N-Acetyl Glucosamine as Therapeutic Intervention for Coronavirus Disease-19 (COVID-19)
Phase: PHASE1
Conditions: Coronavirus, Covid19
Sponsor: Quantinosis.ai LLC

AN OBSERVATIONAL COHORT STUDY TO ASSESS N-ACETYLGLUCOSAMINE 
FOR COVID-19 TREATMENT IN THE INPATIENT SETTING 
 
Protocol Overview and Statistical Analysis Plan 
 
 
Ameer E. Hassan, DO 
Neuroscience Department, Valley Baptist Medical Center 
2101 Pease St, Harlingen, TX 78550 
Email: ameerehassan@gmail.com 
Phone: 956-389-6565 
Fax: 956-389-3567 
ORCID: https://orcid.org/0000-0002-7148-7616 
 
 
Approved: August 26, 2020 
 
NCT04706416 
 
 

1.0 PROTOCOL OVERVIEW 
1.1 Study Design 
This work will be reported in line with STROCSS criteria [1]. This is a single-center, 
observational study to be carried out in adult patients presenting to the emergency department of 
Valley Baptist Medical Center (Harlingen, TX, USA) with shortness of breath. The research 
protocol has been reviewed and received approval from the Institutional Review Board (IRB) at 
MetroWest Medical Center, Framingham Union Hospital, and Leonard Morse Hospital (IRB 
#2020-106; approved August 26, 2020). The study is registered on ClinicalTrials.gov 
(NCT04706416). The study period will be approximately November 2020 to January 2021, 
aiming to enroll 50 patients to receive NAG.  
 
Consecutive patients who present with shortness of breath will be immediately tested for 
COVID-19 through reverse transcription polymerase chain reaction (RT-PCR) and approached 
for enrollment in the study. Those who provide informed consent and receive a positive COVID-
19 diagnosis will be included in the study; those who test negative for COVID-19 will not be 
included. No determination will be made regarding COVID-19 variants or false positive results. 
Study participants will receive 700 mg NAG orally every 12 hours as first-line treatment upon 
admission. Patients in the treatment group will also receive standard of care at the discretion of 
the attending physician, including antibiotics, antivirals, corticosteroids, and convalescent 
plasma. Patients will continue to receive NAG and be followed until study exit, which occurs at 
expiration, discharge, or 30 days. 
 
1.2 Inclusion & Exclusion Criteria 
Inclusion criteria will remain unchanged for the duration of the study and stipulate that all 
patients must be ≥18 years old; present with shortness of breath (since local institutional policy 
only admits patients with shortness of breath); clinical diagnosis of COVID-19 by RT-PCR; 
hospital admittance due to COVID-19; administered NAG orally as first-line treatment; and no 
intubation prior to hospitalization and enrollment in the current study. Patients will be excluded 
if they do not meet criteria above, have an allergy to NAG or shellfish, are currently taking 
warfarin, or are currently pregnant or lactating. 
 
1.3 Data Collection & Outcomes 
Upon admission, the research team will record patient demographics, comorbidities, symptoms, 
disease severity (as assessed by the World Health Organization [WHO] Ordinal Scale for 
Clinical Improvement [2]), need for supplemental oxygen, and time from symptom onset until 
hospital arrival. The research team will also collect bloodwork for the following at admission: 
white blood cell count (WBC), hematocrit (HCT), hemoglobin (HBG), C-reactive protein (CRP), 
procalcitonin (PCT), interleukin-6 (IL-6), and erythrocyte sedimentation rate (ESR). During the 
study period, discretionary treatments and interventions will be recorded daily until study exit. 
 
The primary outcomes of interest are rate of intubation, hospital LOS, and mortality following 
rapid administration of 700 mg NAG for COVID-19 treatment. Secondary outcomes of interest 
include intensive care unit (ICU) admission, ICU LOS, supplemental oxygen duration, rate of 
hospice initiation, and poor clinical outcome (defined as combined death/hospice initiation).  
 
