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Thank you for your thorough and thoughtful revision of the manuscript. You have carefully addressed the methodological, analytical, and interpretative issues raised in the previous round, including clarification of the clinical rationale for rhabdomyolysis in AIS, greater transparency around control selection and confounder adjustment, sensitivity analyses by CK strata, clearer handling of multiple testing and subgroup power, and explicit discussion of DAMA and the in-hospital outcome window.
The revised version now presents a coherent and balanced interpretation of the data, appropriately framing rhabdomyolysis as a marker of systemic severity rather than an independent causal determinant of outcome. Reviewer 2 is satisfied with the changes and recommend acceptance, and I agree that the manuscript now meets the journal’s standards for scientific and methodological rigor.
I am pleased to inform you that your manuscript is accepted for publication. Congratulations, and thank you for choosing our journal for your work.
Thank you for addressing all of the issue
Thank you for addressing all of the issue
Thank you for addressing all of the issue
Thank you for addressing all of the issue
Thank you for your submission. Both reviewers find the topic clinically relevant but identified major issues that must be addressed:
1) Rationale & Novelty – Clarify the pathophysiological or clinical rationale linking rhabdomyolysis with ischemic stroke. Ensure the hypothesis is explicit and supported by literature (e.g., immobilization, statin use, infection).
2) Methods:
-Provide justification for patient exclusions (e.g., MI cases).
-Detail control selection (“Python-based sampling”) for reproducibility.
-Reconsider confounder adjustment strategy beyond univariate significance.
-Consider sensitivity analysis (e.g., CK >5000 U/L).
-Provide clearer variable definitions and metadata in supplements.
3) Results & Interpretation:
-Acknowledge subgroup underpowering and potential type I error.
-Avoid overstating independence of rhabdo effects when confounding is possible.
-Clarify whether “discharge against medical advice” is an outcome marker.
4) Presentation:
-Improve readability (grammar, typographical consistency, abbreviations).
-Strengthen figure legends (especially forest plots) and table clarity.
-Expand discussion to address potential causal pathways and competing explanations (e.g., infection).
Please undertake a thorough revision. Without a stronger rationale and improved methodological rigor, the manuscript will not be suitable for publication.
**PeerJ Staff Note:** Please ensure that all review, editorial, and staff comments are addressed in a response letter and that any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
This is retrospective study looking at the associated co-morbidities and differences in clinical outcome between acute ischemic stroke patients with rhabdomyolysis and without rhabdo. The authors report increased diabetes mellitus, coronary heart disease, acute kidney injury, hypoalbuminemia, increased myoglobin and troponin I, and increased incidence of infections in the rhabdo group.
The writing, analysis, and data representation are okay.
This is a retrospective study.
The design itself is fine.
The rationale for the choice of study groups is not strong.
Major concerns:
1. The fundamental link between ischemic stroke and rhabdomyolysis seems flimsy. Is there any evidence to show that the underlying pathology that causes ischemic stroke can also lead to rhabdomyolysis? Else, it seems to be a random co-morbidity that is seen in a few ischemic stroke patients. I think the rationale for study should be made stronger.
2. Rhadbomyolysis group also presents with a range of other co-morbidities. Therefore, what caused what is not logically clear. It also looks like infection could be an important contributor here. If infection is the common source of poor outcomes, shouldn’t that be prioritized over rhabdo to predict clinical outcome.
Minor points:
1. The authors say, “there were no significant differences between the RML Group and the Control Group with respect to sex (72.60% vs. 72.60%, p=1.000) and median age (80 [69-85] vs. 80 [69-85.25], 100 p=0.946).” Is this a finding? This seems to be due to the selective matching of control group with the Rhabdo group.
2. Is “discharge against medical advice” always an indicator of poor outcome?
1. Several sentences are overly long or contain typographical inconsistencies (e.g., “p< 0.001” with spaces inconsistently, “CK f 1000 U/L” where formatting seems broken). I recommend proofreading or professional editing to improve readability.
2. Figures are relevant and appropriately labeled, though Figure 2’s forest plot requires clearer legends and consistent formatting of odds ratios and confidence intervals. Tables are informative but some abbreviations (e.g., “UA”, “Alb”) should be spelled out in legends for broader accessibility.
3. The introduction gives an adequate overview, but the literature review could be expanded. For example, prior observational studies linking rhabdomyolysis with stroke-related immobilization, statin use, or infection deserve deeper contextualization. Some references are recent and relevant, but inclusion of more large-scale or systematic reviews would strengthen the background.
4. The manuscript is generally self-contained, but the rationale for excluding patients with myocardial infarction (n=10) could be better justified in the Methods.
1. The study question is defined but could be sharpened. While the authors investigate outcomes in AIS patients with rhabdomyolysis, the hypothesis (whether RML independently predicts outcomes) is somewhat buried in the text rather than explicitly stated.
2. The definition of rhabdomyolysis (CK >1000 U/L) is reasonable, but no sensitivity analysis was performed for higher thresholds (e.g., CK >5000 U/L), which may alter interpretation.
3. The use of “Python-based statistical sampling” to generate controls is briefly mentioned, but the reproducibility of this method is not clear without more detail or shared code.
4. Confounder adjustment in the logistic regression seems incomplete; only variables significant in univariate analysis were included. This approach risks residual confounding.
5. Appropriately obtained (Project No. 2024-P-04), and informed consent exemption is justified given the retrospective nature.
1. The authors conclude that RML is not an independent predictor but contributes synergistically with other factors. This is plausible, but subgroup analyses (Figure 3) are underpowered, particularly the NIHSS >15 subgroup (n=5). Confidence intervals are very wide, making the results unstable.
2. The raw data file is provided, but the supplementary material lacks detailed metadata (e.g., variable definitions, missingness handling). This reduces transparency and reproducibility.
3. Multiple comparisons increase the risk of type I error, yet no adjustment method (e.g., Bonferroni, FDR) is mentioned.
4. Some are acknowledged (retrospective, single-center), but others are underemphasized. For example, the absence of follow-up beyond discharge (e.g., 90-day functional outcomes) limits the clinical implications.
This study addresses an underexplored but clinically relevant issue: the interplay between rhabdomyolysis and stroke outcomes. The dataset is impressive, and the findings are potentially impactful for acute stroke care. However, presentation and methodological rigor need improvement before publication.
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