Interdisciplinary Perspectives on Infectious Diseases
Volume 2021 (2021), Article ID 6650469, 12 pages
https://doi.org/10.1155/2021/6650469

Review Article

Severity and Mortality Associated with Steroid Use among Patients with COVID-19: A Systematic Review and Meta-Analysis

Tamiru Sahilu,¹ Tadesse Sheleme,² and Tsegaye Melaku³

¹Department of Pharmacy, College of Health Science, Assosa University, Assosa, Ethiopia
²Department of Pharmacy, College of Health Science, Mettu University, Mettu, Ethiopia
³Department of Clinical Pharmacy, School of Pharmacy, Institute of Health, Jimma University, Jimma, Ethiopia

Correspondence should be addressed to Tadesse Sheleme; tadesse.sheleme@meu.edu.et

Received 23 December 2020; Revised 25 March 2021; Accepted 17 April 2021; Published 6 May 2021

Academic Editor: Massimiliano Lanzafame

Copyright © 2021 Tamiru Sahilu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Background. There are controversial suggestions about steroid use to treat patients infected with COVID-19. Conclusive evidence regarding the use of steroids to treat COVID-19 is still lacking. This meta-analysis aimed to determine the mortality and severity associated with corticosteroid therapy compared to noncorticosteroid treatment in patients with COVID-19. Methods. The information was collected from electronic databases: PubMed, CINAHL, the Cochrane Library, clinicaltrials.gov, and Google scholar through January 30, 2021. Risk ratios (RRs) with 95% confidence intervals (CIs) were performed using random effect models. Endnote citation manager software version X9 for Windows was utilized to collect and organize search outcomes (into relevant and irrelevant studies) and to remove duplicate articles. Results. Thirty-two studies were included in the meta-analysis, including 14,659 COVID-19 patients. No significant differences in mortality between the steroid and nonsteroid treatment groups (RR = 0.95; 95% CI: 0.80–1.13;  = 0.57). There was no significant reduction in mortality in critically ill COVID-19 patients treated with corticosteroid (RR = 0.89; 95% CI: 0.62–1.27;  = 0.52). Significant differences were observed in severe disease conditions between the steroid and nonsteroid treatment groups (RR = 1.10; 95% CI, 1.03–1.19,  = 0.007). Conclusion. There was no significant difference in all-cause mortality between the steroid and nonsteroid treatment users’ of COVID-19 patients. There was no significant reduction of all-cause mortality in critically ill COVID-19 patients treated with corticosteroids.

1. Background

Coronavirus disease-19 (COVID-19) was first identified at the end of 2019 in Wuhan City, China. It rapidly spread in China and other countries throughout the world [1, 2]. In March 2020, the World Health Organization characterized the disease as pandemic [3]. As of May 21, 2020, more than five million confirmed cases have been documented and several death cases reported globally. It is affecting 213 countries and territories around the world and 2 international conveyances [4]. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is identified as the cause of COVID-19 [5].

Currently, there is no drug confirmed by clinical trial to prevent or treat COVID-19. However, more than 300 active clinical treatment trials are under investigation [6]. Drugs that are already marketed for other conditions are being off-label used. For example, antimalarial medications chloroquine and hydroxychloroquine are widely used to treat COVID-19 [7]. A multinational registry analysis debunked the benefit of hydroxychloroquine or chloroquine when used alone or with a macrolide. The finding of the study showed that each of these regimens was associated with decreased in-hospital survival and an increased frequency of ventricular arrhythmias when used for the treatment of COVID-19 [8]. Remdesivir is another drug being used as a promising option for treating COVID-19 based on laboratory experiments [9].

