Title: Association of cardiometabolic index with gallstone disease and insulin resistance based
on NHANES data
Version: 1 Date: 14 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-As a cross-sectional study, the findings can only suggest associations, not causality. There is
no ability to infer whether changes in CMI directly cause the development of GSD or IR, which
limits the conclusions that can be drawn from the study. Longitudinal studies would be needed
to assess causality.
-The study uses the HOMA-IR method for assessing insulin resistance, which, although
commonly used, might not be as accurate as other more direct methods (e.g., the
hyperinsulinemic-euglycemic clamp). While HOMA-IR is a practical method, its use could be
a limitation due to potential inaccuracies in certain populations, especially in those with more
severe insulin resistance.
-While the study adjusts for several confounding variables, there might be additional factors that
could influence the relationship between CMI and GSD that were not considered. For example,
dietary patterns, physical activity levels, and medication use (e.g., statins or other metabolic
disease treatments) are potential confounders that could impact both metabolic health and the
development of GSD.
-The study relies on self-reported data for the diagnosis of GSD, which could introduce
bias. The accuracy of self-reported gallstone diagnoses is uncertain, and this could lead to
misclassification. Ideally, more objective diagnostic data (e.g., ultrasound or CT scans) would
have strengthened the study.
-While the study uses multivariable logistic regression, it doesn’t provide much information on
the goodness-of-fit of the models, such as measures like the Akaike Information Criterion (AIC)
or the pseudo-R². This would help evaluate whether the models adequately fit the data.
The study mentions the use of RCS plots to assess the dose-response relationship between CMI
and IR but does not fully elaborate on the specifics of the dose-response findings. A clearer
presentation of how CMI levels correlate with varying degrees of insulin resistance would have
provided more actionable insights.
-The discussion appropriately addresses the main limitation of the study being cross-sectional.
While the study identifies associations, it cannot establish causality. The authors should
highlight this limitation more strongly and emphasize that future longitudinal studies are needed
to explore temporal relationships between CMI, GSD, and IR. It would also be useful to briefly
mention that longitudinal designs can help confirm whether CMI can indeed serve as a predictor
for the future development of GSD or IR.
-The reliance on self-reported data for the diagnosis of GSD is another limitation the authors
acknowledge. While this is an important point, the discussion could benefit from further
elaboration on the potential bias introduced by self-reported diagnoses, and the implications
for the findings. Additionally, the authors could suggest ways to improve the accuracy of
self-reported data, such as incorporating medical records or imaging studies to confirm GSD
diagnoses.
-The study does not differentiate between various types of gallstones (e.g., cholesterol vs.
pigment stones), which could have different underlying metabolic causes. The discussion could
highlight how including this differentiation could provide a more nuanced understanding of the
relationship between CMI and GSD. Furthermore, exploring whether certain subtypes of GSD
are more strongly linked to CMI and IR would enhance the depth of the analysis.
Title: Association of cardiometabolic index with gallstone disease and insulin resistance based
on NHANES data
Version: 1 Date: 14 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-As a cross-sectional study, the findings can only suggest associations, not causality. There is
no ability to infer whether changes in CMI directly cause the development of GSD or IR, which
limits the conclusions that can be drawn from the study. Longitudinal studies would be needed
to assess causality.
-The study uses the HOMA-IR method for assessing insulin resistance, which, although
commonly used, might not be as accurate as other more direct methods (e.g., the
hyperinsulinemic-euglycemic clamp). While HOMA-IR is a practical method, its use could be
a limitation due to potential inaccuracies in certain populations, especially in those with more
severe insulin resistance.
-While the study adjusts for several confounding variables, there might be additional factors that
could influence the relationship between CMI and GSD that were not considered. For example,
dietary patterns, physical activity levels, and medication use (e.g., statins or other metabolic
disease treatments) are potential confounders that could impact both metabolic health and the
development of GSD.
-The study relies on self-reported data for the diagnosis of GSD, which could introduce
bias. The accuracy of self-reported gallstone diagnoses is uncertain, and this could lead to
misclassification. Ideally, more objective diagnostic data (e.g., ultrasound or CT scans) would
have strengthened the study.
-While the study uses multivariable logistic regression, it doesn’t provide much information on
the goodness-of-fit of the models, such as measures like the Akaike Information Criterion (AIC)
or the pseudo-R². This would help evaluate whether the models adequately fit the data.
