Recommendations for resuming elective hip and knee arthroplasty in the setting of the SARS-CoV-2 pandemic: the European Hip Society and European Knee Associates Survey of Members
Bibliographic record
Abstract
PURPOSE: The COVID-19 pandemic has disrupted the health care system around the entire globe. A consensus is needed about resuming total hip and knee procedures. The European Hip Society (EHS) and the European Knee Association (EKA) formed a panel of experts that have produced a consensus statement on how the safe re-introduction of elective hip and knee arthroplasty should be undertaken. METHODS: A prospective online survey was done among members of EHS and EKA. The survey consisted of 27 questions. It includes basic information on demographics and details the participant's agreement with each recommendation. The participant could choose among three options (agree, disagree, abstain). Recommendations focussed on pre-operative, peri-operative, and post-operative handling of patients and precautions. RESULTS: A total of 681 arthroplasty surgeons participated in the survey, with 479 fully completing the survey. The participants were from 44 countries and 6 continents. Apart from adhering to National and Local Guidelines, the recommendations concerned how to make elective arthroplasty safe for patients and staff. CONCLUSION: The survey has shown good-to-excellent agreement of the participants with regards to the statements made in the recommendations for the safe return to elective arthroplasty following the first wave of the COVID-19 pandemic.
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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".