Corticosteroids were widely used to treat severe acute respiratory syndrome coronavirus-1(SARS-CoV-1) and Middle East respiratory syndrome coronavirus (MERS) during their outbreaks and are being used in patients with COVID-2019 [10]. Up to 70% of critically ill patients are receiving systemic corticosteroids. It is identified that patients treated with a corticosteroid had more clinical symptoms, a higher inflammation index, and more abnormalities on chest computed tomography [11]. A study showed that the use of high-dose corticosteroids increases the risk of death in patients with severe COVID-19 [12], indicating several controversial issues about the use of the steroid to treat patients infected with COVID-19. It is suggested that available evidence does not endorse the use of a steroid for COVID-19 patients, which may cause several side effects [13]. However, it is believed that short-term glucocorticoid therapy with small- or medium-dose could be beneficial for patients with severe conditions [14]. According to the World Health Organization (WHO) guidelines recommendation, glucocorticoids should only be used under clinical trial conditions [15]. Conclusive evidence regarding the use of the steroid to treat COVID-19 is still lacking. Therefore, this study aims to summarize the current evidence of the severity and mortality associated with steroid therapy for patients with COVID-19 which will support us in making the best decision in the management of the COVID-19.

2. Methods

2.1. Study Design

Analyses were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [16]. This study was registered in PROSPERO with registration number CRD42020185773.

2.2. Search Strategy

The information was collected from electronic databases: PubMed, CINAHL, the Cochrane Library, clinicaltrial.gov, and Google scholar. There was no limitation applied to the language. The reference list of all identified articles was searched for additional studies. Then, an extensive list of search terms was prepared by the analysis of title, abstract, and keywords of retrieved articles. A full-scale search of databases in PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, clinicaltrial.gov, and Google scholar from inception to January 30, 2021, was performed. No language restriction was imposed during the identification of studies. Flow diagram was used to summarize the number of studies identified, screened, excluded, and finally included in the study.

The search terms used were ((“covid 19” [All Fields] OR “covid 19” [MeSH Terms] OR “covid 19 vaccines” [All Fields] OR “covid 19 vaccines” [MeSH Terms] OR “covid 19 serotherapy” [All Fields] OR “covid 19 serotherapy” [Supplementary Concept] OR “covid 19 nucleic acid testing” [All Fields] OR “covid 19 nucleic acid testing” [MeSH Terms] OR “covid 19 serological testing” [All Fields] OR “covid 19 serological testing” [MeSH Terms] OR “covid 19 testing” [All Fields] OR “covid 19 testing” [MeSH Terms] OR “sars cov 2” [All Fields] OR “sars cov 2” [MeSH Terms] OR “severe acute respiratory syndrome coronavirus 2” [All Fields] OR “ncov” [All Fields] OR “2019 ncov” [All Fields] OR ((“coronavirus” [MeSH Terms] OR “coronavirus” [All Fields] OR “cov” [All Fields]) AND steroidal” [All Fields] OR “steroidals” [All Fields] OR “steroidic” [All Fields] OR “steroids” [MeSH Terms] OR “steroids” [All Fields] OR “steroid” [All Fields]) AND (“mortality” [MeSH Terms] OR “mortality” [All Fields] OR “mortalities” [All Fields] OR “mortality” [MeSH Subheading]) AND (“cohort studies” [MeSH Terms] OR (“cohort” [All Fields] AND “studies” [All Fields]) OR “cohort studies” [All Fields] OR (“cohort” [All Fields] AND “study” [All Fields]) OR “cohort study” [All Fields])) NOT (“review” [Publication Type] OR “review literature as topic” [MeSH Terms] OR “review” [All Fields]).

2.3. Study Selection

Two reviewers independently carried out a literature search and examined relevant studies and sequentially screened their titles and abstracts for eligibility. The full texts of potentially eligible studies were retrieved. Disagreements were solved in a discussion. A screening guide was used to ensure that all review authors reliably apply the selection criteria.

2.4. Inclusion and Exclusion Criteria

Randomized controlled trials (RCTs), observational studies, prospective and retrospective comparative cohort studies, and case-control studies were eligible for the review. The review considered all articles comparing corticosteroid with noncorticosteroid treatment for patients with the diagnosis of COVID-19. Nonhuman studies and studies that did not report mortality and severity data were excluded from the review. The outcome considered was mortality, death within the hospital (all-cause mortality) of COVID 19 patients. The other outcome studied was the number of severe cases in the two groups (corticosteroid versus noncorticosteroid treatment groups).

