Dear Dr. Bonilla,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

ACADEMIC EDITOR'S COMMENTS:

Line 142-144: "Most COVID-19-related deaths were due to progression to acute respiratory distress syndrome (ARDS) and its heightened inflammatory cytokines release state (8, 9).": this statement is inaccurate. While the original COVID due to wild-type SARS-CoV-2 strains can cause ARDS, the SARS-CoV-2 viruses that have evolved to Omicron strains primarily cause mild symptoms. The authors should introduce this point based on more references, with this one (Liu BM, et al. Genetic Conservation and Diversity of SARS-CoV-2 Envelope Gene Across Variants of Concern. J Med Virol. 2025 Jan;97(1):e70136. doi: 10.1002/jmv.70136. PMID: 39744807.) as an example (citing is optional). 

The authors should discuss a limitation that they could not exclude patients who were hospitalized due to COVID and co-infection with other non-SARS-CoV-2 respiratory pathogens. Different respiratory viruses can lead to similar symptoms with COVID, which cannot be differentiated unless performing related testing using multiplex respiratory PCR panels. The authors should discuss this with more references cited, with these (PMID: 39857007 and 40137747) as example (citing is optional).

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We look forward to receiving your revised manuscript.

Kind regards,

Benjamin M. Liu, MBBS, PhD, D(ABMM), MB(ASCP)

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Thank you for sharing the manuscript. Below is a detailed peer review of the article “Body Mass Index Impact on ICU Interventions and Outcomes in Hospitalized Patients with COVID-19 Infection – A National Population-Based Study.”

SUMMARY OF REQUIRED CHANGES

Grammar: Revise awkward or passive constructions, eliminate redundancies

Ethics: Include IRB name, approval number or formal statement of exemption

References: Fix the citation error (!!! INVALID CITATION !!!), and ensure uniform formatting

Scientific Clarity: Explicitly address possible biases and explain clinical relevance of modest odds ratios

Consistency: Ensure consistent use of terms like “obesity,” “COVID-19 infection,” and “mechanical ventilation”

Reviewer #2: The manuscript addresses an important topic in hospitalized COVID-19 patients during the pre-vaccination period. The use of a large, national cohort from the HCA Healthcare database is a strength, providing robust statistical power. However, several methodological and interpretive concerns warrant attention before publication.

1. Innovation is not seen in the manuscript. As mentioned in lines 145-146, the effect on the complications of COVID-19 has been confirmed.

2. No statistics, tables, or comparisons have been provided or explained regarding various factors other than BMI. please adde to introduction and discussion.

3. Has body mass been examined alongside other factors such as the use of certain medications, underlying diseases, etc.? Please add it to the manuscript

4. Figure1 is very simple and the entire steps of sample selection, data processing, extraction, etc. need to be presented in the form of a tree.

5. The exclusion of patients with significant comorbidities (e.g., malignancy, chronic pulmonary disease, immunocompromised states) and DNR/DNI status is problematic. These exclusions may introduce selection bias, as these conditions are prevalent in real-world COVID-19 populations and could confound the relationship between BMI and outcomes. A sensitivity analysis including these patients, or a justification for their exclusion based on prior literature, is essential.

6. The R² values for multivariate linear regression models (0.053 for duration of mechanical ventilation and 0.037 for ICU LOS) are extremely low, indicating that the models explain only a small fraction of the variance. This suggests that critical unmeasured confounders (e.g., severity scores like SOFA or APACHE II, timing of interventions) may be missing. The reliance on BMI categories alone without adjusting for BMI as a continuous variable limits the granularity of findings.

7. The study relies on BMI calculated from medical records, which may be inaccurate due to supine height measurements, fluid status (e.g., in dialysis patients), or excess muscle mass. This introduces measurement error that could skew results, particularly for underweight and obese categories. The lack of discussion on these limitations undermines the reliability of conclusions.

8. The claim that obesity is independently associated with higher mortality (OR 1.29) is overstated given the non-significant difference in all-cause mortality across BMI categories (p=0.14, Table 3). This inconsistency suggests overfitting or residual confounding. The Discussion also overgeneralizes findings to the U.S. population without acknowledging regional healthcare disparities.

9. While the association between obesity and worse COVID-19 outcomes is consistent with prior studies (e.g., Kompaniyets et al., 2021), the manuscript fails to highlight novel insights or clinical interventions beyond existing knowledge. The recommendation for "tailored medical strategies" is vague and lacks specific actionable guidance.

10. The abstract is dense and lacks a concise summary of key findings (e.g., specific ORs or LOS differences). Revise to include a succinct results overview.

