Title: Cardiometabolic Index as a Predictor of Gallstone Risk: Evidence from NHANES 2017–
2020
Version: 1 Date: 24 Jan 2025
Reviewer's report:
Thank you for the opportunity to review the manuscript entitled "Association between
Cardiometabolic Index and Gallstones: Insights from NHANES 2017–2020." This cross-
sectional study presents a novel investigation into the relationship between the Cardiometabolic
Index (CMI) and gallstone prevalence, using data from the National Health and Nutrition
Examination Survey (NHANES). The analysis of 5,421 participants provides valuable insights
into how CMI, a composite marker of metabolic health, is associated with gallstone risk. The
study utilizes advanced statistical methods, including logistic regression and smoothed curve
fitting, to explore the nonlinear relationship between CMI and gallstones, revealing interesting
threshold effects.
Statistical Comments:
Clarification on Nonlinear Relationship: The study reports a nonlinear relationship between CMI
and gallstone risk, with a threshold effect observed at a CMI value of 0.85. While the analysis
is robust, it would be helpful to provide more detail on the methodology behind the smoothed
curve fitting and the choice of the threshold. A more detailed explanation of why this specific
threshold was chosen, and whether the findings are sensitive to other potential cutoff points,
would add to the transparency of the analysis.
Subgroup Analyses: The manuscript performs subgroup analyses to examine the relationship
between CMI and gallstones across different demographic and clinical categories. However, the
statistical power of these subgroup analyses could be strengthened by discussing the limitations
due to sample size in certain subgroups. For instance, were any subgroups underpowered, and
how might this influence the interpretation of the results?
Multicollinearity and Model Robustness: The study examines the relationship between CMI
and gallstone risk while controlling for various covariates. It would be beneficial to further
clarify the process of handling multicollinearity, especially given the potential overlap between
variables like BMI, waist-to-height ratio (WHtR), and triglyceride levels. Did the authors
consider checking for multicollinearity between these covariates and adjust accordingly?
Clinical Comments:
Clinical Implications of CMI as a Screening Tool: The study demonstrates a strong association
between CMI and gallstone risk, which could have significant clinical implications. The authors
should expand on how CMI could be integrated into clinical assessments to identify individuals
at higher risk of gallstones. For example, should CMI be measured routinely alongside other
traditional risk factors for CVD, such as lipid profile and blood pressure, to better identify at-
risk individuals?
Potential Role of Lifestyle Interventions: Given the relationship between CMI and gallstone
risk, the authors could discuss how lifestyle interventions aimed at improving CMI—such as
dietary modifications, weight loss, or exercise—might reduce the risk of gallstones. Could a
more holistic approach to managing metabolic health help prevent gallstone formation, and
should CMI be used as a monitoring tool in patients undergoing lifestyle interventions?
Gender-Specific Analysis: The study finds that the relationship between CMI and gallstone risk
is consistent across different demographic groups. However, given the higher prevalence of
gallstones in women, it would be interesting to explore whether gender-specific differences in
CMI could provide additional insights into risk stratification. Are there differences in how CMI
influences gallstone risk between men and women, and should gender-specific guidelines be
developed for CMI-based screening?
Further Investigation into the Mechanisms: While the manuscript focuses on the association
between CMI and gallstones, it would be valuable for the authors to discuss potential
mechanisms linking CMI to gallstone formation. For example, how might factors such as lipid
metabolism, insulin resistance, or systemic inflammation—components of CMI—contribute to
the pathophysiology of gallstones? A deeper exploration of these mechanisms would provide a
stronger biological basis for the observed association.
Comparison with TyG Index and Other Biomarkers: While the manuscript emphasizes the role of
CMI, the authors should also discuss other emerging biomarkers, such as the triglyceride-glucose
(TyG) index, which has gained increasing attention as a predictor of metabolic dysfunction and
cardiovascular risk. Recent studies, such as DOI: 10.1186/s12933-024-02392-y, DOI: 10.1038/
s41598-024-67883-0, and DOI: 10.1186/s12933-024-02241-y, suggest that TyG may be a strong
indicator of insulin resistance and metabolic risk. The authors are encouraged to compare CMI
with TyG and discuss how these indices could complement each other in clinical practice,
particularly for predicting gallstone risk and overall metabolic health.
