Title: Cardiometabolic Index as a Predictor of Gallstone Risk: Evidence from NHANES 2017–
2020
Version: 1 Date: 01 Feb 2025
Reviewer:  Amira A A Othman
Reviewer's report:
First of all
I want to congratulate the authors on their work. In this study, Zheng et al. aimed to evaluate the
association between the Cardiometabolic Index (CMI) and the prevalence of gallstones using
data from the NHANES 2017–2020 dataset. The study included 5,421 participants, with 571
reporting gallstones. Logistic regression analyses revealed that individuals in the highest quartile
of CMI had a 90% higher risk of developing gallstones than those in the lowest quartile (OR =
1.90; 95% CI: 1.37-2.62, P < 0.0001). The relationship was nonlinear, with a significant increase
in gallstone risk when CMI was below 0.85 (OR = 2.61; 95% CI: 1.62-4.19), but no additional
risk increases beyond this threshold. The study highlights CMI as a potential predictive marker
for gallstone risk, supporting its integration into clinical assessments for early detection and
prevention.
The authors tried to contribute to this field of research with new findings, nevertheless, there is
an observation for which sufficient justification must be obtained.
In general:
1. The English writing level is shallow, and it is necessary to seek help from an English language
specialist to correct spelling and grammatical errors in the entire text.
2. Abbreviations must be fully written at their first appearance.
3. Eliminate repetitive statements.
In title:
4. I suggest a more specific title such as “Cardiometabolic Index as a Predictor of Gallstone
Risk: Evidence from NHANES 2017–2020”.
In Abstract:
5. The abstract should briefly state the study's novelty, emphasizing that this is the first study
linking CMI to gallstones.
6. The abstract results statistical analysis could be streamlined for clarity.
7. The abstract conclusion should be more precise in recommending CMI as a clinical tool.
In Introduction:
8. State the NHANES dataset.
9. Emphasis on why previous markers of gallstone risk are insufficient would strengthen the
rationale for using CMI.
10. Provide a clearer hypothesis and aim of study at the end of the introduction to guide the
reader.
In Methods:
11. Improve the readability of inclusion and exclusion criteria.
12. The statistical methods, particularly the nonlinear modeling, should be briefly justified.
In Results:
13. Provide a table summarizing key statistical findings to improve readability.
14. which groups were most affected in subgroup analysis.
In Discussion:
15. Compare findings to previous studies on gallstone risk and metabolic indicators.
16. Biological mechanisms linking CMI to gallstones need further explanation.
17. The limitations section should consider self-reported data bias in gallstone diagnosis.
18. Discuss future longitudinal studies and clinical implications of CMI as a screening tool.
Title: Cardiometabolic Index as a Predictor of Gallstone Risk: Evidence from NHANES 2017–
2020
Version: 1 Date: 01 Feb 2025
Reviewer:  Amira A A Othman
Reviewer's report:
First of all
I want to congratulate the authors on their work. In this study, Zheng et al. aimed to evaluate the
association between the Cardiometabolic Index (CMI) and the prevalence of gallstones using
data from the NHANES 2017–2020 dataset. The study included 5,421 participants, with 571
reporting gallstones. Logistic regression analyses revealed that individuals in the highest quartile
of CMI had a 90% higher risk of developing gallstones than those in the lowest quartile (OR =
1.90; 95% CI: 1.37-2.62, P < 0.0001). The relationship was nonlinear, with a significant increase
in gallstone risk when CMI was below 0.85 (OR = 2.61; 95% CI: 1.62-4.19), but no additional
risk increases beyond this threshold. The study highlights CMI as a potential predictive marker
for gallstone risk, supporting its integration into clinical assessments for early detection and
prevention.
The authors tried to contribute to this field of research with new findings, nevertheless, there is
an observation for which sufficient justification must be obtained.
In general:
1. The English writing level is shallow, and it is necessary to seek help from an English language
specialist to correct spelling and grammatical errors in the entire text.
