivers. It has been sug-
gested in the previous studies that the administration of angio-
tensin converting enzyme inhibitors (ACEi) and angiotensin II
receptor blocker (ARB) increased ACE2 receptor expression and
the disease progressed severely, whereas Ca channel blocker was
demonstrated to be safe.
10
In our study, the use of ARB, Ca
channel blocker, and diuretic was found to be associated with
severe prognosis. No difference was found between survivors and
exitus, based on the subgroup analysis of severely ill patients.
Unlike previous studies, ACEi was not associated with severe
clinical manifestations. The use of B blockers was common among
the exitus group, based on the results of the subgroup analysis.
Further research works are required on this issue, though it is
considered that there might be a correlation with the inhibition of
pulmonary beta receptors.
Even though previous studies have put forward that the patients,
who smoke and who have quit smoking, have a poor prognosis;
contrary to this finding, no difference was found in the clinical course
TABLE 5 ROC analysis results for the
diagnostic forces of age and laboratory
values in predicting exitus in severe‐
critical cases
Cutoff Sensitivity Specificity +PV −PV AUC %95 CI p
Age >62 79.17 53.41 48.1 82.5 0.685 0.600–0.762 <.001
WBC >8.49 47.92 69.32 46 70.9 0.542 0.455–0.628 .428
NE >8.01 39.58 76.14 47.5 69.8 0.554 0.466–0.639 .309
LE ≤0.8 56.25 65.91 47.4 73.4 0.594 0.506–0.677 .065
NLR >10.11 35.42 80.68 50 69.6 0.59 0.502–0.674 .082
Plt ≤267 87.5 25 38.9 78.6 0.539 0.451–0.625 .456
HGB ≤11.1 34.04 87.5 59.3 71.3 0.569 0.481–0.654 .201
CRP >80 66.67 50 42.1 73.3 0.572 0.484–0.657 .162
Procalsitonin >0.21 56.25 67.44 49.1 73.4 0.627 0.539–0.709 .014
ALT ≤25 58.33 52.27 40 69.7 0.536 0.449–0.622 .492
AST >44 33.33 59.09 30.8 61.9 0.514 0.427–0.601 .784
Urea >40 56.25 70.45 50.9 74.7 0.632 0.545–0.713 .008
Creatinine >1.11 43.75 75 48.8 71 0.577 0.490–0.661 .145
LDH >615 22.73 95.24 71.4 70.2 0.525 0.435–0.614 .662
Ferritin >602 43.75 77.01 51.2 71.3 0.588 0.500–0.672 .098
D‐Dimer >980 58.7 63.1 46.6 73.6 0.591 0.502–0.677 .082
Troponin I >7.4 85.42 48.28 47.7 85.7 0.715 0.631–0.789 <.001
CK‐MB >2.6 45.83 75.58 51.2 71.4 0.619 0.531–0.701 .018
SO
2
≤89.8 52.17 77.36 66.7 65.1 0.644 0.541–0.737 .012
Lactate >1.1 81.25 30.59 39.8 74.3 0.513 0.425–0.601 .796
Note: Bold and italic values are statistically significant.
Abbreviations: ALT, alanine transaminase; AST, aspartate transaminase; AUC, area under the curves;
CI, confidence interval; CK‐MB, creatinin kinase‐myocardial band; CRP, C‐reactive protein; Hgb,
hemoglobin; LDH, lactate dehydrogenase; LE, lymphocyte; NE, neutrophil; NLR, neutrophil/
lymphocyte ratio; Plt, platelet; ROC, receiver operating characteristic; WBC, white blood cell.
8
|
TAHTASAKAL ET AL.

of 112 (28.2%) smokers/quitters in our study.
11
Hence, it has been
found out that smoking does not cause poor prognosis.
Complaints of shortness of breath, fatigue, diarrhea, and
hemoptysis were more common in severely ill patients, based on the
results of the conducted studies.
12
It was determined based on the
results of our study that complaints of fever and shortness of breath
were more prevalent in the patients with poor prognosis, while
muscle aches and sore throat were more prevalent among patients
mild clinical manifestation. The presence of dyspnea predicts that the
clinical course could be severe. There were no complaints predicting
mortality, but unlike previous studies, diarrhea was more common in
survivors. The survival rate was higher in patients with a complaint
duration longer than 5 days before admission to the hospital. It is
considered that late admission due to mild symptoms might be
associated.
Similar studies have suggested that increased levels of LDH,
NLR, WBC, and BNP (b‐type natriuretic peptide) might be associated
with the severity of the disease.
13
The level of the LDH is considered
to be elevated in correlation with the degree of lung damage.
