Review for 10.1186/s12876-025-04158-6 (2025)

Title: CTI as a Biomarker for Diarrhea in U.S. Adults: Insights from NHANES 2005–2010
Version: 3 Date: 21 Jun 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
1. Study Design Limitation: Cross-Sectional Nature
The study design is cross-sectional, limiting any inference of causality between CTI and chronic
diarrhea/constipation.
Authors should explicitly acknowledge this limitation earlier in the discussion and avoid any
suggestive causal language throughout the paper (e.g., "CTI leads to chronic diarrhea").
2. Lack of External Validation or Replication
The findings are limited to one population (U.S.) and one dataset (NHANES 2005–2010).
Highlight the need for external validation in different populations or newer NHANES cycles
(e.g., post-2010) to assess temporal consistency and generalizability.
3. Inadequate Justification for CTI Cutoff Values
No clear rationale for stratification or interpretation of CTI quartiles or threshold levels.
Authors should either conduct ROC curve analysis to determine optimal CTI cutoffs or explicitly
acknowledge the exploratory nature of the quartile classification.
4. Potential Misclassification of Diarrhea/Constipation
Definitions rely solely on self-reported Bristol Stool Form Scale (BSFS) and frequency
thresholds without clinical diagnosis.
Discuss the potential for recall bias or symptom misclassification and its impact on effect
estimates.
5. Overadjustment or Collinearity in Models
Model III adjusts for both diabetes and insulin resistance (via CTI), which may introduce
collinearity or overadjustment bias.
Sensitivity analysis excluding diabetes as a covariate (or modeling it as a mediator) could clarify
whether CTI's effect is independent of diagnosed metabolic disease.
6. Mediation Analysis is Mentioned but Not Described
The text states that mediation analysis was conducted but does not report any results or
methodology (e.g., mediator, method used, significance).
Either report the mediation results (e.g., via tables or supplementary material) or remove the
statement if not performed.
7. Incomplete Details on Statistical Testing and RCS Curves
The restricted cubic spline (RCS) analysis is mentioned without presenting the actual spline
plots or results.
Include figures for RCS or at least a supplementary figure to illustrate non-linear relationships
clearly.
8. Lack of Detailed Description of Missing Data Handling
Large numbers of exclusions were made due to missing data (e.g., 7,032 missing medical
history), but no method like multiple imputation was used or discussed.
Address the potential for selection bias due to complete-case analysis and explain why
imputation was not used.
9. Ambiguity Around Medication Use Analysis
The statin and metformin subgroup analyses are referenced, but no descriptive statistics or
interaction tests are provided.
Include interaction p-values and basic descriptive characteristics of medication subgroups to
support conclusions.
10. Redundancy and Repetition
Several parts of the discussion (e.g., explanation of insulin resistance, inflammation) are repeated
or overly detailed without adding new insight.
Streamline discussion to avoid redundancy and enhance focus on novel findings and
implications.
11. No Clarification on Directionality in Subgroup Findings
Subgroups with non-significant associations (e.g., diabetics, non-hypertensive individuals) are
discussed as “exceptions,” but effect directions and confidence intervals are not shown.
Provide a forest plot of subgroup analyses or a supplementary table to clarify consistency and
heterogeneity across groups.
12. No Mention of Dietary Intake or Microbiome Confounders
Given the gut health focus, the absence of dietary adjustment (e.g., fiber, fat, FODMAPs) and
microbiome consideration is a major confounder.
Explicitly mention this as a key unmeasured confounder and suggest it as a priority for future
studies.