52 e-Letters

published between 2016 and 2019

  • Still in doubt about the efficacy of Cognitive Functional Therapy for chronic nonspecific low back pain. Letter to the editor concerning the trial by O’Keeffe et al. 2019.

    We congratulate O’Keeffe et al. [1] for their research on the comparative efficacy of Cognitive Functional Therapy (CFT) and physiotherapist-delivered group-based exercise and education for individuals with chronic low back pain (CLBP). Their study shows that “CFT can reduce disability, but not pain, at 6 months compared with the group-based exercise and education intervention”. The CFT approach is very promising and has caught the attention and interest of a number of clinicians worldwide in the management of non‐specific disabling CLBP. The study by O’Keeffe et al. [1] has methodological strengths compared to a previous clinical trial by Vibe Fersum et al. [2,3] such as a higher sample size which means it is less vulnerable to type-II error. Nonetheless, some shortcomings threaten substantially the risk of bias and type I error that are worthy of further discussion.

    The first is the choice of three physiotherapists for delivering both interventions in this trial. This aspect was considered by O’Keeffe et al. [1] as a strength of the study because it arguably minimized differences in clinicians’ expertise and communication style. Notwithstanding, this fact could also have decreased the treatment effect on the control group. It is important to remember that the trial was performed by the research group that not only developed CFT but also has trained the physiotherapists on such an approach, and thus the enthusiasm and motivation to apply the intervention on the CFT...

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  • Drugs do not Level the Playing Field

    Here is my simple response to this absurd proposal. If drugs help those who are not as genetically advantaged to be more competitive with those who are, shall we prohibit the genetically advantaged from taking them? Otherwise, you create the situation where all athletes must take these drugs just to maintain the status quo. Athletes who prefer not to use drugs would suffer the most. Since drug use monitoring will be required anyway for safety, let's prohibit their use as much as possible. Allowing their use only benefits the pharmaceutical companies who sell the drugs. Sports would becomes less about athletic ability and more about who can come up with the best drug formula for competitive success.

  • How does BDNF affect cognitive function during exercise?

    Dear editor,
    We have read with great interest the article by Wheeler et al1 showing distinct effects of exercise with and without breaks in sitting on cognition. In this study, they also demonstrated that both activity conditions increase serum brain-derived neurotrophic growth factor (BDNF) levels. Although we highly appreciate the efforts of the authors to explore potential mechanisms, we suggest that the followings need to be addressed.
    BDNF is an important member of the neurotrophic factors family which enhances neuronal development and plasticity. It is synthesized as the N-glycosylated precursor (brain-derived neurotrophic factor precursor, proBDNF), and secreted into cell matrix processed by Golgi complex. Additionally, BDNF is a novel kind of myokines produced by skeletal muscle after the muscle contraction immediately. Hayashi and coworkers2 observed that both exercise and electrical muscle stimulation could increase the mRNA and protein expression of BDNF in skeletal muscle of rats. In addition, exercise could also enhance gene expression of BDNF and other neuroprotective factors in hippocampus via peroxisome proliferator-activated receptor gamma coactivator-1α-fibronectin type III domain-containing protein 5/irisin (PGC-1α-FNDC5/irisin) pathway.3
    BDNF has been reported to play a pivotal role in the improvement of learning and memory function, which might be associated with the phosphorylation of tropomyosin-related kinase B (TrkB) in cognitive-...

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  • The ACWR model presented in the IOC consensus is flawed and not validated

    The BJSM recently rejected our request of retraction or errata corrige of the editorials by Blanch and Gabbett(1) and Gabbett (2) presenting the relation between the Acute:Chronic Workload Ratio (ACWR) and likelihood of injuries. The preprint and a list of some of the errors presented in that figure can be found here: https://osf.io/preprints/sportrxiv/gs8yu/. In challenging our request, it was underlined several times by the Editor in Chief of BJSM that the “model” was presented as illustrative only, and this seems to make errors acceptable like if the editorials are a “safe zone” where for illustrative purposes it is possible to bend and even break scientific rules and methods, presenting models using unpublished and uncontrollable data.

    However, the reason of this communication is to warn the members of the consensus (and readers) that the ACWR model published in the IOC consensus(3) as a validated model has in fact not been validated at all: [page 1034] “The model has currently been validated through data from three different sports (Australian football, cricket and rugby league)(187)”. The reference 187 is one of the two editorials(1) for which we asked the retraction. So on one side the Editor in Chief insists that it is just an illustrative (flawed) model, but on the other side the same Editor in Chief, co-author (with one of the proponents of the model) of the IOC consensus wrote and published that it...

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  • Continued Question About As-Treated Analysis

    Dear Drs. McGuine, Hetzel, and Kliethermes,

    Thank you for your thorough response to my initial comment.

    I am wondering if you could help me understand the new AE-level as-treated analysis you have done in response to Point 2. This accounts for all non-compliant AEs among all athletes, correct? If I understood you correctly, there were somewhat more than the 711 non-compliant AEs reported in the paper and which you reported in your response to Point 4, correct?

    What would be very helpful to see is a.) the number of AEs and b.) the number of SRCs that occurred during those AEs for each of the following groups when considering any non-compliant AE, not just ones from athletes who suffered an SRC while non-compliant or were non-compliant >50% of the time:

    Assigned HG/Did Not Wear:
    Assigned HG/Did Wear:
    Assigned No HG/Did Not Wear:
    Assigned No HG/Did Wear:

    Thank you again for your thorough response.