14
Studies have shown NLR as an index, which is associated with the
TABLE 6 Single cox regression analysis results for the effect of
age and laboratory values on mortality
BpExp(B) 95.0% CI
Yaş0.029 0.003 1.030 1.010 1.049
WBC 0.019 0.031 1.019 1.002 1.037
NE 0.098 0.000 1.103 1.052 1.156
LE −0.925 0.007 0.396 0.203 0.775
NLR 0.050 0.000 1.051 1.034 1.068
Plt 0.000 0.891 1.000 0.996 1.003
Hgb −0.073 0.268 0.929 0.816 1.058
CRP 0.006 0.000 1.007 1.003 1.010
Procalsitonin 0.589 0.000 1.803 1.445 2.250
ALT 0.005 0.001 1.005 1.002 1.008
AST 0.003 0.000 1.003 1.002 1.005
Urea 0.006 0.074 1.006 0.999 1.013
Creatinine 0.066 0.387 1.068 0.920 1.241
LDH 0.002 0.001 1.002 1.001 1.003
Ferritin 0.000 0.458 1.000 1.000 1.000
D‐Dimer 0.000 0.186 1.000 1.000 1.000
Troponin I 0.000 0.313 1.000 1.000 1.000
CKMB 0.009 0.193 1.009 0.995 1.023
PO
2
−0.015 0.032 0.985 0.971 0.999
PCO
2
0.018 0.085 1.018 0.998 1.039
SO
2
−0.071 0.001 0.931 0.894 0.971
Lactate 0.478 0.000 1.613 1.251 2.080
Note: Bold and italic values are statistically significant.
Abbreviations: ALT, alanine transaminase; AST, aspartate transaminase;
CI, confidence interval; CK‐MB, creatinin kinase‐myocardial band; CRP,
C‐reactive protein; Hgb, hemoglobin; LDH, lactate dehydrogenase; LE,
lymphocyte; NE, neutrophil; NLR, neutrophil/lymphocyte ratio; Plt,
platelet; WBC, white blood cell.
TABLE 7 Results of multivariate analysis made with the model
created with significant variables in univariate analysis
BpExp(B) 95.0% CI
Step 1 AST 0.003 .000 1.003 1.002 1.005
Step 2 NLR 0.049 .000 1.050 1.032 1.070
AST 0.003 .000 1.003 1.002 1.005
Step 3 NLR 0.049 .000 1.050 1.031 1.070
AST 0.003 .000 1.003 1.002 1.005
Lactate 0.348 .030 1.416 1.035 1.938
Step 4 NLR 0.043 .000 1.044 1.022 1.067
CRP 0.004 .024 1.004 1.001 1.008
AST 0.003 .002 1.003 1.001 1.004
Lactate 0.373 .017 1.453 1.069 1.974
Reference range
WBC 4.5–10.5 × 10
9
/L
NE 1.5–6×10
9
/L
LE 1.32–3.57 × 10
9
/L
Plt 150–400 × 10
9
/L
HGB 13–17.5 g/dL
CRP >5 mg/L
PCT <0.12 μg/L
ALT 0–41 U/L
AST 0–40 U/L
Üre 17–43 mg/dL
Creatinine 0.72–1.18 mg/dL
LDH < 248 U/L
Ferritin 23–336 μg/L
D‐dimer 0–500 μg/L
Troponin I < 19.8 ng/L
CKMB 0.6–6.3 μg/L
PO
2
70–100 mmHg
PCO
2
35–46 mmHg
SO
2
95%–100%
Lactate 0–2 mmol/L
Note: Bold and italic values are statistically significant.
Abbreviations: ALT, alanine transaminase; AST, aspartate transaminase;
CI, confidence interval; CK‐MB, creatinin kinase‐myocardial band; CRP,
C‐reactive protein; Hgb, hemoglobin; LDH, lactate dehydrogenase; LE,
lymphocyte; NE, neutrophil; NLR, neutrophil/lymphocyte ratio; Plt,
platelet; WBC, white blood cell.
TAHTASAKAL ET AL.
|
9

severity of the disease and being over 5.86 suggests that the disease
could progress severely.
13
Contrary to that it was determined in our
study that there was no significant difference between the two
groups; but it was found out that NLR more than 3.69 might indicate
a poor prognosis and the AUC value, which was calculated based on
the optimal cut off point, was not significant in predicting the exitus.
Coagulopathy and embolic incidents in COVID‐19 worsen the
prognosis of the disease. Correlated with this, an increase occurs in the
levels of D‐dimer and numerous studies have revealed that D‐dimer
elevation is a considerable marker for determining critical disease at an
early stage.
7,15
Likewise, it has been determined in the previous studies
that the risk of acute myocardial infarction increased by 25 times in
patients with COVID‐19 and 50% of the patients who died had typically
an increase in their cardiac enzymes.
12
Many of the hemograms, acute
phase reactants and biochemical tests, which are performed routinely,
have been used to determine mortality or severity.