 

Beginning on the study start date, the previous 100 COVID-19-positive consecutive patients 
admitted to Valley Baptist Medical Center will be retrospectively identified via chart review to 
serve as the control/comparison arm. Data for these patients will be collected before 
commencement of the NAG trial. Univariate analysis will be performed for all primary and 
secondary outcomes, followed by multivariate analysis for primary outcomes and select 
secondary outcomes that approach significance and have sufficient frequency of occurrence to be 
meaningful; the main conclusions of this study will be drawn from multivariate analysis. Due to 
its status as a pilot study and the urgency of releasing information about COVID-19, a priori 
sample size calculations will not be performed for this study. Instead, samples are based on cost, 
patient availability, limited timeline, and best practices in the view of the principal investigator, 
with the intention of detecting potential effects or trends to be further evaluated in later studies. 
Since IRB does not require patient consent for de-identified data and there is sufficient data 
availability, a larger study arm will be selected for the control arm to increase the power and 
sensitivity of the analysis while reducing risk of type 2 error, at no extra cost in terms of time or 
resources.  
 
 
 

2.0 STATISTICAL ANALYSIS PLAN 
Continuous parameters will be assessed for normality based on cross-validation using Anderson-
Darling [3], D'Agostino-Pearson omnibus [4], Shapiro-Wilk [5], and Kolmogorov-Smirnov tests 
[6]. Comparisons of normally distributed data between groups will be analyzed using unpaired 
Student’s t-tests. Effect sizes from t-tests will be reported as mean differences with 95% 
confidence intervals (CIs) based on normal approximation. Comparisons of nonparametric data 
between groups will be analyzed using the Mann-Whitney U test. Effect sizes from 
nonparametric tests will be reported as Hodge’s-Lehman differences (H-L Diff) and their 
respective 95% CIs. Comparisons of dichotomous data between groups will be analyzed using 
Fisher’s exact binomial test [7]. Effect sizes from Fisher’s exact test will be reported as odds 
ratios (ORs) with 95% CIs computed using the Baptista-Pike method [8].  
 
A correlation matrix showing the strength and direction of correlation between covariates and 
outcomes will be generated using Spearman’s rank correlation test via the ‘corrplot’ package in 
R. Spearman’s rank correlation will be used to provide a more robust measurement of correlation 
in the face of high leverage outliers. Simple linear or logistic regressions will be used to evaluate 
potential predictors of primary and secondary outcomes. Multivariate regression using best 
subset selection will be performed based on model comparison using adjusted R2 values (linear 
regressions) or adjusted pseudo-R2 values (logistic regressions). Model predictive performance 
of multiple linear regression will also be evaluated by root mean square error (RMSE) values and 
multiple logistic regressions will be evaluated by area under the receiver operating characteristic 
curve (ROC). Comparisons of best subset selection with models including the full set of 
covariates considered for multivariate analysis will also be performed. Best subset selection will 
be carried out using the ‘leaps’ package in R. P-values ≤0.05 are considered significant for all 
analyses. All statistics will be performed in RStudio (Version 1.3.959, RStudio, PBC, Boston, 
MA).  
 
 
 
 

3.0 REFERENCES 
 
[1] 
Agha R, Abdall-Razak A, Crossley E, Dowlut N, Iosifidis C, Mathew G. STROCSS 2019 
Guideline: Strengthening the reporting of cohort studies in surgery. Int J Surg 2019;72:156-65. 
https://doi.org/10.1016/j.ijsu.2019.11.002 
[2] 
Clinical Management of COVID-19: Living Guidance. In: Organization WH, editor. 
https://www.who.int/publications/i/item/clinical-management-of-covid-192021. 
[3] 
Anderson TW, Darling DA. A Test of Goodness of Fit. Journal of the American 
Statistical Association 1954;49(268):765-9. https://doi.org/10.1080/01621459.1954.10501232 
[4] 
Koziol JA, D'Agostino RB, Stephens MA. Goodness-of-Fit Techniques. Journal of 
Educational Statistics 1987;12(412). https://doi.org/doi:10.2307/1165059 
[5] 
Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). 
Biometrika 1965;52(3-4):591-611. https://doi.org/10.1093/biomet/52.3-4.591 
[6] 
Kolmogorov–Smirnov Test. Springer New York. p. 283-7. 
[7] 
Fisher R. On the Interpretation of χ2 from Contingency Tables, and the Calculation of P. 
Journal of the Royal Statistical Society 1922;85(1):87-94. https://doi.org/10.2307/2340521 
[8] 
Baptista J, Pike M. Algorithm AS 115: Exact Two-Sided Confidence Limits for the Odds 
Ratio in a 2 × 2 Table. Journal of the Royal Statistical Society 1977;26(2):214-20. 
https://doi.org/10.2307/2347041