Case Study: EIMS Acupuncture Treatment for Posterior Tibialis Tendonitis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Posterior tibialis tendon dysfunction (PTTD) is a progressive ailment of a lower limb that, if left untreated, can lead to irreversible changes in the structure and function. The authors of the present study hypothesized the damages to the tibias tendon can be countered and reversed using electrical acupuncture and concurrent treatment of the associated muscle. INTERVENTION: The following study details a successful treatment of the early stage PTTD in a group of competitive athletes using a specific Electrical Intra Muscular Stimulation (EIMS) protocol developed and rooted in years of practice and the knowledge of the pathophysiology of the muscle and tendon tissues. Specifically, a combination the posterior and the original EIMS approach was used to stimulate the tendon and muscle concurrently at a frequency of 2 Hz. Analysis of the VAS scores showed a significant improvement following the treatment sessions. CONCLUSION: The success of this combined muscle/tendon stimulation protocol is given a strong correlation between the mechanism of tendon and muscle injury and recovery. The fast rate of healing and the simplicity of the materials required for the treatment offer a great potential for a wide-spread application. The authors extrapolate that the treatment method, with applicable modifications in needling locations, can be used for an array of common ailments involving tendons and muscles of the lower limb and foot, including the over-pronation, which is now common place due to the overweight problem in the general population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".