Preoperative Patient Optimization for Lower Extremity Total Joint Arthroplasty Surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
» Identifying medical comorbidities and optimizing modifiable risk factors (biological, social, and psychological) have been suggested as a strategy to improve the value of total joint arthroplasty (TJA) care, while reducing the risk of intraoperative and postoperative complications. Modifiable biological factors include weight management to reduce obesity, optimizing diabetic control, improving malnutrition, optimizing bone health, improving anemia, managing anticoagulants and bleeding risk, controlling inflammatory conditions, reducing methicillin-sensitive Staphylococcus aureus/methicillin-resistant S. aureus colonization, and reducing frailty. Modifiable social and psychological factors include tobacco and smoking cessation, reducing alcohol use, ceasing drug use/misuse, optimizing mental health (i.e., depression, anxiety), patient TJA education and managing expectations, and evaluating discharge determination and living status. This review comprehensively evaluates and summarizes preoperative patient optimization strategies for lower extremity TJA surgery, both in the primary and revision settings.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 it