2.5. Methodological Quality Assessment

Selected papers were assessed by two independent reviewers for methodological validity before inclusion in the review. Observational studies were assessed using Newcastle–Ottawa Scale (NOS), which consists of three domains: (1) subject selection, (2) comparability of the study groups, and (3) assessment of outcome(s). A score of 0–9 was allocated to each study. A standardized Cochrane risk of bias tool was used for the randomized controlled trial (RCT). Any disagreements that arise between the reviewers were resolved through discussion.

2.6. Data Extraction

Two reviewers independently extracted data from the studies using a predesigned format prepared. Data that were extracted include first author, a region of study, included population, study design, sample size, comparator group, patient status, age, gender, interventions, mortality, and severity. Severe cases were characterized as patients admitted to ICU or on invasive mechanical ventilation.

2.7. Data Analysis and Statistical Methods

To perform a meta-analysis, Review Manager 5.4 (Copenhagen: The Cochrane Collaboration, 2014) was used. The outcome variables were calculated using the Mantel Haenszel formula. Risk ratios (RRs) were reported with 95% confidence intervals (CIs) for the variables. The value was two-tailed, and the statistical significance was set at ≤0.05. Heterogeneity was assessed with the Q-statistic test and the I² test. The I² statistic measured the percentage of total variation across the studies due to clinical or methodological heterogeneity instead of chance. The significant Q statistics ( < 0.05) indicated heterogeneity across the studies; thus, a random effect model was utilized. Substantial heterogeneity was represented by I² for >50%.

3. Results and Discussion

The search returned a total of 1419 (PubMed: 85, Google Scholar: 1290, clinicaltrials.gov: 24, Cochrane Library: 1, and other sources: 19) citations, of which 40 were duplicates. According to the exclusion criteria, 1292 citations were excluded after the title and abstract screening. Figure 1 shows the study selection processes.

Figure 1: PRISMA study flow diagram.

3.1. Characteristics of the Included Studies

The present meta-analysis included 28 observational studies [12, 17–43] and 4 RCTs [44–47]. These studies included 14,659 patients with the diagnosis of COVID-19 who received corticosteroids (5,830 patients) or noncorticosteroids (8,829 patients). Tables 1 and 2 list the characteristics of the included studies. All eligible studies were published in 2020/21. Individual assessment of the risk of bias was presented in Table 3.

Table 1: Characteristics of included studies.

S.No
Authors
Study type
Sample size
Number of control
Patient status
Country
Follow-up period

1
Wang et al. [19]
Retrospective study
46
20
COVID-19 with pneumonia
Wuhan Union Hospital, China
January 20 to February 25, 2020

2
Fadel et al. [17]
Multicenter quasi-experimental study
213
81
COVID-19
Five hospitals in Michigan, USA
March 12, 2020 through March 27, 2020

3
Wu et al. [21]
Retrospective cohort study
201
139
COVID-19 with pneumonia
Wuhan Jinyintan Hospital in China
December 25, 2019, to January 26, 2020

4
Li et al. [12]
Ambispective cohort study
548
207
COVID-19
Tongji Hospital, China
January 26, to March 3, 2020.

5
Zhou et al. [23]
Multicenter, retrospective cohort study
191
134
COVID-19
Wuhan, China
Dec 29, 2019, to Jan 31, 2020

6
Shang et al. [18]
Multicenter, retrospective, observational study
416
220
COVID-19
Hubei province, China
Dec 27, 2019, to Feb 17, 2020

7
Yang et al. [22]
Retrospective observational study
52
22
SARS-CoV-2 pneumonia
Wuhan, China
December, 2019, to Jan 26, 2020

8
Huang et al. [24]
Prospective cohort study
41
32
COVID-19
Wuhan, China
Dec 16, 2019, to Jan 2, 2020

9
Guan et al. [27]
Retrospective cohort study
1099
895
COVID-19
China
December 11, 2019, to January 31, 2020.

10
Zhao et al. [26]
Retrospective cohort study
91
12
COVID-19
Jingzhou Central Hospital, China
January 16, 2020, to February 10, 2020.

