Evaluation of Zinc Sulfate as an Adjunctive Therapy in COVID-19 Critically ill Patients

A Two Center Propensity-Score Matched Study

Khalid Al Sulaiman; Ohoud Aljuhani; Abdulrahman I. Al Shaya; Abdullah Kharbosh; Raed Kensara; Alhomaidi Al Guwairy; Aisha Alharbi; Rahmah Algarni; Shmeylan Al Harbi; Ramesh Vishwakarma; Ghazwa B. Korayem

Disclosures

Crit Care. 2021;25(363)

Abstract and Introduction

Abstract

Background: Zinc is a trace element that plays a role in stimulating innate and acquired immunity. The role of zinc in critically ill patients with COVID-19 remains unclear. This study aims to evaluate the efficacy and safety of zinc sulfate as adjunctive therapy in critically ill patients with COVID-19.

Methods: Patients aged ≥ 18 years with COVID-19 who were admitted to the intensive care unit (ICU) in two tertiary hospitals in Saudi Arabia were retrospectively assessed for zinc use from March 1, 2020 until March 31, 2021. After propensity score matching (1:1 ratio) based on the selected criteria, we assessed the association of zinc used as adjunctive therapy with the 30-day mortality. Secondary outcomes included the in-hospital mortality, ventilator free days, ICU length of stay (LOS), hospital LOS, and complication (s) during ICU stay.

Results: A total of 164 patients were included, 82 patients received zinc. Patients who received zinc sulfate as adjunctive therapy have a lower 30-day mortality (HR 0.52, CI 0.29, 0.92; p = 0.03). On the other hand, the in-hospital mortality was not statistically significant between the two groups (HR 0.64, CI 0.37–1.10; p = 0.11). Zinc sulfate use was associated with a lower odds of acute kidney injury development during ICU stay (OR 0.46 CI 0.19–1.06; p = 0.07); however, it did not reach statistical significance.

Conclusion: The use of zinc sulfate as an additional treatment in critically ill COVID-19 patients may improve survival. Furthermore, zinc supplementation may have a protective effect on the kidneys.

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Crit Care. 2021;25(363) © 2021 BioMed Central, Ltd.
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Abstract and Introduction
Background
Methods
Results
Discussion
Conclusion
References

Table 1. Regression analysis for the outcomes after PS matching
	Outcomes			Hazard ratio (HR) (95%CI)	P-value$
	Control	Zinc	P-value^^	Hazard ratio (HR) (95%CI)	P-value$
In-hospital mortality, n (%)^§	32 (40.0)	23 (28.4)	0.12	0.64 (0.37, 1.10)	0.11
30-day mortality, n (%)^§	31 (38.8)	19 (23.2)	0.03	0.52 (0.29, 0.92)	0.03
			P-value^	beta coefficient (estimates) (95%CI)	P-value$*
Ventilator free days, Median (Q1, Q3)^§	0.0 (0.00, 26.00)	20.0 (0.00, 28.00)	0.02	0.33 (− 0.21, 0.87)	0.22
ICU Length of Stay (Days), Median (Q1, Q3)^&	8.0 (5.00, 15.00)	10.0 (6.00, 15.00)	0.28	0.10 (− 0.16, 0.36)	0.46
Hospital Length of Stay (Days), Median (Q1, Q3)^&	16.0 (10.00, 28.00)	17.0 (12.00, 29.00)	0.61	0.03 (− 0.21, 0.27)	0.79

^§Denominator of the percentage is the total number of patients
^&Denominator is patients who survived
^^Chi-square test is used to calculate the P-value
^Wilcoxon rank sum test is used to calculate the P-value
^$Cox proportional hazards regression analysis is used to calculate hazard ratio (HR) and p-value
^$*Generalized linear model is used to calculate beta coefficient (estimates) and p-value

Table 2. Regression analysis for ICU complication (s) after PS matching
Outcomes	Crude analysis		P-value^^	Odds Ratio (OR) (95%CI)	P-value*^
Outcomes	Control	Zinc	P-value^^	Odds Ratio (OR) (95%CI)	P-value*^
Acute kidney injury, n (%)^§	25 ( 31.3)	10 ( 15.4)	0.02^^	0.46 (0.19, 1.06)	0.07
Liver injury, n (%)^§	7 ( 8.8)	2 ( 2.5)	0.08**	0.24 (0.05, 1.26)	0.09
Thrombosis/infraction, n (%)^§	7 ( 8.8)	3 ( 3.8)	0.19**	0.46 (0.11, 1.98)	0.29
Respiratory failure requiring MV, n (%)^$*	9/26 (34.6)	9/27 (33.3)	0.92^^	0.98 (0.31, 3.14)	0.98

^§After zinc initiation
^$*Denominator of the percentage is non-mechanically ventilated patients with 24 h of ICU admission
^^Chi-square/**Fisher Exact test is used to calculate the P-value
*^Multivariable logistic regression analysis is used to calculate Odds ratio and p-value

Table 3. COVID-19 Inflammatory surrogate markers: peak levels follow-up
	Surrogate markers*		P-value^	Beta coefficient (estimates) (95%CI)	P-value$*
	Control	Zinc	P-value^	Beta coefficient (estimates) (95%CI)	P-value$*
Ferritin level (ug/l), Median (Q1, Q3)^§	891.9 (350.0, 2476.0)	941.1 (511.0, 2344.0)	0.69	0.21 (− 0.18, 0.60)	0.29
D-dimer level (mg/l), Mean (SD)^§	15.0 (36.8)	6.7 (9.2)	0.75	− 0.80 (− 1.28, − 0.32)	0.001
Fibrinogen Level (gm/l), Median (Q1, Q3)^§	5.5 (3.39, 7.18)	4.8 (3.95, 6.65)	0.31	− 0.99 (− 1.51, − 0.48)	0.0002
C-reactive protein (mg/l), Mean (SD)^§	184.2 (148.1)	174.0 (124.3)	0.92	− 0.05 (− 0.36, 0.27)	0.77

^§Denominator is the total number of patients
^Wilcoxon rank sum test is used to calculate the P-value
^$*Generalized linear model is used to calculate estimates and p-value
*All levels represent peak levels for each one of the biomarkers