Title: Association Between Neutrophil-Albumin Ratio and Ultrasound-Defined Metabolic
Dysfunction-Associated Fatty Liver Disease in U.S. Adults: Evidence from NHANES
2017-2018
Version: 0 Date: 26 Dec 2024
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While the introduction sets the stage well, it could be made clearer that the study aims to explore
NAR’s predictive power for NAFLD specifically in a broader population (NHANES dataset) to
support targeted prevention and treatment strategies.
-The introduction could provide more insight into the potential mechanisms linking systemic
inflammation (as reflected by NAR) and liver fat accumulation or liver injury, which would be
helpful for readers who are less familiar with the concept.
-The description of the GLM and GAM methods could benefit from a more detailed explanation
of how the models were selected and the assumptions behind these choices. For instance, what
was the rationale for the specific covariates included in each model? This additional detail would
help readers understand why these specific covariates (such as ALT, AST, BUN) were chosen
for adjustment.
-The discussion touches on the nonlinear relationship between NAR and CAP but could expand
on the biological rationale for this pattern. Why is the risk of NAFLD most strongly affected at
lower NAR levels, and what does this imply for clinical practice? A more in-depth exploration
of the threshold effect could be helpful.
-While the potential clinical applications of NAR are mentioned, the manuscript could benefit
from a clearer step-by-step outline of how NAR would be integrated into clinical workflows.
For example, how would NAR be used alongside other markers like ALT or triglycerides in a
real-world clinical setting to identify at-risk individuals?
Title: Association Between Neutrophil-Albumin Ratio and Ultrasound-Defined Metabolic
Dysfunction-Associated Fatty Liver Disease in U.S. Adults: Evidence from NHANES
2017-2018
Version: 0 Date: 26 Dec 2024
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While the introduction sets the stage well, it could be made clearer that the study aims to explore
NAR’s predictive power for NAFLD specifically in a broader population (NHANES dataset) to
support targeted prevention and treatment strategies.
-The introduction could provide more insight into the potential mechanisms linking systemic
inflammation (as reflected by NAR) and liver fat accumulation or liver injury, which would be
helpful for readers who are less familiar with the concept.
-The description of the GLM and GAM methods could benefit from a more detailed explanation
of how the models were selected and the assumptions behind these choices. For instance, what
was the rationale for the specific covariates included in each model? This additional detail would
help readers understand why these specific covariates (such as ALT, AST, BUN) were chosen
for adjustment.
-The discussion touches on the nonlinear relationship between NAR and CAP but could expand
on the biological rationale for this pattern. Why is the risk of NAFLD most strongly affected at
lower NAR levels, and what does this imply for clinical practice? A more in-depth exploration
of the threshold effect could be helpful.
-While the potential clinical applications of NAR are mentioned, the manuscript could benefit
from a clearer step-by-step outline of how NAR would be integrated into clinical workflows.
For example, how would NAR be used alongside other markers like ALT or triglycerides in a
real-world clinical setting to identify at-risk individuals?
Please review this paper.
user
Title: Association Between Neutrophil-Albumin Ratio and Ultrasound-Defined Metabolic
Dysfunction-Associated Fatty Liver Disease in U.S. Adults: Evidence from NHANES
2017-2018
Version: 0 Date: 26 Dec 2024
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While the introduction sets the stage well, it could be made clearer that the study aims to explore
NAR’s predictive power for NAFLD specifically in a broader population (NHANES dataset) to
support targeted prevention and treatment strategies.
-The introduction could provide more insight into the potential mechanisms linking systemic
inflammation (as reflected by NAR) and liver fat accumulation or liver injury, which would be
helpful for readers who are less familiar with the concept.
-The description of the GLM and GAM methods could benefit from a more detailed explanation
of how the models were selected and the assumptions behind these choices. For instance, what
was the rationale for the specific covariates included in each model? This additional detail would
help readers understand why these specific covariates (such as ALT, AST, BUN) were chosen
for adjustment.
-The discussion touches on the nonlinear relationship between NAR and CAP but could expand
on the biological rationale for this pattern. Why is the risk of NAFLD most strongly affected at
lower NAR levels, and what does this imply for clinical practice? A more in-depth exploration
of the threshold effect could be helpful.
-While the potential clinical applications of NAR are mentioned, the manuscript could benefit
from a clearer step-by-step outline of how NAR would be integrated into clinical workflows.
For example, how would NAR be used alongside other markers like ALT or triglycerides in a
real-world clinical setting to identify at-risk individuals?
assistant