11
Ling et al. [25]
Retrospective cohort study
66
61
COVID-19
Shanghai, China
January 20, to February 10, 2020

12
Horby et al. [44]
Randomized controlled trial
6425
4321
COVID-19
United Kingdom
March 9, to June 8, 2020

13
Angus et al. [45]
Randomized controlled trial
384
101
COVID-19
REMAP-CAP multicenter (Australia, Canada, France, Ireland, The Netherlands, New Zealand, the United Kingdom, and the United States)
March 9 to August 12, 2020

14
Borie et al. [28]
Cohort study
171
63
COVID-19
Paris
March 27 to April 10, 2020

15
Dequin et al. [46]
Randomized controlled trial
149
73
Critically Ill patients with COVID-19
France
March 7 to June 29, 2020

16
Falcone et al. [43]
Prospective observational study
315
174
COVID-19 and pneumonia
University Hospital of Pisa
March 4–April 30, 2020

17
Fernández-Cruz et al. [29]
Retrospective controlled cohort study
463
67
COVID-19 and pneumonia
Spain
4 March 2020 to 7 April 2020

18
Jeronimo et al. [47]
Randomized controlled trial
393
199
COVID-19
Brazil
18 April to 16 June 2020

19
Krishnan et al. [30]
Retrospective observational study
152
136
COVID-19 and pneumonia
USA
March 10, to April 15, 2020

20
Li et al. 2020 [31]
Multicenter, retrospective study
294
111
Critically ill COVID-19 patients
Hubei, China
Between December 30, 2019 and February 19, 2020

21
Papamanoli et al. [32]
Retrospective cohort
447
294
severe COVID-19 pneumonia
New York, USA
1 March to 15 April 2020

22
Tomazini et al. [48]
Randomized controlled trial
299
148
Acute respiratory distress syndrome and COVID-19
Brazil
April 17 to July 21, 2020

23
You et al. [33]
Retrospective cohort study
343
225
COVID-19
China
February 1 to March 31, 2020

24
Rodríguez-Baño et al. [34]
Retrospective cohort study
778
583
COVID-19
Spain
February 2 to March 31, 2020

25
Ma et al. [35]
Multicenter retrospective cohort study
72
25
COVID-19
China
January 2020 to March 2020

26
Lu et al. [36]
Retrospective cohort study
62
31
Critically ill COVID-19
China
January 25 to February 25, 2020

27
Cao et al. [37]
Retrospective cohort study
102
51
COVID-19
China
January 3 and February 1, 2020

28
Nelson et al. [38]
Retrospective cohort study
117
69
COVID-19 pneumonia
USA
March 1, 2020 and April 12, 2020

29
Bani-Sadr et al. [39]
Prospective cohort study
257
85
COVID-19 pneumonia
France
3 March 2020 and 14 April 2020

30
Salton et al. [40]
Multicenter observational study
173
90
severe COVID-19 pneumonia
Italy
February 27 to May 21, 2020

31
Mikulska et al. [41]
Observational single-center study
196
66
COVID-19 pneumonia
Italy
NR

32
Majmundar et al. [42]
Retrospective cohort study
205
145
COVID-19 pneumonia
USA
March 15 to April 30, 2020

Table 2: Characteristics of included studies.

