Review for 10.1186/s12876-025-03950-8 (2025)

Title: Association of cardiometabolic index with gallstone disease and insulin resistance based
on NHANES data
Version: 1 Date: 24 Mar 2025
Reviewer's report:
Dear Editor,
Thank you for inviting me to review the manuscript entitled "Association between
cardiometabolic index and gallstones, as well as insulin resistance of gallstone patients: A cross-
sectional study."
This manuscript presents a cross-sectional analysis using NHANES data to explore the
association between the Cardiometabolic Index (CMI) and both gallstone disease (GSD) and
insulin resistance (IR) in patients with cholelithiasis. The authors applied robust statistical
methods, including restricted cubic spline modeling and multivariate logistic regression, to
examine these associations. The topic is clinically relevant and timely, given the growing burden
of metabolic disorders globally. However, several areas—particularly in presentation, statistical
justification, and clinical interpretation—require improvement to enhance the manuscript's
clarity and scientific rigor.
Clinical Comments:
Novelty and Relevance: The study provides useful insight by linking CMI—a relatively simple
index—to both GSD risk and IR. However, the clinical implications of using CMI as a screening
tool for GSD or IR are not thoroughly discussed. Please elaborate on its potential utility in
practice.
Gallstone Disease Definition: The diagnosis of GSD is based on self-reported history rather
than imaging or clinical confirmation. This introduces recall bias and misclassification. Please
acknowledge this limitation more prominently in the discussion.
Female-Specific Findings: The finding that CMI-GSD association is stronger in women is
interesting. The hormonal and metabolic explanations offered are valid but would benefit from
references to recent literature on estrogen’s role in bile metabolism and gallbladder motility.
Clinical Use of Cut-off Values: The paper identifies a CMI cut-off (#0.40) predictive of IR in
GSD patients. Please clarify how this cut-off compares with other clinical tools or indices (e.g.,
TyG, BMI, HOMA-IR) for screening or early intervention.
Comparison with Other IR Indicators – TyG Index:
The manuscript would benefit significantly from a comparative discussion of CMI versus other
recent insulin resistance indices, particularly the Triglyceride-Glucose (TyG) index, which has
been gaining strong validation in recent studies as a surrogate marker for IR. The TyG index is
simple, widely used, and considered more stable than insulin-based indices in large population
studies. The authors are encouraged to compare the predictive power of CMI against TyG and
discuss their respective strengths and limitations in assessing IR, especially in the context of
metabolic-related diseases like GSD. This comparison would enhance the clinical utility and
contextual depth of the manuscript.
The following recent studies can be cited, and their content can be reflected in this comparative
analysis:
DOI: 10.1186/s12933-024-02241-y
DOI: 10.1186/s12933-024-02392-y
Statistical Comments:
Use of Restricted Cubic Spline (RCS): The use of RCS is commendable, but details about
knot placement and choice should be reported in the Methods section for transparency and
reproducibility.
Subgroup Interaction Analysis: While subgroup differences (e.g., gender effect modification)
are reported, interaction p-values should be provided clearly for each subgroup to validate
significance claims.
ROC Analysis and CMI Cut-off: The AUC (0.79) indicates good predictive ability, but the
confidence interval should be interpreted carefully. Please clarify how the 0.40 cut-off was
derived (Youden index or another method?).
Model Justification: Logistic regression models were constructed (Model 1–3), but there is
no discussion on multicollinearity among predictors or goodness-of-fit statistics (e.g., AIC,
Hosmer-Lemeshow). Consider including these or explaining your variable selection strategy.