PREreview of The Impact of COVID-19 Vaccine on Rate of Hospitalization and Outcome of COVID- 19 Infection in a Single Center in the Eastern Province of Saudi Arabia

In this manuscript, the authors sought to “quantify vaccination efficiency” to reduce hospitalization and death rates under real-world settings in a Hospital from Saudi Arabia. The authors conducted a retrospective cohort study including 331 patients from a single center, performed statistical comparisons between unvaccinated and vaccinated individuals, and described differences among them. They conclude that hospital stay was prolonged in unvaccinated individuals. While the research question could be interesting, there are several methodological limitations of this study that should be addressed by the authors since the study is poor at trying to support any of its conclusions in its current form and significant efforts are needed to improve this study so that conclusions are well-founded. Mi main comments are the following:

1. It is not clear what the authors mean by “efficiency”. This is important to define since the study design needs to adequately match the research question.

2. The authors have not complied with STROBE recommendations to report their manuscript. Therefore, several key elements are absent and limit the quality of the manuscript. Since this is an observational study using routinely collected health data, the authors should review the STROBE and RECORD statements available at the Equator Network (https://www.equator-network.org/) and provide both the STROBE and RECORD checklists alongside their manuscript so that the manuscript can be fully evaluated. I am currently not able to fairly evaluate all aspects related to this study since key elements were not described by the authors.

3. A sample size was apparently not calculated to address the study hypothesis. 

4. The statistical analyses, despite being correct, are not robust enough to corroborate the objective of the study. The application of a Cox regression analysis could help the authors support their conclusions. The creation of Kaplan-Meier survival curves would also be useful to compare the number of events graphically from admission to each outcome is taken into account. The estimation of the effect sizes for each vaccination-related outcome should be adjusted for other confounding variables such as sex and age, and even demographic, clinical or laboratory variables.

5. The analysis of laboratory data by categories is not recommended since a lot of information is lost when making the categories for each parameter. Quantitative comparisons by parametric statistics would be better if the data meet statistical assumptions needed for these analyses.

6. The statistical analysis section needs to be described as a continuous text, complying with all STROBE recommendations. Enough explanation should be given on how primary and secondary outcomes were analyzed. This section should provide enough description for someone to reproduce analyses in the hypothetical case that the dataset is requested. There should be a clear flow with enough descriptions, for example: descriptive analyses, inferential analyses, subanalyses, secondary analyses, statistical assumptions, software, and other statistical considerations (i.e. how was significance defined). 

7. There are too many tables for descriptive data (frequency and percentage), which could have easily been fitted into a single table of descriptive data. See STROBE recommendations for examples of how descriptive data can be presented.