Relationship between Preoperative Patient Characteristics and Expectations in Candidates for Total Knee Arthroplasty
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine the relationship between patient expectations for improvement following primary total knee arthroplasty (TKA) and patient preoperative characteristics. METHODS: This was a cross-sectional analysis of preoperative expectations. Expectations for improvement were evaluated in six distinct domains. The baseline factors used as independent variables were age, gender, presence of comorbidity, sub-domains of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC; pain, stiffness, physical limitation related to lower extremity), and SF-36 physical and mental health component scores. Stepwise logistic regression analysis was applied to examine the relationships between dependent and independent variables. RESULTS: The study cohort consisted of 236 candidates for TKA (154 women and 82 men, mean age 67, SD = 9.98). Expectations were high on average. Presence of comorbidity was associated with expectations of pain relief. Preoperative mental health was related to expectations for a return to activities of daily living; age, gender, physical health, and mental health were related to expectations for improved leisure, recreational, and sports activities. Preoperative physical health was related to expectations for potential return to full recovery. No baseline factors were associated with expectations for improved range of motion or for providing care to and interacting with others. CONCLUSION: Expectations related to recovery from surgery appeared to have distinct dimensions and were associated with patient baseline characteristics.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".