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Response to comment from Dr. Sloan: ‘Look what's going down’

2012· letter· en· W2045071392 on OpenAlexaff
Robert P. Nolan, John S. Floras, Lamiaa A. Ahmed, Paula Harvey, Natalie Hiscock, H. Hendrickx, Duncan Talbot

Bibliographic record

VenueJournal of Internal Medicine · 2012
Typeletter
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversity Health NetworkWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineCriticismMetaphorHeart rateReading (process)Heart rate variabilityPower (physics)Cognitive psychologyAudiologyInternal medicinePsychologyLiteratureTheologyLinguisticsBlood pressurePhilosophy

Abstract

fetched live from OpenAlex

Dear Sir, We appreciate the Editorial Comment by Dr. R. P. Sloan 1 on our recent proof of principle study 2 of the cholinergic anti-inflammatory reflex. Nevertheless, we are concerned that four points of criticism raised in the Comment 1 signify inaccurate reading of our text. This obliges a response, if only to facilitate a clear and parsimonious reading of our paper. To continue with the Buffalo Springfield metaphor (to ‘For What It's Worth’*) entitling Dr. Sloan's Comment 1, we invite readers to focus on this song's refrain as they consider our reported results and to simply look what's going down amongst measures of inflammation when markers of vagal heart rate modulation increase over time. The first inaccuracy is that the Comment 1 informs readers that the results in our paper were derived from baseline-adjusted change scores in a marker of vagal heart rate modulation (RR high frequency [HF] power) during a stress challenge protocol. Accordingly, the Comment 1 asserts that it is an understatement to say that the study design and results are difficult to follow. In fact, no such change scores were utilized. It is noted three times in the study design and assessment protocol subsections of our paper that we evaluated the association between pro-inflammatory factors (hsCRP and IL-6) and markers of vagal heart rate modulation, ‘under a stable resting baseline condition’ (p.162); and again, ‘over the 6-min resting baseline…’ (p.163), and most specifically, ‘…the 10-minute adaptation period… was followed by a 6-min resting baseline interval, which is the focus of the current investigation.’ (p.163) 2. Our effort to account for how our text may have contributed to the above-noted problem alerted our team to two related inaccuracies in the Comment 1 that may help to explain how details in our text and in the Comment 1 began to diverge. The Comment notes that ‘the design appears to derive from a study previously published by (our) group…’ (P. 159) 1, and the only citation provided directs readers to our 2005 clinical trial of behavioural neurocardiac training 3. In fact, we explicitly acknowledge in the limitations paragraph of the Discussion that our investigation was a secondary analysis of data obtained from our 2010 trial of behavioural neurocardiac training 4, and the 2010 trial is cited throughout the Introduction, Methodology and Discussion sections as the source study for our investigation, and yet this key paper is never referenced in the Comment 1. The reader is informed in the Comment that our current study ‘…analysed the relationship between changes in HF power and changes in inflammatory markers…’ 1. This is partially correct and (surprisingly) it is more consistent with details of our 2005 trial 3. In contrast, markers of vagal heart rate modulation in our 2010 trial 4 included not only HF power, but baroreflex sensitivity and RR interval as well. Indeed, a compelling feature of our secondary analysis of that trial is that we observed an inverse association between change in each of these markers of vagal heart rate modulation and change in hsCRP—as the resting baseline measures were compared before versus after an 8-week period of behavioural intervention. Fourthly, the Comment 1 takes issue with the fact that the present substudy of our 2010 trial 4 collapsed subjects into one cohort. Accordingly, it is claimed that the ‘whole point of neurocardiac training…is vitiated’ (p. 159) 1. We suggest that this criticism misses the essential point of our substudy. Our aim was not to evaluate whether behavioural neurocardiac training versus autogenic relaxation evoked greater reduction in proinflammatory activity. Indeed, it is noted in the limitations section of our paper that the evaluation of change in inflammatory activity was not factored into the sample size or primary hypothesis of our 2010 clinical trial 4. Rather, the stated objective of the present substudy was to evaluate whether changes in markers of vagal heart rate modulation observed following either of the above-noted behavioural interventions was independently and inversely associated with changes in pro-inflammatory activity. Arguably, data must be obtained from studies such as our present proof of principle study before the potential superiority of any behavioural intervention in regulating inflammation can be evaluated in the context of a hypothesis-driven clinical trial. Looking forward, we trust that this response to the Comment 1 will focus on discussion and encourage further testing of the hypothesized cholinergic anti-inflammatory reflex. We stand behind our present findings that, to our knowledge, build significantly on previous research in evaluating, under controlled conditions, whether an increase over time in vagal heart rate modulation attenuates independently pro-inflammatory activity. No conflict of interest was declared.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.298
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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