  • Letter to the editor

    After careful appraisal and following our own investigations, we are concerned that the article “Is interval training the magic bullet for fat loss? A systematic review and meta-analysis comparing moderate-intensity continuous training with high-intensity interval training (HIIT)” [1] may have some data extraction and analysis errors that warrant further review by the editor and authors, and which more concerningly, may impact the original conclusions of the article.

    We were initially concerned about the reported results within the Thomas et al. paper [2], particularly the biological plausibility of a mean between-group fat-loss difference of 13.44 kg over 12 weeks. Given that the authors did not report any study-level data, we decided to investigate the effect size within this paper. However, this study [2] did not report any fat mass data, only % body fat data. Given that the authors of the review [1] reported “When studies provided insufficient data for inclusion in the meta-analysis (five studies), the corresponding authors were contacted via email to determine whether additional data could be provided; however, no corresponding authors responded.”, it is unclear how an unpublished mean difference of -13.44 kg in favour of HIIT/SIT could be presented within the fat mass analysis of this review. Furthermore, when reviewing another of the included studies [3], we found that fat mass data were reported, but not included in the current meta-analysis [1]. Given the m...

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  • Response to the comments for the paper: Does soccer headgear reduce the incidence of sport-related concussion? A cluster, randomised controlled trial of adolescent athletes.

    To: The British Journal Sports Medicine

    We are grateful for Dr. Binney’s interest in our study and his consideration of a portion of the results presented in the manuscript.

    Listed below are our responses to each of the concerns raised in the letter.

    1. In the as-treated analysis you have a very strange result. Your multivariate risk ratio (which is actually a rate ratio) is 0.63 for everyone overall, 0.64 for females, and 0.93 for males. The result for everyone should be between the results for males and females. Can you please clarify how you got these results, including the exact model(s) you used and how you calculated the rate ratios? Did you use a group*sex interaction term to get the sex-specific results?

    Response: We thank you for noticing the mathematical inconsistency in Table 4 rate ratio results for the as-treated analyses. You are correct that if these results were from one model, the overall rate ratio estimate would need to be in-between the male/female estimates. We should note that these were actually 3 separate mixed-effects models: (1) the overall model adjusting for all variables including sex, (2) female sub-group model adjusting for all variables –excluding sex, and (3) male sub-group model adjusting for all variables –excluding sex. We apologize that the footnote in the table is unclear in this regard. We did attempt to use interaction models for this analyses, but did not achieve consistent convergence. As such, we opt...

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  • Concerns About As-Treated Analysis

    Dear Dr. McGuine et al,

    I'd like to commend you on running a large RCT on such an important topic (assessing the purported effectiveness of concussion-reduction technologies). Unfortunately I have some concerns about some aspects of your data and analysis, particularly the as-treated analysis in Table 4and your reported adherence numbers. I am hoping you can clarify these concerns and re-do parts of your analysis.

    1. In the as-treated analysis you have a very strange result. Your multivariate risk ratio (which is actually a rate ratio) is 0.63 for everyone overall, 0.64 for females, and 0.93 for males. The result for everyone should be between the results for males and females. Can you please clarify how you got these results, including the exact model(s) you used and how you calculated the rate ratios? Did you use a group*sex interaction term to get the sex-specific results?

    2. How you defined the as-treated group is concerning. You state that you only re-classified a subject if they spent >50% of their time in their non-assigned group OR if they were concussed while in their non-assigned group. This approach will bias the results of your as-treated analysis as you are deliberately misclassifying the AEs of people who do not get hurt and the non-concussed AEs of those who do. You need to classify every AE, rather than each athlete, as headgear or no headgear and repeat the as-treated analysis. Otherwise this analysis is highly questionable and...

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  • Response to 'A few unanswered questions'

    Dear Dr. Anoop Balachandran

    We would like to thank you for your insightful and interesting comment.

    Regarding the first point, we presented the 28.5% to illustrate the relative difference in total absolute fat (kg) change between interventions, so the reader could have information about the relative difference between groups. We would like to highlight that it was only possible to perform this analysis using the within group changes, since the change between group analysis was showed in absolute values.

    About the second point, it was not our purpose to analyse lean body mass; however, we agree that this topic is very important for health and athletic performance purposes. This is an unanswered question and we are performing studies to test the effects of interval training on lean body mass to help shedding light in the topic.

    Best regards.

  • Accounting for Multiple Testing Calls into Question the Significance of these Results

    In this article the authors discuss their analysis of 21 female and 22 male athletic events. Testing all 43, they find 3 events significant with p<0.05. When testing 43 events, the expectation is that a well-calibrated statistical test will produce 2 false positives with random data, on average, due to the definition of the p-value. The odds of producing 3 false positives are also rather high; for normally distributed simulated data under the null, I found 3 or more false positives approximately 1/3 of the time such an analysis is performed, see here for a simulation notebook: https://github.com/davidasiegel/False-Positive-Rate-for-Multiple-Tests-i....

    This is why adjustments for multiple comparisons needs to be performed. It was neglected in their initial study and neglected again in this study. In the 2017 study they state, "These different athletic events were considered as distinct independent analyses and adjustment for multiple comparisons was not required." This doesn't make sense to me; if the analyses are distinct, then all the more reason to correct for multiple comparisons. If a Bonferroni correction were performed, none of the p-values would test significant at the level of the study (p<0.05/43 = 0.001). Therefore I do not see why there is any reason to reject the null hypothesis for any of these results.


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