Title: Cardiometabolic Index as a Predictor of Gallstone Risk: Evidence from NHANES 2017–
2020
Version: 1 Date: 24 Jan 2025
Reviewer's report:
Thank you for the opportunity to review the manuscript entitled "Association between
Cardiometabolic Index and Gallstones: Insights from NHANES 2017–2020." This cross-
sectional study presents a novel investigation into the relationship between the Cardiometabolic
Index (CMI) and gallstone prevalence, using data from the National Health and Nutrition
Examination Survey (NHANES). The analysis of 5,421 participants provides valuable insights
into how CMI, a composite marker of metabolic health, is associated with gallstone risk. The
study utilizes advanced statistical methods, including logistic regression and smoothed curve
fitting, to explore the nonlinear relationship between CMI and gallstones, revealing interesting
threshold effects.
Statistical Comments:
Clarification on Nonlinear Relationship: The study reports a nonlinear relationship between CMI
and gallstone risk, with a threshold effect observed at a CMI value of 0.85. While the analysis
is robust, it would be helpful to provide more detail on the methodology behind the smoothed
curve fitting and the choice of the threshold. A more detailed explanation of why this specific
threshold was chosen, and whether the findings are sensitive to other potential cutoff points,
would add to the transparency of the analysis.
Subgroup Analyses: The manuscript performs subgroup analyses to examine the relationship
between CMI and gallstones across different demographic and clinical categories. However, the
statistical power of these subgroup analyses could be strengthened by discussing the limitations
due to sample size in certain subgroups. For instance, were any subgroups underpowered, and
how might this influence the interpretation of the results?
Multicollinearity and Model Robustness: The study examines the relationship between CMI
and gallstone risk while controlling for various covariates. It would be beneficial to further
clarify the process of handling multicollinearity, especially given the potential overlap between
variables like BMI, waist-to-height ratio (WHtR), and triglyceride levels. Did the authors
consider checking for multicollinearity between these covariates and adjust accordingly?
Clinical Comments:
Clinical Implications of CMI as a Screening Tool: The study demonstrates a strong association
between CMI and gallstone risk, which could have significant clinical implications. The authors
should expand on how CMI could be integrated into clinical assessments to identify individuals
at higher risk of gallstones. For example, should CMI be measured routinely alongside other
traditional risk factors for CVD, such as lipid profile and blood pressure, to better identify at-
risk individuals?
Potential Role of Lifestyle Interventions: Given the relationship between CMI and gallstone
risk, the authors could discuss how lifestyle interventions aimed at improving CMI—such as
dietary modifications, weight loss, or exercise—might reduce the risk of gallstones. Could a
more holistic approach to managing metabolic health help prevent gallstone formation, and
should CMI be used as a monitoring tool in patients undergoing lifestyle interventions?
Gender-Specific Analysis: The study finds that the relationship between CMI and gallstone risk
is consistent across different demographic groups. However, given the higher prevalence of
gallstones in women, it would be interesting to explore whether gender-specific differences in
CMI could provide additional insights into risk stratification. Are there differences in how CMI
influences gallstone risk between men and women, and should gender-specific guidelines be
developed for CMI-based screening?
Further Investigation into the Mechanisms: While the manuscript focuses on the association
between CMI and gallstones, it would be valuable for the authors to discuss potential
mechanisms linking CMI to gallstone formation. For example, how might factors such as lipid
metabolism, insulin resistance, or systemic inflammation—components of CMI—contribute to
the pathophysiology of gallstones? A deeper exploration of these mechanisms would provide a
stronger biological basis for the observed association.
Comparison with TyG Index and Other Biomarkers: While the manuscript emphasizes the role of
CMI, the authors should also discuss other emerging biomarkers, such as the triglyceride-glucose
(TyG) index, which has gained increasing attention as a predictor of metabolic dysfunction and
cardiovascular risk. Recent studies, such as DOI: 10.1186/s12933-024-02392-y, DOI: 10.1038/
s41598-024-67883-0, and DOI: 10.1186/s12933-024-02241-y, suggest that TyG may be a strong
indicator of insulin resistance and metabolic risk. The authors are encouraged to compare CMI
with TyG and discuss how these indices could complement each other in clinical practice,
particularly for predicting gallstone risk and overall metabolic health.