The study mentions the use of RCS plots to assess the dose-response relationship between CMI
and IR but does not fully elaborate on the specifics of the dose-response findings. A clearer
presentation of how CMI levels correlate with varying degrees of insulin resistance would have
provided more actionable insights.
-The discussion appropriately addresses the main limitation of the study being cross-sectional.
While the study identifies associations, it cannot establish causality. The authors should
highlight this limitation more strongly and emphasize that future longitudinal studies are needed
to explore temporal relationships between CMI, GSD, and IR. It would also be useful to briefly
mention that longitudinal designs can help confirm whether CMI can indeed serve as a predictor
for the future development of GSD or IR.
-The reliance on self-reported data for the diagnosis of GSD is another limitation the authors
acknowledge. While this is an important point, the discussion could benefit from further
elaboration on the potential bias introduced by self-reported diagnoses, and the implications
for the findings. Additionally, the authors could suggest ways to improve the accuracy of
self-reported data, such as incorporating medical records or imaging studies to confirm GSD
diagnoses.
-The study does not differentiate between various types of gallstones (e.g., cholesterol vs.
pigment stones), which could have different underlying metabolic causes. The discussion could
highlight how including this differentiation could provide a more nuanced understanding of the
relationship between CMI and GSD. Furthermore, exploring whether certain subtypes of GSD
are more strongly linked to CMI and IR would enhance the depth of the analysis.
Please review this paper.
user
Title: Association of cardiometabolic index with gallstone disease and insulin resistance based
on NHANES data
Version: 1 Date: 14 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-As a cross-sectional study, the findings can only suggest associations, not causality. There is
no ability to infer whether changes in CMI directly cause the development of GSD or IR, which
limits the conclusions that can be drawn from the study. Longitudinal studies would be needed
to assess causality.
-The study uses the HOMA-IR method for assessing insulin resistance, which, although
commonly used, might not be as accurate as other more direct methods (e.g., the
hyperinsulinemic-euglycemic clamp). While HOMA-IR is a practical method, its use could be
a limitation due to potential inaccuracies in certain populations, especially in those with more
severe insulin resistance.
-While the study adjusts for several confounding variables, there might be additional factors that
could influence the relationship between CMI and GSD that were not considered. For example,
dietary patterns, physical activity levels, and medication use (e.g., statins or other metabolic
disease treatments) are potential confounders that could impact both metabolic health and the
development of GSD.
-The study relies on self-reported data for the diagnosis of GSD, which could introduce
bias. The accuracy of self-reported gallstone diagnoses is uncertain, and this could lead to
misclassification. Ideally, more objective diagnostic data (e.g., ultrasound or CT scans) would
have strengthened the study.
-While the study uses multivariable logistic regression, it doesn’t provide much information on
the goodness-of-fit of the models, such as measures like the Akaike Information Criterion (AIC)
or the pseudo-R². This would help evaluate whether the models adequately fit the data.
The study mentions the use of RCS plots to assess the dose-response relationship between CMI
and IR but does not fully elaborate on the specifics of the dose-response findings. A clearer
presentation of how CMI levels correlate with varying degrees of insulin resistance would have
provided more actionable insights.
-The discussion appropriately addresses the main limitation of the study being cross-sectional.
While the study identifies associations, it cannot establish causality. The authors should
highlight this limitation more strongly and emphasize that future longitudinal studies are needed
to explore temporal relationships between CMI, GSD, and IR. It would also be useful to briefly
mention that longitudinal designs can help confirm whether CMI can indeed serve as a predictor
for the future development of GSD or IR.
-The reliance on self-reported data for the diagnosis of GSD is another limitation the authors
acknowledge. While this is an important point, the discussion could benefit from further
elaboration on the potential bias introduced by self-reported diagnoses, and the implications
for the findings. Additionally, the authors could suggest ways to improve the accuracy of
self-reported data, such as incorporating medical records or imaging studies to confirm GSD
diagnoses.
-The study does not differentiate between various types of gallstones (e.g., cholesterol vs.
pigment stones), which could have different underlying metabolic causes. The discussion could
highlight how including this differentiation could provide a more nuanced understanding of the
relationship between CMI and GSD. Furthermore, exploring whether certain subtypes of GSD
are more strongly linked to CMI and IR would enhance the depth of the analysis.
assistant