Three Cases of Posterior Tibial Tendinitis Treated with Ultrasound-Guided Hydrodissection
Bibliographic record
Abstract
Background: Posterior tibial tendinopathy (PTT) is a degenerative condition impacting the posterior tibial tendon, often leading to pain, impaired mobility, and potential deformities like flatfoot.While traditional therapies such as physical therapy, orthotics, and NSAIDs are common, minimally invasive techniques like ultrasound-guided hydrodissection are emerging as promising alternatives.Objectives: This study aims to evaluate the efficacy and safety of ultrasound-guided hydrodissection in treating posterior tibial tendinopathy, offering a non-steroidal, minimally invasive treatment option.Methods: Three patients diagnosed with posterior tibial tendinopathy underwent ultrasoundguided hydrodissection using 5% dextrose solution.The procedure involved injecting the solution between the tendon and sheath to break adhesions and improve gliding function.Pain levels were assessed using the Numerical Rating Scale (NRS), and functional outcomes were measured via clinical tests like plantar flexion, inversion, and the single-heel rise test.Results: All patients reported significant pain reduction, with NRS scores dropping from 6-7 to 0. Functional improvements were noted, with restored mobility and resolution of symptoms.No adverse effects were observed during or after the treatments, which required only 2-3 sessions for full recovery.Conclusion: Ultrasound-guided hydrodissection is an effective and safe treatment for posterior tibial tendinopathy.This minimally invasive approach addresses adhesions and improves tendon function, providing a viable alternative to steroid injections or surgical interventions.Future studies with larger samples and standardized protocols are recommended to validate these findings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| 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".