Iglesias JI, Vassallo AV, Sullivan JB, Elbaga Y, Patel VV, Patel N, Ayad L, Benson P, Pittiglio M, Gobran E, Clark A, Khan W, Damalas K, Mohan R, Singh SP. Retrospective analysis of anti-inflammatory therapies during the first wave of COVID-19 at a community hospital. World J Crit Care Med 2021; 10(5): 244-259 [PMID: 34616660 DOI: 10.5492/wjccm.v10.i5.244]
Corresponding Author of This Article
Jose I Iglesias, DO, Associate Professor, Department of Critical Care, Community Medical Center, 99 W Rt 37, Toms River, NJ 08757, United States. jiglesias23@gmail.com
Research Domain of This Article
Critical Care Medicine
Article-Type of This Article
Observational Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Table 3 Univariate Cox proportional hazards survival analysis of pharmacological and therapeutic interventions in coronavirus disease 2019 intensive care unit patients
B
SE
P value
HR
95%CI
GC (all patients)
-0.84
0.16
< 0.001
0.45
0.38-0.61
Vasopressors
0.039
35
0.027
1.4
1.05-2.1
IV ascorbic acid
0.1
0.15
0.49
1.1
0.91-1.5
Hydroxychloroquine
-0.58
0.36
0.1
0.56
0.27-1.14
Azithromycin
0.25
28
0.39
1.3
0.72-2.3
Heparin therapeutic dose
0.15
0.35
0.67
1.16
0.51-2.31
Heparin prophylaxis dose
-0.27
0.3
0.35
0.76
0.48-1.3
Convalescent plasma
0.29
1
0.77
1.3
0.72-9.8
Remdesivir
6 (3)
0
Prone positioning
0.36
0.52
0.44
1.43
0.51-1.4
Tocilizumab
-0.48
0.27
0.08
0.61
0.36-1.06
GC only
-0.75
0.21
0.001
0.47
0.18-0.41
GC + tocilizumab
-1.3
0.21
<0.001
0.27
0.4-1.15
Table 4 Inflammatory markers in coronavirus disease 2019 survivors and non-survivors
Non-survivors (n = 167)
Survivors (n = 94)
P value
IL-6 day 1 (pg/mL)
112 (70, 137)
100 (70, 135)
0.34
IL-6 day 2
415 (139, 476)
350 (78, 423)
0.016
D-dimer day 1 (ng/mL)
1125 (647, 2434)
991 (513, 2196)
0.04
D-dimer day 2
849 (604, 1210)
1140 (646, 2263)
0.03
CRP day 1 (mg/L)
117 (89, 159)
113 (96, 149)
0.9
CRP day 2
107 (81, 154)
117 (88, 167)
0.62
Ferritin day 1 (ng/mL)
931 (593, 1367)
960 (609, 1395)
0.51
Ferritin day 2
822 (447, 1432)
1053 (712, 2057)
0.05
Table 5 Unadjusted Cox proportional hazards analysis of independent predictors of survival in intensive care unit patients with coronavirus disease 2019
Table 6 Propensity score adjusted Cox proportional hazards analysis of independent predictors of survival in intensive care unit patients with coronavirus disease 2019
B
SE
P value
HR
95%CI
Age
0.03
0.007
< 0.001
1.031
1.02-1.05
Sex (male)
0.41
0.2
0.038
1.51
1.022-2.22
Vasopressors
0.47
0.23
0.019
1.6
1.081-2.37
GC + Tocilizumab
-0.78
0.22
0.001
0.46
0.29-0.72
GC only
-0.44
0.22
0.048
0.65
0.42-0.99
Table 7 Propensity score adjusted (glucocorticoids as a time-adjusted covariate) Cox proportional hazards analysis of independent predictors of survival in intensive care unit patients with coronavirus disease 2019
Table 8 Propensity score adjusted (glucocorticoids as a time adjusted covariate) Cox proportional hazards analysis of independent predictors of survival in intensive care unit patients with all treatment groups added into the model
B
SE
P value
HR
95%CI
Time adjusted GC
2.5
1.01
0.015
12
1.62-85
Age
0.03
0.007
< 0.001
1.03
1.01-1.04
Sex (male)
0.4
0.2
0.04
1.5
1.01-2.2
Vasopressors
0.5
0.2
0.01
1.66
1.12-2.45
GC + tocilizumab
-3.07
1.02
0.003
0.046
0.006-0.46
GC (only)
-2.77
1.02
0.007
0.06
0.008-0.46
Citation: Iglesias JI, Vassallo AV, Sullivan JB, Elbaga Y, Patel VV, Patel N, Ayad L, Benson P, Pittiglio M, Gobran E, Clark A, Khan W, Damalas K, Mohan R, Singh SP. Retrospective analysis of anti-inflammatory therapies during the first wave of COVID-19 at a community hospital. World J Crit Care Med 2021; 10(5): 244-259