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Thank you for the comprehensive revisions you have made in response to reviewer 3. The manuscript is now ready for publication.
[# PeerJ Staff Note - this decision was reviewed and approved by Jeremy Loenneke, a PeerJ Section Editor covering this Section #]
Thank you for revising your manuscript in response to reviewers 1 and 2, who were unfortunately unavailable for re-review. We have therefore secured the opinion of a third independent expert, who has recommended a number of revisions, including changes that will improve the statistical reporting and transparency of data analysis. When submitting your revised manuscript, please include a response to this reviewer that quotes the entirety of the report and responds to every comment in turn.
Figure legends
Page 9, Fig. 2 legend (lines ~320–325): Explicitly state SD1 and SD2 units (milliseconds).
Page 9, Fig. 3 legend (lines ~335–340): Add a note that HR/LF is a dimensionless index derived as HR (beats·min⁻¹) ÷ LF power (ms²), used comparatively as a sympathetic marker.
Control group generalizability
Page 12, Limitations (lines ~441-448): Add a sentence acknowledging that the use of an “active” control group (rather than sedentary) may limit generalizability compared to conventional exercise-training studies.
Consistency in terminology and abbreviations
Page 2, Abstract (lines ~25-35): Ensure all abbreviations (HRR, HRV, CG) are defined at first mention.
Throughout manuscript: Standardize the wording (“fitness functional training” vs. “Fitness Functional Training”) and use consistently in manuscript.
Non-causal language
Page 2, Abstract (lines ~63-65) and Page 11-12, Discussion/Conclusion (lines ~408-474): Please re-check for residual causal phrasing. All statements should be framed as "associations" or "may reflect".
GLM transparency
Page 7, Statistical analyses (lines ~260-270): Add a short table or paragraph specifying which distribution/link function (normal or gamma, identity link) was selected for each of your main outcome variables (eg. HRR, SD1, SD2, HR/LF).
Multiple comparisons
Page 7, Statistical Analyses (lines ~272-277): Insert a justification for LSD post-hoc tests, eg. “due to small number of planned pairwise contrasts; primary inferences rely on GLM main effects with covariate adjustment.”
Effect-size reporting
Page 8-9, Results (lines ~287-311): Alongside standardized β, please add 95%CIs .
HRV processing consolidation
Page 5, HRV analysis (lines ~192-204): Add a one-paragraph to the effect of “signal-processing summary” (sample rate, interpolation/detrending if used, artifact threshold <1%, Hanning window, AR order 16, band definitions, segment length, Kubios version).
Confounder handling visibility
Page 8-9, Results (lines ~287-295): At first mention of adjusted results, add to the effect of “GLM adjusted for age, BMI, TT, R, and HR/LF, as specified in Methods.”
Sympathovagal interplay
Page 10, Discussion (lines ~360-365): Add a bridging sentence, something to the effect of “Similar SD1 despite elevated HR/LF in FFG may reflect compensatory vagal reactivation during sustained sympathetic outflow.”
Training volume vs. intensity
Page 12, Discussion (lines ~447-456): Add a sentence something to the effect of “It is likely that modality, intensity, and volume all contributed to recovery kinetics; our cross-sectional design cannot isolate their independent effects.”
Data availability
Page 13, Data Availability statement: please confirm inclusion of a working link to your de-identified dataset.
Ethics wording
Page 4, Ethics (lines ~137-144): the authors should explicitly state, “All participants provided written informed consent” within the Ethics paragraph itself.
I recommend the following:
Provide a supplementary results table reporting medians (IQR) per group, adjusted β (95%CI), and p-values for HRR (1–5 min), SD1, SD2, and HR/LF.
Add a disclaimer in the Conclusion (Page 12, lines ~470-474): something to the effect of “These findings describe autonomic recovery patterns and are not designed to adjudicate cardiovascular risk.”
Standardize figure formatting: define boxplot elements (median, IQR, whiskers, outliers) and confirm consistent decimal precision across axes.
Reviewer 2 is particularly concerned about the lack of a control group.
**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.
Strengths:
The manuscript is well-structured, with clear objectives and a logical flow.
Professional English language is used throughout, and the text is unambiguous.
Figures and tables are relevant, high-quality, and well-labeled.
Suggestions for Improvement:
Abstract: The conclusion could be more concise. Replace "Lastly, results suggest..." with a stronger summary (e.g., "These findings indicate...").
Introduction:
Expand the rationale for comparing FFT and endurance training by citing recent trends in high-intensity training (e.g., Thompson, 2023).
Clarify the novelty gap: While Morlin et al. (2023) compared HRR, this study adds HRV analysis. Emphasize this distinction early.
Methods:
Specify the Polar® RS800CX’s validation protocol (e.g., Barbosa et al., 2016) to strengthen reproducibility.
Justify the 48-hour activity cessation (cite Timón et al., 2019 for recovery timelines in FFT).
Strengths:
Rigorous cross-sectional design with appropriate inclusion/exclusion criteria.
Ethical approval and informed consent are documented.
