Recommendations on the use of restrictions and assistive devices after total hip arthroplasty: an adolopment of guidelines
Bibliographic record
Abstract
PURPOSE: Movement restrictions and assistive devices have traditionally been recommended to prevent hip dislocation after total hip arthroplasty (THA). Considering the advancements in THA surgery, a review of treatment recommendations is worthwhile. The aim of this study was to investigate whether unrestricted protocol (without movement restrictions and assistive devices) should be recommended for THA patients. METHODS: A multiprofessional panel used the GRADE-Adolopment to develop the present recommendations, following the GIN-McMaster-Guideline-Development-Tool. We selected guideline topic and target audience, formulated clinical questions and prioritised outcomes. For the first question, a source guideline was identified and adoloped, whereas the second question required a de-novo recommendation. Therefore, the GRADE-Evidence-Profile and the Evidence-to-Decision framework were completed. Finally, the panel discussed and formulated the final recommendations. RESULTS: 0.52-1.08). Finally, considering small desirable health effects and trivial undesirable health effects of the intervention, we integrated two "conditional-recommendations" in favour of an unrestricted protocol. CONCLUSION: Through GRADE-adolopment approach new recommendations to provide an evidence-based guidance after THA have been formulated.
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 | 0.045 | 0.129 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".