S. No
Authors
Median age (IQR) in years
Gender
Intervention
No. of patients

Mortality
Severe cases

Control group
Intervention group
Control group
Intervention group

1
Wang et al. [19]
54 (48–64)
26 (57%) males
Methylprednisolone (n = 26)
1
2
NR
NR

2
Fadel et al. [17]
62 (51–62)
109 (51.2%) male
Methylprednisolone (n = 132)
21
18
21
27

3
Wu et al. [21]
51 (43–60)
128 (63.7%) men
Methylprednisolone (n = 62)
21
23
NR
NR

4
Li et al. [12]
60 (48–69)
279 (50.9%) male
Systemic corticosteroids (n = 341)
NR
NR
73
196

5
Zhou et al. [23]
56 (46–67)
Male 119 (62%)
Corticosteroids (n = 57)
28
26
NR
NR

6
Shang et al. [18]
49 (36–61)
197 (47%) males
Corticosteroid therapy (n = 196)
8
43
62
77

7
Yang et al. [22]
59·7
35 (67%) males
Glucocorticoids (n = 30)
16
16
22
30

8
Huang et al. [24]
49 (41–58) years
30 [73%] males
Use of corticosteroid (n = 9)
NR
NR
7
6

9
Guan et al. [27]
47 years
639 males
Systemic glucocorticoids(n = 204)
10
5
96
77

10
Zhao et al. [26]
46 years
49 males
Glucocorticoid (n = 79)
1
1
5
25

11
Ling et al. [25]
44 (34–62) years
38 males
Glucocorticoid (n = 5)
0
0
NR
NR

12
Horby et al. [44]
66.1 years
4088 males
Dexamethasone (n = 2104)
1065
454
683
324

13
Angus et al. [45]
Mean age, 60 years
29% female
Hydrocortisone (n = 283)
33
78
101
283

14
Borie et al. [28]
Median (IQR): 67.1 (56.7–78.1)
Female 48 (28.1%)
Methyl-prednisolone (n = 108)
25
32
63
108

15
Dequin et al. [46]
Mean age, 62.2 years
30.2% women
Hydrocortisone (n = 76)
20
11
73
76

16
Falcone et al. [43]
Median age was 70 (IQR, 57–80)
(76.2%) males
Steroids (n = 141)
43
27
NR
NR

17
Fernández-Cruz et al. [29]
Mean age 66.75 years
317 males
Steroids (n = 396)
16
55
0
58

18
Jeronimo et al. [47]
Mean age (SD) 55 ± 15 yrs
139 females
Methylprednisolone (n = 194)
76
72
NR
NR

19
Krishnan et al. [30]
68 years (IQR 58–75)
95 males
Oral steroids n = 16
82
10
136
16

20
Li et al. [31]
66 yrs (56–75)
197 (67%) males
Corticosteroids, n = 183
49
97
111
183

21
Papamanoli et al. [32]
Mean age 61.5 yrs
Females 156
Methylprednisolone, n = 153
146
71
294
153

22
Tomazini et al. [48]
Mean age 61.4 yrs
Females 112
Dexamethasone (n = 151)
91
85
148
151

23
You et al. [33]
Mean age 53.8
Female 157
Methylprednisolone (n = 118)
1
14
9
58

24
Rodríguez-Baño et al. [34]
Age 71 yrs
Female 226
Corticosteroids (n = 195)
62
30
NR
NR

25
Ma et al. [35]
Age 60 (13.8) yrs
Female 32 (44%)
Corticosteroid group (n = 47)
2
2
25
47

26
Lu et al. [36]
57 (50–69) yrs
Male 32
Steroid (n = 31)
5
12
31
31

27
Cao et al. [37]
Age, years 54(37–67)
Female 49
Methylprednisolone Sodium (n = 51)
6
11
NR
NR

28
Nelson et al. [38]
Age 61.5 (46–69)
Male 80
Methylprednisolone n = 48
29
15
69
48

29
Bani-Sadr et al. [39]
Age 71 yrs
Male 135
Corticosteroids n = 172
17
31
12
9

30
Salton et al. [40]
Age 65.75 yrs
Male 120
Methylprednisolone (n = 83)
21
6
90
83

31
Mikulska et al. [41]
Age mean 67.5 yrs
Male 132
Methylprednisolone (n = 130)
22
14
NR
NR

32
Majmundar et al. [42]
Age, mean 57.61
Male 153
Corticosteroids (N = 60)
34
8
0
0

NR: not reported.

Table 3: Methodological quality assessment.

