Can orthopedic trials change practice?
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The impact of large, randomized trials in orthopedic surgery on surgeons' preferences for a particular surgical approach remains unclear. We surveyed surgeons to assess whether they would change practice based upon results of a large, multicenter randomized controlled hip fracture trial. METHODS: We conducted a cross-sectional survey among International Hip Fracture Research Collaborative (IHFRC) surgeons and surgeons who were members of Arbeitsgemeinschaft fuer Osteosynthesefragen - Association for the Study of Internal Fixation (AO/ASIF) to determine the likelihood that they would change practice based on findings of a proposed large, multicenter randomized controlled trial (the Hip Fracture Evaluation with Alternatives of Total Hip Arthroplasty versus Hemi-Arthroplasty (HEALTH) study). We asked surgeons their current preferences for the management of displaced femoral neck fractures and whether a trial that definitively revealed a substantial improvement in function and quality of life with no difference in risk of revision surgery was important and would cause them to change practice. RESULTS: Of 883 surgeons surveyed, 210 responded from IHFRC and 586 from AO/ASIF (a response rate of 90%). Most surgeons (61%) preferred hemiarthroplasty (HA) for treating displaced femoral neck fractures. 72% of responding surgeons believed that a substantial improvement in patient function with total hip arthroplasty (THA) and no adverse effects on revision surgery would be an important finding. Moreover, of 483 surgeons who preferred hemiarthroplasty, 62% would change their practice based upon the findings of the trial. INTERPRETATION: Large clinical trials in orthopedics are worthwhile endeavors, as they have the potential to change practice among surgeons. Surgeons seem willing to adopt alternative surgical approaches if the evidence is compelling and sound.
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 | 0.731 | 0.911 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.024 | 0.014 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".