Suggestions for Improvement:
Sample Size:
The FFG (n=15) is smaller than EG (n=23). Address potential power limitations by discussing post-hoc power analysis (e.g., "Despite the smaller FFG, effect sizes were large enough to detect differences.").
Confounding Variables:
Age and BMI differed between groups. While adjusted statistically, acknowledge residual confounding as a limitation.
Training Volume:
EG trained ≈17h/week vs. FFG’s 7h. Discuss how volume disparities might influence autonomic recovery (cite Cabral-Santos et al., 2016 on intensity vs. volume).
Strengths:
Robust statistical analysis (GLM with gamma distribution, AIC, LSD post-hoc).
Raw data and HRV methodology (Kubios software) are well-documented.
Suggestions for Improvement:
HR/LF Index:
Justify using HR/LF as a sympathetic marker with additional citations (e.g., Tanque et al., 2021).
Figures:
Figure 1: Add error bars for quartiles to clarify dispersion.
Figures 2–3: Label y-axes with units (ms for SD1/SD2; bpm for HR/LF).
Discussion:
Reconcile conflicting literature on arterial stiffness (e.g., Zuo et al., 2022 vs. Hasegawa et al., 2018).
Address why FFG’s sympathetic activity remained elevated despite similar SD1 (cite Tulppo et al., 2011 on sympathovagal interplay).
Major Strengths:
Novel comparison of HRR and HRV in FFT vs. endurance athletes.
Clinically relevant implications for FFT practitioners’ cardiovascular monitoring.
Critical Weaknesses:
Cross-Sectional Limitation: Avoid causal claims (e.g., "FFT causes slower HRR"). Reframe as "associations."
Overstatement of Clinical Impact: Tone down claims about "vulnerability to diseases" without longitudinal evidence.
Suggested Revisions:
Introduction:
Add: "While Morlin et al. (2023) reported impaired HRR in FFT, the autonomic mechanisms (e.g., HRV) remain unexplored."
Methods:
Clarify: "R-R intervals were processed using Kubios HRV (v3.3.1) with medium artifact threshold (<1% removal; Tarvainen et al., 2014)."
Discussion:
Add: "Persistent sympathetic activity in FFG may reflect metaboreflex activation (Boyes et al., 2023), but longitudinal studies are needed."
The manuscript presents valuable insights into the autonomic nervous system (ANS) through the non-linear analysis of Poincaré plots and the heart rate recovery (HRR) responses, specifically examining the results of maximal running exercise followed by a recovery process. However, despite the original proposal's focus on comparisons among various fitness group levels and exercise modalities, several methodological issues raise doubts about the conclusions drawn regarding this topic.
An observational cross-sectional study should reveal group differences regarding the time moment depicted in the study. In this case, it is not clear at all. Although EG and FFG partially differed in the volume and type of exercise performed during their training process and their total training period before the study, the CG did not behave as a control. The findings from the maximal incremental test showed significantly higher time to exhaustion, along with a faster or similar recovery process, as evaluated through HRV assessments, compared to EG and FFG, raising questions about the results. Although the higher VO2peak for the EG compared to CG (expected, given that it is group-dependent), a similar response between CG and FFG indicated that CG could not represent this role in the present study. From this perspective, it may be possible to understand the reasons behind some of the results found by the authors.
Besides, these results could be influenced by a methodological choice that is not well justified in this context. Based on Cole et al. (1999), the authors performed an active cool-down recovery to determine and expect the well-known physiological processes of vagal reactivation and sympathetic withdrawal, which lasted over 5 minutes. Although performed by these authors, would such an active cool-down protocol not introduce variability that may obscure precise HRV dynamics? Comparing different groups may mask the distinct natural vagal reactivation responses of these groups. Since active recovery helps clean metabolite accumulation, such as lactate concentration, and subsequently accelerates vagal reactivity, this process should vary among the groups studied. The actual scenario does not represent this expectation.
Aside from the misleading definition of the control group regarding their baseline results, the subsequent recovery process supports this hypothesis. Even without considering active recovery as a confounding factor, a similar vagal reactivation between CG and EG regarding HRR and between FFG and CG concerning SD1 over 5 minutes makes it difficult to understand how CG could be considered less trained than the fitness groups. The same might be debated regarding the HR/LF ratio, which demonstrates higher persistence from sympathetic system activation in FFG but not in CG. In this case, illustrating the differences between FFG and EG does not hide the similar activation between EG and CG.
Additionally, the authors conducted a GLM analysis to identify differences among the groups, but there was no mention of intragroup analysis. Such an approach could reveal the temporal progression (from minute 1 to minute 5) regarding the ANS parameters assessed for each group. Since the protocol did not appear sensible enough to elicit significant differences between the control and fitness groups, one plausible way to justify these results might be to concentrate on within-group comparisons.
Unfortunately, these inconsistencies prevented the authors from effectively discussing the results, which weakened the rationale and the manuscript's overall impact.
The likely use of an active cool-down recovery process may mask the significant differences between the groups.
The participants in the Control group, as well as those in the fitness groups, did not accurately represent their respective baseline status.
I suggest reconsidering the control group and rethinking its usefulness.
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