A Pilot Study In to the Effects of Cervical Manual Therapy Plus Conventional Physical Therapy on Clinical Outcomes and Electrodiagnostic Findings in People With Carpal Tunnel Syndrome
Bibliographic record
Abstract
Background: Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy that has a significant impact on patients' quality of life. Current physical therapy treatment options show limited effects or low-quality evidence, especially in the long term. To date, there has been little research to look at the effects of treating the cervical spine on decreasing symptoms distally to the carpal tunnel. This study aimed to evaluate the effects of cervical manual therapy plus conventional physical therapy on patients with carpal tunnel syndrome. Methods: This pilot pretest/posttest and six-month follow-up clinical study included 15 adult patients with CTS. For two weeks, each patient received 10 sessions of supervised intervention treatment. The efficacy of the therapies was assessed at baseline (T0), immediately after treatment (T1), and six months after treatment (T2). The visual analog scale (VAS), a symptom severity scale, the functional capacity scale of the Boston Carpal Tunnel Questionnaire (BCTQ), the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire, median nerve motor distal latency (mMDL), and median sensory nerve conduction velocity (mSNCV) were outcome measures. Results: <.05). Conclusion: This pilot study indicates that cervical manual therapy plus conventional physical therapy applied for two weeks improves clinical outcomes and electrodiagnostic findings in people with CTS.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".