16,17
Based on the
results of the study, which was carried out by Wang et al.,
18
an increase
in the levels of Troponin I, CRP, IL‐6, PCT, neutrophils, and a decrease in
the level of lymphocytes points out to severe disease status. Based on
the results of our study, since the increased baseline levels of WBC, NE,
CRP, ALT, AST, urea, creatinine, LDH, ferritin, D‐dimer, cardiac enzymes,
high lactate, and the decreased baseline level of lymphocyte occur in the
presence of a severe clinical manifestation; thus it is considered that they
can be used as markers of poor prognosis. Based on the ROC analysis,
thefactthatthecutoffvaluesareabovefortheWBC(>7.79×10
9
/L),
NE ( > 4.99 × 10
9
/L), CRP (>46mg/L), AST (>40U/L), urea (>24mg/
dL), creatinine (> 0.76 mg/dL), LDH ( > 325 U/L), ferritin ( > 303 μg/L), D‐
dimer ( > 574 μg/L), troponin I ( > 5.3 μg/L), CK‐MB ( > 1.4 µg/L), LE
(≤1.04 × 10
9
/L), and below for the SO
2
, indicate a poor prognosis. To
estimate the severity of the disease, ROC analysis revealed that the AUC
values of neutrophil to lymphocyte ratio(NLR),CRP,troponinI,LDH,
ferritin, D‐dimer, NE, LE, and SO
2
were 0.762, 0.757, 0.742, 0.705, 0.698,
0.694, 0.688, 0.678, and 0.66, respectively (Table 4).
Previous studies have revealed that increased levels of D‐dimer,
troponin, and IL‐6 are associated with higher mortality risk.
19
The
fact that the values of C‐reactive protein, AST, troponin I, and
D‐dimer was higher in the exitus group compared with the survivors
suggest that it could be used as a marker in predicting mortality. The
multivariate analysis performed on all patients supports this finding.
According to the multivariate analysis, an increase of 0.043, 0.004,
0.003, and 0.373 in NLR, CRP, AST, and lactate values causes a
1.044, 1.004, 1.003, and 1.453‐fold increase in mortality.
It was found out that mortality could be predicted with cut‐off
values of procalcitonin more than 0.21 μg/L, urea more than 40 mg/
dL, troponin more than 7.4 μg/L, CK‐MB more than 2.6 μg/L, and SO
2
less than 89 in the group of severely ill patients. To predict mortality,
the ROC curve AUC values for troponin I, age, SO
2
, PCT, and CK‐MB
were 0.715, 0.685, 0.644, 0.632, 0.627, and 0.617, respectively.
Based on this finding, it was found out that the values of NLR and
CRP were the most effective data in predicting the poor prognosis
while troponin I was the most effective data in predicting mortality
(Table 5). Given the results of these examinations, it can be
considered that mortality, which is linked to multiorgan dysfunctions
and cardiac complications, are common.
4.1 |Limitations
Our study has any limitations. First, it was evaluated according to the
initial clinical and examinations. Factors that may affect prognosis
during hospitalization were not taken into consideration and it was
single center and retrospectively study.
5|CONCLUSION
It was found out in our study that apart from the age, gender, co-
morbidity, and received medication, the prognosis of the patients
could be predicted by certain tests. The clinical progress could be
predicted to be severe, if the baseline values of NLR, CRP, troponin I,
LDH, D‐dimer, ferritin, and NE are above the specified cut‐off point
and if the value of the lymphocyte is below the cut‐off point. It was
determined that the values of troponin I, SO
2
, and elder age could be
used to predict mortality in severity patient groups. On the other
hand, it may show how many times the mortality will increase with
the increase in NLR, AST, lactate, and CRP values in all patients.
Thanks to this, it will enable early treatment and close follow‐up
opportunities at the onset of the disease by predicting prognosis.
The prognostic factors in our study still need to be further va-
lidated by future studies. They should be helpful to provide scores or
biochemical markers for predicting severity and mortality in
COVID‐19, which is very useful for clinical application.
AUTHOR CONTRIBUTIONS
The authors confirm contribution to the paper as follows: Study
conception and design: Ceren A. Tahtasakal, Ahsen Oncul. Data col-
lection: Emine Celik, HakkıMeric Turkkan, and Murat Ocal. Analysis
and interpretation of results: Ceren A. Tahtasakal, Ahsen Oncul, and
Dilek Y. Sevgi. Draft manuscript preparation: Ceren A. Tahtasakal,
Ahsen Oncul, Dilek Y. Sevgi, and Banu Bayraktar. All authors re-
viewed the results and approved the final version of the manuscript
CONFLICTS OF INTEREST
The authors declare that there are no conflicts of interest that could
be perceived as prejudicing the impartiality of the research reported.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from
the corresponding author upon reasonable request.
ETHICAL APPROVAL
Approval of the Sisli Hamidiye Etfal Training and Research Hospital
ethics committee was obtained on April 22, 2020, with the decision
number of 2731/1481.
10
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TAHTASAKAL ET AL.

ORCID
Ceren A. Tahtasakal https://orcid.org/0000-0003-0392-229X
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How to cite this article: Tahtasakal CA, Oncul A, Sevgi DY,
et al. Could we predict the prognosis of the COVID‐19 disease?
JMedVirol. 2020;1–11. https://doi.org/10.1002/jmv.26751
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