Who, when, and why total joint replacement surgery? The patient's perspective
Bibliographic record
Abstract
PURPOSE OF REVIEW: Although total joint replacement is an effective treatment for advanced arthritis, many whom might benefit are unwilling to consider this procedure. This review highlights advances in understanding of patients' perceptions of total joint replacement. RECENT FINDINGS: Research shows that patients' willingness to consider total joint replacement varies by sex, race/ethnicity, and socioeconomic status as a result of systematic differences in knowledge and beliefs about the procedure. Individuals with low socioeconomic status and minorities view the procedure less favorably than their wealthier, white counterparts, possibly partly explaining disparity in rates of use of the procedure among these groups. Among those undergoing total joint replacement, up to 30% experience a suboptimal outcome or are dissatisfied with results. Early work suggests that patients' expectations and self-efficacy are important potential predictors of postoperative outcome. Patient information needs regarding total joint replacement vary significantly and possibly systematically by sex and race/ethnicity. Available information materials may not address the concerns of many individuals contemplating the procedure, posing a potential barrier to surgery. SUMMARY: Targeted culturally sensitive knowledge dissemination strategies are needed to improve the knowledge and beliefs of people with hip/knee arthritis about total joint replacement.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".