Newcastle–Ottawa scale (NOS)

Studies
Selection
Comparability
Outcome
Quality score

A
B
c
d
e
f
g
h

Fadel et al. [17]

8

Guan et al. [27]

9

Huang et al. [24]

8

Li et al. [12]

6

Ling et al. [25]

6

Shang et al. [18]

6

Yang et al. [22]

6

Wang et al. [19]

6

Wu et al. [21]

7

Zhao et al. [26]

6

Zhou et al. [23]

7

Borie et al. [28]

6

Falcone et al. [43]

7

Fernández-Cruz et al. [29]

7

Krishnan et al. [30]

6

Li et al. [31]

6

Papamanoli et al. [32]

7

You et al. [33]

6

Rodríguez-Baño et al. [34]

7

Ma, Q et al. [35]

7

Lu et al. [36]

7

Cao et al. [37]

6

Nelson et al. [38]

7

Bani-Sadr et al. [39]

6

Salton et al. [40]

7

Mikulska et al. [41]

6

Majmundar et al. [42]

7

Cochrane risk of bias tool

I
J
k
l
m
n

Horby et al. [44]
Low risk of bias
Low risk of bias
High risk of bias
Unclear risk of bias
Low risk of bias
Low risk of bias

Angus et al. [45]
Low risk of bias
Low risk of bias
High risk of bias
Low risk of bias
Low risk of bias
Low risk of bias

Dequin et al. [46]
Low risk of bias
High risk of bias
High risk of bias
Low risk of bias
Low risk of bias
Low risk of bias

Jeronimo et al. [47]
Low risk of bias
Low risk of bias
High risk of bias
Low risk of bias
Low risk of bias
Low risk of bias

a: representativeness of the exposed cohort, b: selection of the nonexposed cohort, c: ascertainment of exposure, d: demonstration that the outcome of interest was not present at the start of the study, e: comparability of cohorts based on the design or analysis, f: assessment of outcome, g: follow-up long enough for outcomes to occur, h: adequacy of follow-up of the cohort; i: random sequence generation (selection bias), j: allocation concealment (selection bias), k: blinding of participants and personnel (performance bias), l: blinding of outcome assessment (detection bias), m: incomplete outcome data (attrition bias), n: selective reporting (reporting bias).

3.2. Mortality Associated with Steroid Use in Patients with COVID-19

In the 26 included studies [17–19, 21–23, 25–30, 32–35, 37–42, 44, 45, 47, 48] with 13,565 patients, there were no significant differences in mortality between the steroid and nonsteroid treatment groups (RR = 0.95; 95% CI: 0.80–1.13;  = 0.57, I² = 78%,  < 0.0001) (Figure 2). The sensitivity analysis showed that the exclusion of three studies [18, 21, 33] changed the above conclusion.

Figure 2: Forest plot for mortality of COVID-19 patients taking steroids versus nonsteroids.

3.3. Mortality Associated with Steroid Use in Patients with Critically Ill COVID-19 Patients

In the 5 included studies [22, 31, 36, 44, 46] with 1,564 critically ill COVID-19 patients, there were no significant differences in mortality between the steroid and nonsteroid treatment groups (RR = 0.89; 95% CI: 0.62–1.27;  = 0.52, I² = 78%,  = 0.001) (Figure 3).

Figure 3: Forest plot for mortality associated with steroid use in patients with critically ill COVID-19 patients.

3.4. Severity Associated with Steroid Use in Patients with COVID-19

Twenty-three studies reported the severity data of the COVID-19 patients. In the included studies [12, 17, 18, 22, 24, 26–33, 35, 36, 38–40, 42, 44–46, 48] with 12,473 patients, there were significant differences in severe disease condition between the steroid and nonsteroid treatment groups (RR = 1.10; 95% CI, 1.03–1.19,  = 0.007) (Figure 4). There was significant heterogeneity among the studies (I² = 99%  < 0.001); the random-effects model was used.

Figure 4: Forest plot for severe events of COVID-19 patients taking steroids versus nonsteroids.

3.5. Publication Bias

To assess the small-study effect and publication bias, the regression-based Egger’s test was performed. The funnel-plot analysis showed a symmetrical shape for mortality (Figure 5), indicating no publication bias; Egger’s test indicated nonsignificant small-study effects ( = 0.570). The funnel-plot analysis showed asymmetrical shape for severe cases (Figure 6), indicating publication bias; Egger’s test indicated significant small-study effects for severe cases ( = 0.027).

Figure 5: Funnel plot for mortality.

Figure 6: Funnel plot for severe cases.

