Manual Therapy and Exercise in Treatment of Patients with Cervical Radiculopathy: A Protocol for a Case Series
Bibliographic record
Abstract
Study Design: Manual therapy and exercise in the treatment of patients with cervical radiculopathy: A protocol for a case series.\nBackground: Cervical radiculopathy (CR) most commonly originates from space occupying lesions, resulting in upper extremity radicular pain. Numerous physical therapy interventions are available for treating CR symptoms, however present practice patterns incorporate the application of a combination of interventions with inconclusive or mixed results. Clinical practice guidelines advocate for the utilization of thoracic manipulation to treat CR.\nObjectives: It is hypothesized that the use of specific manual therapy techniques combined with exercise will have a positive effect on CR as measured by reduced levels of pain, disability, and improved range of motion (ROM), yet there are no studies to support this theory. Therefore, the purpose of this case series is to observe the short-term effects of specific manual therapy techniques and exercise directed to the thoracic and cervical spine in patients with CR.\nMethods: The protocol utilizes a one-group pretest-posttest design. This quasi-experimental design is intended to determine the short-term effects of thoracic manipulation, cervical rotation mobilization and exercise on pain and disability. Subjects completed the Neck Disability Index (NDI), the Numeric Pain Rating Scale (NPRS) at pre and post intervention, and a Global Rating of Change (GROC). Inclusion criteria: Subjects 18-60 years old, scored a 5 or higher on the NDI, and tested positive for at least 3 out of the 4 test items as reported in Wainner et al’s clinical prediction rule (CPR) for CR. Exclusion criteria: Any red flag items indicating non-musculoskeletal origin of symptoms or contraindications to manipulation. Interventions included thoracic manipulations followed by local cervical rotation mobilization and exercise prescription.\nResults: Of 5 subjects screened, only one fit the inclusion criteria of our study. This subject demonstrated decreases in NDI scores short of estabilished minimal detectable change (MDC) thresholds and decreases in NPRS scores that met MDC thresholds immediately following treatment and at 48 hour follow up. The subject reported improvement on the GROC scale that did not meet minimally cinically important difference (MCID) threshold.\nConclusion: Due to the single subject who qualified for inclusion, we were unable to draw statistically meaningful conclusions about our protocol. This could be due to the fact that this condition does not commonly affect the demographics represented in the subject pool. However, the subject who did qualify showed a clinically meaningful change on the NDI and NPRS outcome measures suggesting that further investigation using this protocol is warranted.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".