Implementation of Outpatient Total Joint Arthroplasty in Canada: Where We are and Where We Need to Go
Bibliographic record
Abstract
Bryn O Zomar, 1–3 Shannon L Sibbald, 1 Doug Bickford, 4 James L Howard, 2, 5 Dianne M Bryant, 1, 3 Jacquelyn D Marsh, 1, 3 Brent A Lanting 2, 3, 5 1Faculty of Health Sciences, University of Western Ontario, London, ON, Canada; 2London Health Sciences Centre, London, ON, Canada; 3Bone and Joint Institute, University of Western Ontario, London, ON, Canada; 4Southwestern Ontario Stroke Network, London, ON, Canada; 5Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, CanadaCorrespondence: Brent A Lanting 339 Windermere Road, Rm B9-003, London, ON N6A 5A5, CanadaTel +1 519-663-3335Email brent.lanting@lhsc.on.caAbstract: Total joint arthroplasties (TJA) are successful procedures for the treatment of end-stage hip and knee arthritis. Length of stay in hospitals after these procedures has been steadily decreasing over time, with outpatient procedures (discharge on the same day as surgery) introduced in the US within the last 20 years. Reducing length of stay after TJA can provide cost savings. Centres in Canada have started to utilize outpatient TJA procedures, but we have identified some barriers that may have limited their implementation. We have summarized the current literature for outpatient TJA and discussed potential solutions for the current barriers.Keywords: total knee arthroplasty, total hip arthroplasty, outpatient, implementation, barriers
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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".