3.6. Sensitivity Analysis

Sensitivity analysis for between-study heterogeneity and analytical methods was performed to show the robustness of the finding. The analysis showed that the result was stable except for the exclusion of three studies [18, 21, 33] that changed the conclusion (Figure 7).

Figure 7: Sensitivity analysis: forest plot for mortality of COVID-19 patients taking steroids versus nonsteroids.

The rationale for the use of corticosteroids is to decrease the host inflammatory responses in the lungs, which may lead to acute lung injury and acute respiratory distress syndrome [6]. Because of the high amount of cytokines induced by COVID-19 infection, corticosteroids were used frequently for the treatment of patients with severe illness, for possible benefit by reducing inflammatory-induced lung injury [24]. There were potential harms and a lack of proven benefit for corticosteroid cautions against their routine use in patients with COVID-19 [6].

Our analysis demonstrated that the mortality rate was comparable in COVID-19 patients treated with corticosteroids versus noncorticosteroids. However, in patients with critically ill COVID-19 patients, even though nonsignificant (RR = 0.89; 95% CI: 0.62–1.27;  = 0.52), a lower mortality rate in corticosteroid treatment groups was observed. Evidence suggests that cytokine storm, a hyperinflammatory state resembling secondary hemophagocytic lymphohistiocytosis (HLH), is a contributing factor in COVID-19-associated mortality [49].

In our finding, there were no significant differences in mortality between the corticosteroid and noncorticosteroid treatment groups in critically ill COVID-19 patients. The initial clinical trial results from the United Kingdom (UK) showed that dexamethasone, a corticosteroid, can be lifesaving for patients who are critically ill with COVID-19. For patients on ventilators, the treatment was shown to reduce mortality by about one-third, and for patients requiring only oxygen, mortality was cut by about one-fifth, according to preliminary findings shared with the World Health Organization (WHO) [50].

The most commonly invoked rationale for giving steroids in patients with severe COVID-19 is to modulate the destructive inflammatory immune response that occurs with advancing disease. The guidelines recommend against using corticosteroids to try to modulate the immune system in mechanically ventilated COVID-19 patients without acute respiratory distress syndrome (ARDS) but do recommend steroids in those with COVID-19 and ARDS [51]. Our finding demonstrates that there is an association between severe COVID-19 and corticosteroid therapy (RR = 1.10; 95% CI, 1.03–1.19,  = 0.007).

A previous meta-analysis in persons with SARS-CoV-2, SARS-CoV, or MERS-CoV (Middle East respiratory syndrome coronavirus) infection indicated that corticosteroid did not significantly reduce the risk of death [52]. Another meta-analysis that included 5 studies indicated a lack of benefit of corticosteroid therapy on mortality in critically ill patients with COVID-19 [53]. In addition, a review that included 15 studies with coronavirus-infected patients (2 studies with COVID-19 patients) showed that corticosteroid treatment was associated with higher mortality and critical patients were more likely to require corticosteroids therapy [54].

Some of the limitations of this meta-analysis are as follows: the included studies are retrospective cohort studies, there is a high degree of between-study heterogeneity, and mortality may be influenced by other therapeutic options.

4. Conclusion

No significant differences in mortality between the corticosteroid and noncorticosteroid treatment groups were observed. There was no significant reduction in mortality in critically ill COVID-19 patients treated with corticosteroids. More randomized clinical trials are needed to further verify this conclusion.

Abbreviations

ARDS: | Acute respiratory distress syndrome
CI: | Confidence interval
HLH: | Hemophagocytic lymphohistiocytosis
ICU: | Intensive care unit
MERS-CoV: | Middle east respiratory syndrome coronavirus
NOS: | Newcastle–Ottawa scale
PRISMA: | Preferred reporting items for systematic reviews and meta-analyses
RCT: | Randomized controlled trial
RR: | Risk ratio
SARS-CoV-2: | Severe acute respiratory syndrome coronavirus 2
UK: | United Kingdom
WHO: | World Health Organization.

Data Availability

The data presented are properly cited and can be obtained from already published original research articles, which are available on electronic databases.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

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