Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)?

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Review applsci-3369540-peer-review-v1

The paper, "Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)?", examines changes in electromyography (EMG) patterns and gait parameters following multilevel surgical treatment in individuals with cerebral palsy (CP). The study focuses on EMG indices, including the EMG Deviation Index (EDI), EMG Profile Score (EPS), and Dynamic Motor Control Index (DMC), to evaluate their potential in predicting surgical outcomes. By analyzing systematic changes in EMG post-surgery, the research highlights DMC as a promising predictor of treatment success, offering valuable insights into motor control improvements in CP patients.

Minor Revision Suggestions

• Lines 43-45: Provide a more detailed rationale for the importance of eliminating subjectivity in EMG interpretation to strengthen the methodological justification.
• Lines 97-110: Clearly articulate the study's hypotheses and emphasize their clinical significance to ensure the objectives are well-defined and impactful.
• Lines 377-381: Perform an adjusted analysis to account for potential surgical bias, which will enhance the robustness of the results.
• Include a discussion on why specific muscles, such as the tibialis anterior and gastrocnemius lateralis, showed no significant EMG changes post-surgery. This will provide greater context and address any unexplained findings.
• Suggest concrete clinical pathways for integrating DMC and other EMG indices into practice to predict surgical outcomes more effectively.

Overall Evaluation: The article makes a valuable contribution to understanding the role of EMG and motor control indices in assessing surgical outcomes for patients with cerebral palsy. To maximize the paper’s clarity and impact, the authors should address confounding factors, improve the articulation of their results, and provide deeper insights into clinical applications. These revisions will enhance the manuscript’s relevance and significance for the scientific and clinical community.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript titled "Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)?" investigates changes in EMG patterns and gait quality in CP patients following surgery, utilizing advanced clustering techniques and indices. While it is well-written and provides valuable insights, several concerns need to be addressed before it is ready for publication:

1.     The discussion highlights that proximal surgeries resulted in higher responder rates than distal surgeries, but the manuscript does not adequately address how this variability affects the results and conclusions.

2.     Despite no significant changes in DMC post-surgery, it is proposed as a predictor of outcomes. This inconsistency needs a more thorough explanation in the discussion.

3.     Factors such as spasticity levels and growth, which could significantly impact EMG and gait outcomes in a diverse cohort, are not sufficiently addressed in the manuscript.

4.     The influence of patient age on surgical outcomes, a critical consideration for CP treatment, is not explored.

5.     While EMG data is extensively analyzed, the manuscript lacks details on preprocessing and noise handling methods, which are essential for ensuring reproducibility.

6.     The potential application of EMG indices such as DMC and EDI for real-time clinical feedback or intraoperative decision-making is not discussed, limiting the practical relevance of the findings.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This is an interesting study proposing to investigate the utility of EMG in the prediction of surgery outcome in CP patients. Overall, the methods and results look sound and are well presented. The reviewer has few comments that would like to see addressed:

1) Some of the tables showing the value of the metrics pre- and post-surgery (e.g. table 7) can potentially be presented as bar charts (with indication of error bars and statistical significance between sub-groups) for a possibly better legibility. 

2) A line or two on the cerebral palsy (e.g., definition, prevalence, important facts, etc.) in the introduction section would be helpful to readers new to this disorder.

3) Can the authors comment on whether EMG artifacts were present in the data analyzed and if so how they were dealt with? It was not clear if the signal processing addressed any noise/artificial reduction/removal from the EMG signals before signal envelopes were estimated. It was not clear neither if this was addressed in their previous work (i.e., "Rectus femoris electromyography signal clustering: Data-driven management of crouch gait in patients with cerebral palsy") since the authors reference this work.

4) Figure 2: What does SPM(t) show exactly? Is SPM(t) an average across data from all patients as shown? Can the authors further explain why/how SPM was used to compare changes over a gait cycle?

5) "The examined EMG indices, EDI and EPS, basically describe EMG patterns, and tend to become more typical (Table 3) as gait becomes more typical after the surgery (gait parameters, Table 2): Can you define "typical" (perhaps using expected range of values?).

Author Response

Please see the attachment

Author Response File: Author Response.pdf