Please review this paper.
user
Title: Cardiometabolic Index as a Predictor of Gallstone Risk: Evidence from NHANES 2017–
2020
Version: 1 Date: 24 Jan 2025
Reviewer's report:
Thank you for the opportunity to review the manuscript entitled "Association between
Cardiometabolic Index and Gallstones: Insights from NHANES 2017–2020." This cross-
sectional study presents a novel investigation into the relationship between the Cardiometabolic
Index (CMI) and gallstone prevalence, using data from the National Health and Nutrition
Examination Survey (NHANES). The analysis of 5,421 participants provides valuable insights
into how CMI, a composite marker of metabolic health, is associated with gallstone risk. The
study utilizes advanced statistical methods, including logistic regression and smoothed curve
fitting, to explore the nonlinear relationship between CMI and gallstones, revealing interesting
threshold effects.
Statistical Comments:
Clarification on Nonlinear Relationship: The study reports a nonlinear relationship between CMI
and gallstone risk, with a threshold effect observed at a CMI value of 0.85. While the analysis
is robust, it would be helpful to provide more detail on the methodology behind the smoothed
curve fitting and the choice of the threshold. A more detailed explanation of why this specific
threshold was chosen, and whether the findings are sensitive to other potential cutoff points,
would add to the transparency of the analysis.
Subgroup Analyses: The manuscript performs subgroup analyses to examine the relationship
between CMI and gallstones across different demographic and clinical categories. However, the
statistical power of these subgroup analyses could be strengthened by discussing the limitations
due to sample size in certain subgroups. For instance, were any subgroups underpowered, and
how might this influence the interpretation of the results?
Multicollinearity and Model Robustness: The study examines the relationship between CMI
and gallstone risk while controlling for various covariates. It would be beneficial to further
clarify the process of handling multicollinearity, especially given the potential overlap between
variables like BMI, waist-to-height ratio (WHtR), and triglyceride levels. Did the authors
consider checking for multicollinearity between these covariates and adjust accordingly?
Clinical Comments:
Clinical Implications of CMI as a Screening Tool: The study demonstrates a strong association
between CMI and gallstone risk, which could have significant clinical implications. The authors
should expand on how CMI could be integrated into clinical assessments to identify individuals
at higher risk of gallstones. For example, should CMI be measured routinely alongside other
traditional risk factors for CVD, such as lipid profile and blood pressure, to better identify at-
risk individuals?
Potential Role of Lifestyle Interventions: Given the relationship between CMI and gallstone
risk, the authors could discuss how lifestyle interventions aimed at improving CMI—such as
dietary modifications, weight loss, or exercise—might reduce the risk of gallstones. Could a
more holistic approach to managing metabolic health help prevent gallstone formation, and
should CMI be used as a monitoring tool in patients undergoing lifestyle interventions?
Gender-Specific Analysis: The study finds that the relationship between CMI and gallstone risk
is consistent across different demographic groups. However, given the higher prevalence of
gallstones in women, it would be interesting to explore whether gender-specific differences in
CMI could provide additional insights into risk stratification. Are there differences in how CMI
influences gallstone risk between men and women, and should gender-specific guidelines be
developed for CMI-based screening?
Further Investigation into the Mechanisms: While the manuscript focuses on the association
between CMI and gallstones, it would be valuable for the authors to discuss potential
mechanisms linking CMI to gallstone formation. For example, how might factors such as lipid
metabolism, insulin resistance, or systemic inflammation—components of CMI—contribute to
the pathophysiology of gallstones? A deeper exploration of these mechanisms would provide a
stronger biological basis for the observed association.
Comparison with TyG Index and Other Biomarkers: While the manuscript emphasizes the role of
CMI, the authors should also discuss other emerging biomarkers, such as the triglyceride-glucose
(TyG) index, which has gained increasing attention as a predictor of metabolic dysfunction and
cardiovascular risk. Recent studies, such as DOI: 10.1186/s12933-024-02392-y, DOI: 10.1038/
s41598-024-67883-0, and DOI: 10.1186/s12933-024-02241-y, suggest that TyG may be a strong
indicator of insulin resistance and metabolic risk. The authors are encouraged to compare CMI
with TyG and discuss how these indices could complement each other in clinical practice,
particularly for predicting gallstone risk and overall metabolic health.
assistant