Review of Methods for Evaluating Changes in the Tension and Properties of the Gluteus Medius Muscle (GMED) and the Tensor Fascia Latae (TFL) as a Result of Hip Osteoarthritis (HOA) and After Total Hip Arthroplasty (THA)—Could MyotonPRO Assessment Be the New Standard?
Bibliographic record
Abstract
Background/Objectives: Osteoarthritis (OA) is a condition affecting many joints, including the hip. The treatment of advanced hip osteoarthritis (HOA) involves total hip arthroplasty (THA). Atrophy of abductor muscles is often diagnosed in patients with HOA. This review presents a number of studies evaluating changes that occur in the gluteus medius (GMED) and tensor fasciae latae (TFL) as a result of HOA and THA. MyotonPRO is a portable and non-invasive device that allows for the assessment of muscle quality. This review aimed to collect studies assessing changes in GMED and TFL following HOA and THA and to determine whether MyotonPRO can be used for this assessment. Methods: We conducted a comprehensive search of databases, including Google Scholar, Science Direct, and PubMed, for relevant articles published between 2012 and 2024. A total of 37 articles were included in our review. Qualified papers evaluated changes in the lower limb muscles, including TFL and GMED, as a result of HOA and THA using MyotonPRO and other methods. Results: In this article, we emphasize the influence of the tested muscles on HOA and the postoperative course after THA using MyotonPRO. We have shown that myotonPRO was used to assess muscle changes due to knee OA and GMED and TFL in other groups of patients. Conclusions: This is the first review of the literature to indicate a new direction of research using myotonPRO. The use of MyotonPRO will allow for the more detailed development of rehabilitation programs for patients with HOA and after THA.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".