Chiropractic Therapy Plus Multimodal Physical Therapy Versus Multimodal Physical Therapy Alone in the Management of Individuals with Cervicothoracic Dorsalgia: A Randomized Clinical Trial
Bibliographic record
Abstract
Aim: The study aims to compare the effects of thoracic spinal adjustment and multimodal physical therapy to those of multimodal physical therapy alone in patients with cervicothoracic dorsalgia. Methods: This single-center, prospective, randomized, clinical study included a total of 43 patients diagnosed with cervicothoracic dorsalgia (aged 20-55; 22 female and 21 male), was conducted between March 2019 and February 2020. The participants were randomly assigned into 2 groups: Multimodal Physical therapy (MPT, n=21) and MPT plus thoracic spinal adjustment (MPT+TSA; n=22). In MPT group, modalities including hot packs, transcutaneous electrical nerve stimulation (TENS), therapeutic ultrasound and neck-posture exercises were applied for 15 sessions. MPT + TSA group received the same MPT approach, with the addition of TSA once a week during 4 weeks of treatment. The Spinal Mouse® posture analysis for thoracic kyphosis and thoracic mobility, Visual Analog Scale (VAS) for pain, Neck Disability Index (NDI), Quebec back pain questionnaire (Quebec) were assessed at baseline and 4th week. Results: The intra-group comparison outcomes revealed significant improvement in VAS, NDI, Quebec for both groups (MPT and MPT + TSA; p
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".