Percutaneous Tenotomy for the Management of Spastic Contractures in Adults: A Systematic Review
Bibliographic record
Abstract
Introduction: Percutaneous tenotomy is an emerging, minimally-invasive procedure to treat muscle and tendon contractures, including those resulting from spasticity. Such contractures often cause pain, functional impairment, impact quality of life and may not respond to conservative or medical therapy. Further, spastic contractures typically affect frail, older patients unsuitable for management with open surgical procedures. We undertook the first PRISMA-compliant systematic review exploring use of percutaneous tenotomy to manage contractures occurring in the context of spasticity in adults. Methods: We searched 6 databases for primary research papers featuring an entirely adult sample undergoing percutaneous tenotomy, published in either English or French. Quality assessment was performed using the Oxford Centre for Evidence-Based Medicine Scale and the Methodological Index for Non-Randomized Studies. Synthesis of included study data was performed where possible. Results: Six studies were included, reporting 160 patients undergoing more than 430 tenotomies to 27 different tendons. All were low quality. Synthesis of evidence across studies indicated that percutaneous tenotomy has a low complication rate and may support patients to obtain a range of post-operative goals, including improved skin hygiene, ease of patient care and joint range. However, synthesis across studies was limited by heterogenous patient assessment and poor reporting. Conclusion: This review found some evidence supporting the safety and efficacy of percutaneous tenotomy in adults with contracture, but higher-quality studies are required. Further work should standardise the approach and reporting of these procedures to facilitate evidence synthesis and to develop best practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".