Reviewer #3: Review Comments

1. Structure and Title

The title is clear and effectively reflects the core content of the study. However, it could be slightly shortened for improved readability, for example:

"Body Mass Index and Critical Care Outcomes in Hospitalized COVID-19 Patients: A National Cohort Study"

Abstract: The abstract well-articulates the objectives, methodology, and key findings. However, in the Methods section, it would enhance clarity if the source of the data (e.g., specific database or registry) were explicitly mentioned.

2. Introduction

The introduction adequately sets the epidemiological and clinical context of the relationship between Body Mass Index (BMI) and respiratory disease severity, particularly in COVID-19 . However, more recent literature on the "obesity paradox" in respiratory illnesses could be referenced for a more comprehensive background

The hypothesis is clearly defined. Nevertheless, the significance of this study compared to previous work—such as the studies by Kompaniyets et al. (2021) and Kapoor et al. (2022) —should be more explicitly highlighted.

3. Methods

The study population and sample size (22,000 patients) are commendable, and data were drawn from the HCA Healthcare database, which is representative of 149 hospitals across 18 U.S. states. However, it would improve the methodological rigor if the authors clarified how variables such as prior vaccination status or previous SARS-CoV-2 infection (e.g., IgG serostatus) were accounted for in the analysis.

The BMI categories follow CDC standards, which is appropriate. However, the exclusion of the underweight group (BMI <18.5) from many analyses should be justified and discussed, especially if it was due to low sample size or confounding factors.

Statistical analysis: The use of ANOVA and regression models is suitable. However, further explanation should be provided regarding how confounding variables such as age, sex, and comorbidities (e.g., diabetes) were controlled in the models.

Limitations: The authors appropriately acknowledge limitations such as lack of access to detailed clinical data (e.g., inflammatory markers, medication use). However, this could be expanded by addressing how antiviral treatments and vaccination timing may have influenced outcomes, particularly during the pre-vaccination period.

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4. Results

Table 3 is well-structured, but for the "Duration of Mechanical Ventilation" section, a bar chart would better emphasize differences than a tabular format.

Key Findings:

Obese patients had the highest rates of tracheostomy placement and prolonged mechanical ventilation, findings consistent with prior studies.

All-cause mortality did not show significant differences across BMI categories, which contrasts with some reported findings and deserves further discussion.

The multivariate analysis reported significant odds ratios for diabetes (OR: 1.70) , obesity (OR: 1.57), and chronic kidney disease (OR: 1.87) . However, the inverse association between age and tracheostomy need (OR: 0.98) requires clarification.

5. Discussion

The discussion compares well with previous studies such as Petrilli et al. (2020)

, but could benefit from referencing Simonnet et al. (2020), who demonstrated a strong association between obesity and mechanical ventilation requirements.

The clinical mechanisms linking obesity to mechanical ventilation needs are explained clearly. However, the role of altered leukocyte metabolism in obese individuals could be expanded upon to provide a deeper biological insight.

Limitations: The authors have appropriately addressed issues such as limited access to palliative care data and type of antiviral drugs used. Further elaboration on how obesity and associated comorbidities (e.g., diabetes) affected clinical decision-making and ICU management would strengthen this section.

Clinical Relevance: The results are well-connected to clinical practice, but the importance of weight management and obesity prevention strategies in reducing risks associated with COVID-19 severity should be emphasized.

6. Conclusion

The conclusions are well-summarized. To strengthen the impact, the authors could specify actionable strategies for managing obese patients with COVID-19, such as:

Increased vigilance in respiratory support.

Early decision-making protocols for tracheostomy when indicated.

Prioritizing vaccination and early intervention in obese patient groups.

7. Tables and Figures

Table 3 is well-constructed, but the variables "Need for Mechanical Ventilation" and "Tracheostomy Placement" would benefit from being presented as percentages to improve interpretability.

Figures 3 and 4 are appropriately structured, but the legends should clearly indicate the confidence intervals (CI) and beta/OR values for the regression outputs.

Figure Captions: The captions could be more precise. For instance, in Figure 4, it would improve clarity to specify the BMI range for the obese category.

8. References

The reference list includes recent and relevant sources. However, additional citations could be added for topics such as obesity and cytokine storm, and immunometabolism in obesity.

Some references, particularly

, should be updated to include the correct author names and publication years.

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Reviewer #1: Yes:  Ali Khanifar

Reviewer #2: Yes:  Davood Azadi

Reviewer #3: No

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Body mass index and critical care outcomes in hospitalized COVID-19 patients – a national cohort study

PONE-D-25-18274R1

Dear Dr. Bonilla,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Benjamin M. Liu, MBBS, PhD, D(ABMM), MB(ASCP)

Academic Editor

PLOS ONE

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