Perspectives of orthopaedic surgeons on patients' appropriateness for total joint arthroplasty: a qualitative study
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: As total joint arthroplasty (TJA) rates rise, there is need to ensure appropriate use. Our objective was to elucidate surgeons' perspectives on appropriateness for TJA. METHODS: Semi-structured telephone interviews were conducted in a sample of orthopaedic surgeons that perform TJA in three Canadian Provinces. Surgeons were asked to discuss their criteria for TJA appropriateness for osteoarthritis; potential value of a decision-support tool to select appropriate candidates; and the role of other stakeholders in assessing appropriateness. RESULTS: Of 17 surgeons approached for participation, 14 completed interviews (12 males; 7 aged <50 years; 5 academic; 8 in urban practices). Surgeons agreed that pain and pain impact on patients' quality of life and function were the key criteria to assess appropriateness for TJA, but that these concepts were difficult to assess and not always congruent with structural changes on joint radiography. Some used a wider range of criteria, including their assessments of patient expectations, ability to cope and readiness for surgery. While patient age was not identified as a criterion itself, surgeons did acknowledge that appropriateness criteria may differ for younger versus older patients. Most agreed that a decision-support tool would help ensure that all elements of appropriateness are assessed in a standardized manner, albeit the ultimate decision to offer surgery must be left to the discretion of surgeons, within the context of the doctor-patient relationship. CONCLUSIONS: Surgeons recognized the need for a tool to support decision making for TJA, particularly in the context of increasing surgical demand in younger patients with less severe arthritis. The work to develop and test such a decision-support tool is underway.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".