Intervention Reporting in Total Hip or Knee Arthroplasty Prehabilitation Trials
Bibliographic record
Abstract
Background: Prehabilitation is defined as the process of improving an individual’s functional capacity to tolerate an upcoming stressor. In the surgical context, potential benefits of prehabilitation include reducing length of stay in hospital, postoperative pain, and complications. The objective of this review is to evaluate the completeness of intervention reporting details and changes in quality of this reporting over time for total hip (THA) or knee arthroplasty (TKA) prehabilitation interventions using the Template for Intervention Description and Replication (TIDieR) Checklist. Methods: MEDLINE, EMBASE, CENTRAL, and Google Scholar were searched from inception to May 3, 2024, to identify published articles or protocols of randomized controlled trials reporting prehabilitation interventions for adults undergoing elective THA or TKA. Two independent reviewers completed screening and data extraction. Results: From 1278 unique search results, 191 full-text studies were assessed for eligibility, and 84 studies met inclusion criteria (n=54 TKA, n=15 THA, n=15 TKA/THA). Included studies were published from 1992 to 2024. Prehabilitation intervention modalities reported across studies included exercise (n=51), multimodal programs (n=14), behavioural (n=6), nutritional supplementation or weight loss (n=3), and other (n=10). The mean (standard deviation) TIDieR score was 7.7 (1.8), indicating moderate reporting quality overall. The proportion of studies reporting each item completely were as follows: name (100%), rationale (100%), materials (65%), procedures (85%), providers (25%), mode of delivery (75%), location (67%), dose and duration (86%), tailoring (31%), modifications (5%), planned adherence (37%), and actual adherence (35%). Conclusions: The reporting quality of interventions in the majority of prehabilitation RCTs was moderate. The TIDieR framework can be used to support evaluation and replication of prehabilitation for THA and TKA by identifying key intervention components. Quality of intervention reporting was similar between trials published before TIDieR was introduced in 2014 and post-TIDieR. This review highlights the varied landscape of THA/TKA prehabilitation.
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 | 0.538 | 0.796 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.016 | 0.024 |
| Bibliometrics | 0.028 | 0.031 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".