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Record W7065424542

The effect of spinal manipulative therapy on heart rate variability and pain in patients with persistent or recurrent neck pain

2022· dissertation· en· W7065424542 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Archive (Karolinska Institutet) · 2022
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsHeart rate variabilityHeart rateAutonomic nervous systemQuality of life (healthcare)Randomized controlled trial
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: Persistent or recurrent neck pain is a common reason to seek healthcare. Manual therapy in
\ncombination with exercises is recommended by clinical guidelines for this patient group. Autonomic dysregulation with reduced parasympathetic activity, increased sympathetic activity, and impaired conditioned pain modulation is seen in a range of chronic pain conditions such as persistent or recurrent neck pain. An immediate response to spinal manipulative therapy of the autonomic nervous system has been observed, but the evidence is of very low to moderate quality and the underlying mechanisms are unknown. Examining the long-term effect of spinal manipulative therapy on the autonomic nervous
\nsystem, pain, and disability is thus relevant, and measures of heart rate variability can provide
\nan objective measure of this relationship.
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\nThe aim of this project was to examine the effects on pain, disability, and heart rate variability of adding spinal manipulative therapy to home stretching exercises over a period of two weeks. Further, an explorative investigation into the relationship between changes in pain and changes in heart rate variability was undertaken. In addition the temporal stability and responsiveness of the conditioned pain modulation measurements was also investigated.
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\nMETHOD: A randomized controlled clinical trial was carried out in multidisciplinary primary care clinics. One group received home stretching exercises and spinal manipulative therapy, and the other group received home stretching exercises only. The subjective pain experience was investigated by assessing pain intensity (NRS-11) and the affective quality of pain (McGill questionnaire). Neck disability (NDI) and health status (EQ-5D) were also measured. Heart rate variability at rest was measured using a portable heart monitor. CPM was measured using a universal “clamp” from Clas Ohlson and a coldwater bath (0-2 ℃). The subjects received four treatments over two weeks. Linear mixed models were used to investigate the group by time interaction. Multivariate analysis of variance (MANOVA) was used to investigate the temporal stability of the CPM test. The study was approved by the Regional Ethical Review Board (Stockholm) (ref: 2018/2137-31).
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\nRESULTS: No statistically significant group effect was found for pain, disability, or any of the heart rate variability indices. No statistically significant association was found between changes in pain (NRS-11) and changes in HRV. The CPM test appears to be moderately stable over time for both subjects who experienced a clinically important difference and those who did not over a two-week treatment period.
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\nCONCLUSION: Adding spinal manipulative therapy to a two-week stretching protocol did not significantly improve heart rate variability, pain or disability in this well-controlled RCT. Further investigations found no significant association between treatment response from spinal manipulative therapy and home stretching exercises and HRV over two weeks. Further research on pain, disability and HRV should focus on subjects with higher pain intensity and a longer intervention period. Also, further investigation of the relationship between pain and HRV is warranted. The CPM utilized showed moderate temporal stability for this patient group. Changes in persistent or recurrent neck pain over two weeks were not associated with changes in the CPM test response.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.279
Teacher spread0.262 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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