Title: The Association between Healthy Eating Index-2015 with Anthropometric,
Cardiometabolic and Hepatic Indices among Patients with Non-alcoholic Fatty Liver Disease
Version: 2 Date: 09 Jan 2023
Reviewer's report:
The Authors performed a descriptive analysis on the distribution of HEI quartiles among
different features of NAFLD. A male susceptibility to worse hepatic indices was shown.
This study has several limitations, starting from the language: it is difficult to read and to
understand in several key passages.
About the methods: NAFLD is not defined in the inclusion and exclusion criteria, nor how it
was diagnosed. Most scores are not widely validated and no robust information may be given
(AIP, LAP, CMI, LCI).
A linear regression analysis only describes a correlation (curve in a graph) between two
continous variables. To assess a risk, and a n association, a logistic regression analysis with
odds ratio would be required, also considering that a transformation of the HEI into categorical
variable has already been done in this paper. In addition, the regression models lack critical
information that is included in the NAFLD landscape (diabetes, BMI, transaminases). The
choice of the variable reflects a lack of knowledge in the field.
In addition, almost all findings are not significant. Male sex has been widely addressed as a risk
factor in this field, these results do not add to the current scientific knowledge.
Taken together, the language use, the methodological weakness and the inconsistency of the
results are strong limitations to this paper.
Title: The Association between Healthy Eating Index-2015 with Anthropometric,
Cardiometabolic and Hepatic Indices among Patients with Non-alcoholic Fatty Liver Disease
Version: 2 Date: 09 Jan 2023
Reviewer's report:
The Authors performed a descriptive analysis on the distribution of HEI quartiles among
different features of NAFLD. A male susceptibility to worse hepatic indices was shown.
This study has several limitations, starting from the language: it is difficult to read and to
understand in several key passages.
About the methods: NAFLD is not defined in the inclusion and exclusion criteria, nor how it
was diagnosed. Most scores are not widely validated and no robust information may be given
(AIP, LAP, CMI, LCI).
A linear regression analysis only describes a correlation (curve in a graph) between two
continous variables. To assess a risk, and a n association, a logistic regression analysis with
odds ratio would be required, also considering that a transformation of the HEI into categorical
variable has already been done in this paper. In addition, the regression models lack critical
information that is included in the NAFLD landscape (diabetes, BMI, transaminases). The
choice of the variable reflects a lack of knowledge in the field.
In addition, almost all findings are not significant. Male sex has been widely addressed as a risk
factor in this field, these results do not add to the current scientific knowledge.
Taken together, the language use, the methodological weakness and the inconsistency of the
results are strong limitations to this paper.
Please review this paper.
user
Title: The Association between Healthy Eating Index-2015 with Anthropometric,
Cardiometabolic and Hepatic Indices among Patients with Non-alcoholic Fatty Liver Disease
Version: 2 Date: 09 Jan 2023
Reviewer's report:
The Authors performed a descriptive analysis on the distribution of HEI quartiles among
different features of NAFLD. A male susceptibility to worse hepatic indices was shown.
This study has several limitations, starting from the language: it is difficult to read and to
understand in several key passages.
About the methods: NAFLD is not defined in the inclusion and exclusion criteria, nor how it
was diagnosed. Most scores are not widely validated and no robust information may be given
(AIP, LAP, CMI, LCI).
A linear regression analysis only describes a correlation (curve in a graph) between two
continous variables. To assess a risk, and a n association, a logistic regression analysis with
odds ratio would be required, also considering that a transformation of the HEI into categorical
variable has already been done in this paper. In addition, the regression models lack critical
information that is included in the NAFLD landscape (diabetes, BMI, transaminases). The
choice of the variable reflects a lack of knowledge in the field.
In addition, almost all findings are not significant. Male sex has been widely addressed as a risk
factor in this field, these results do not add to the current scientific knowledge.
Taken together, the language use, the methodological weakness and the inconsistency of the
results are strong limitations to this paper.
assistant