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Record W2735258122 · doi:10.1186/s13063-017-2055-8

RETRACTED ARTICLE: Esoteric Connective Tissue Therapy for chronic low back pain to reduce pain, and improve functionality and general well-being compared with physiotherapy: study protocol for a randomised controlled trial

2017· article· en· W2735258122 on OpenAlexaboutno aff
Christoph Schnelle, Steffen Messerschmidt, Eunice J Minford, Kate Greenaway-Twist, Maxine Szramka, Marianna Masiorski, Michelle Sheldrake, Mark E. Jones

Post-publication record

NatureRetraction
ReasonLack of IRB/IACUC Approval and/or Compliance;
Date3/4/2021 0:00
Flagged by OpenAlex?Yes

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenueTrials · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyofascial pain diagnosis and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyRandomized controlled trialLow back painChronic painVisual analogue scaleBack painClinical trialConnective tissueAlternative medicineSurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Low back pain causes more global disability than any other condition. Once the acute pain becomes chronic, about two-thirds of sufferers will not fully recover after 1-2 years. There is a paucity of effective treatments for non-specific, chronic low back pain. It has been noted that low back pain is associated with changes in the connective tissue in the affected area, and a very low-impact treatment, Esoteric Connective Tissue Therapy (ECTT), has been developed to restore flexibility in connective tissue. ECTT uses patterns of very small, circular movements, to the legs, arms, spine, sacrum and head, which anecdotally are effective in pain relief. In an unpublished single-arm phase I/II trial with chronic pain patients, ECTT showed a 56% reduction in pain after five treatments and 45% and 54% improvements at 6 months and 7-9 years of follow-up respectively. METHODS: The aim of this randomised controlled trial is to compare ECTT with physiotherapy for reducing pain and improving physical function and physical and mental well-being in patients with chronic low back pain. The trial will be held at two hospitals in Vietnam. One hundred participants with chronic low back pain greater than or equal to 40/100 on the visual analogue scale will be recruited and randomised to either ECTT or physiotherapy. Four weekly treatments will be provided by two experienced ECTT practitioners (Treatment Group, 40 minutes each) and hospital-employed physiotherapy nurses (Control Group, 50 minutes). The primary outcomes will be changes in pain, physical function per the Quebec Pain Functionality Questionnaire and physical and mental well-being recorded by the Short Form Health Survey (SF-36), with mixed modelling used as the primary statistical tool because the data are longitudinal. Initial follow-up will be at either 4 or 8 months, with a second follow-up after 12 months. DISCUSSION: The trial design has important strengths, because it is to be conducted in hospitals under medical supervision, because ECTT is to be compared with a standard therapy and because the assessor and analyst are to be blinded. The findings from this trial will provide evidence of the efficacy of ECTT for chronic low back pain compared with standard physiotherapy treatment. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12616001196437 . Registered on 30 August 2016.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.992
Threshold uncertainty score0.336

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.028
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.1010.011

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 head0.039
GPT teacher head0.389
Teacher spread0.350 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designRandomized trial
Domainnot available
GenreProtocol

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

Citations9
Published2017
Admission routes1
Has abstractyes

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