2. Abbreviations must be fully written at their first appearance.
3. Eliminate repetitive statements.
In title:
4. I suggest a more specific title such as “Cardiometabolic Index as a Predictor of Gallstone
Risk: Evidence from NHANES 2017–2020”.
In Abstract:
5. The abstract should briefly state the study's novelty, emphasizing that this is the first study
linking CMI to gallstones.
6. The abstract results statistical analysis could be streamlined for clarity.
7. The abstract conclusion should be more precise in recommending CMI as a clinical tool.
In Introduction:
8. State the NHANES dataset.
9. Emphasis on why previous markers of gallstone risk are insufficient would strengthen the
rationale for using CMI.
10. Provide a clearer hypothesis and aim of study at the end of the introduction to guide the
reader.
In Methods:
11. Improve the readability of inclusion and exclusion criteria.
12. The statistical methods, particularly the nonlinear modeling, should be briefly justified.
In Results:
13. Provide a table summarizing key statistical findings to improve readability.
14. which groups were most affected in subgroup analysis.
In Discussion:
15. Compare findings to previous studies on gallstone risk and metabolic indicators.
16. Biological mechanisms linking CMI to gallstones need further explanation.
17. The limitations section should consider self-reported data bias in gallstone diagnosis.
18. Discuss future longitudinal studies and clinical implications of CMI as a screening tool.
Please review this paper.
user
Title: Cardiometabolic Index as a Predictor of Gallstone Risk: Evidence from NHANES 2017–
2020
Version: 1 Date: 01 Feb 2025
Reviewer:  Amira A A Othman
Reviewer's report:
First of all
I want to congratulate the authors on their work. In this study, Zheng et al. aimed to evaluate the
association between the Cardiometabolic Index (CMI) and the prevalence of gallstones using
data from the NHANES 2017–2020 dataset. The study included 5,421 participants, with 571
reporting gallstones. Logistic regression analyses revealed that individuals in the highest quartile
of CMI had a 90% higher risk of developing gallstones than those in the lowest quartile (OR =
1.90; 95% CI: 1.37-2.62, P < 0.0001). The relationship was nonlinear, with a significant increase
in gallstone risk when CMI was below 0.85 (OR = 2.61; 95% CI: 1.62-4.19), but no additional
risk increases beyond this threshold. The study highlights CMI as a potential predictive marker
for gallstone risk, supporting its integration into clinical assessments for early detection and
prevention.
The authors tried to contribute to this field of research with new findings, nevertheless, there is
an observation for which sufficient justification must be obtained.
In general:
1. The English writing level is shallow, and it is necessary to seek help from an English language
specialist to correct spelling and grammatical errors in the entire text.
2. Abbreviations must be fully written at their first appearance.
3. Eliminate repetitive statements.
In title:
4. I suggest a more specific title such as “Cardiometabolic Index as a Predictor of Gallstone
Risk: Evidence from NHANES 2017–2020”.
In Abstract:
5. The abstract should briefly state the study's novelty, emphasizing that this is the first study
linking CMI to gallstones.
6. The abstract results statistical analysis could be streamlined for clarity.
7. The abstract conclusion should be more precise in recommending CMI as a clinical tool.
In Introduction:
8. State the NHANES dataset.
9. Emphasis on why previous markers of gallstone risk are insufficient would strengthen the
rationale for using CMI.
10. Provide a clearer hypothesis and aim of study at the end of the introduction to guide the
reader.
In Methods:
11. Improve the readability of inclusion and exclusion criteria.
12. The statistical methods, particularly the nonlinear modeling, should be briefly justified.
In Results:
13. Provide a table summarizing key statistical findings to improve readability.
14. which groups were most affected in subgroup analysis.
In Discussion:
15. Compare findings to previous studies on gallstone risk and metabolic indicators.
16. Biological mechanisms linking CMI to gallstones need further explanation.
17. The limitations section should consider self-reported data bias in gallstone diagnosis.
18. Discuss future longitudinal studies and clinical implications of CMI as a screening tool.
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