Effectiveness of Massage Including Proximal Trigger Point Release for Plantar Fasciitis: a Case Report
Bibliographic record
Abstract
BACKGROUND: Plantar fasciitis (PF) is a common degenerative condition of the plantar fascia. Symptoms include tenderness on the plantar surface of the foot, pain on walking after inactivity, and difficulty with daily activities. Rest, non-steroidal anti-inflammatories, and manual therapies are frequently used treatments for PF. Trigger point release (TrPR) for PF has been found as a viable treatment option. OBJECTIVE: To determine the effects of massage, including proximal TrPR, for pain and functional limitations in a patient with PF. METHOD: A student massage therapist from MacEwan University administered five massages, one initial and one final assessment over five weeks to a 46-year-old female with diagnosed PF. She complained of unilateral plantar heel pain (PHP) and deep pulling from mid-glutes to the distal lower limb bilaterally. Evaluation involved active and passive range of motion, myotomes, dermatomes, reflexes, and orthopedic tests. The treatment aim was to decrease PHP by releasing active trigger points (TrPs) along the posterior lower extremity to the plantar surface of the foot, lengthening the associated muscles and plantar fascia. Hydrotherapy, Swedish massage, TrPR, myofascial release, and stretches were implemented. Pain was measured using the numerical rating scale pre- and post-treatments, and the Foot Function Index was used to assess function at the first, middle, and last appointments to assess the effectiveness of massage including proximal TrPR for PF. RESULTS: PHP and functional impairments decreased throughout the five-week period. CONCLUSION: The results indicate massage, including proximal TrPR, may decrease pain and functional impairments in patients with PF. Further research is necessary to measure its efficacy and confirm TrPR as a treatment option.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| 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".