Long-duration immediate postoperative knee flexion positioning results in better functional outcomes after total knee arthroplasty.
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate the effects of affected knee flexion for 24 vs. 72 hours on blood loss, pain, range of motion, and functional outcomes after total knee arthroplasty. PATIENTS AND METHODS: The present study included 46 participants with a mean age of 64.33 ± 6.70 years. The affected knee of the first 23 participants, based on the order of operations, was positioned at 70° flexion for 24 hours, and the knee of the next 23 participants was positioned at 70° flexion for 72 hours. Participants were evaluated before the operation and on postoperative day 3 and week 6. Pain, edema, range of motion, time up and go test scores, and Western Ontario McMaster Universities Arthritis Index scores, hemoglobin, and hematocrit were measured before the operation and on postoperative at day 3 and week 6. RESULTS: We found that the calculated blood loss was 575.07 ± 282.44 and 578.39 ± 297.11 mL in patients who underwent short- and long-duration flexion positioning, respectively (p = 0.921). The active flexion angles at postoperative week 6 were 83.61° ± 22.03° and 105.91° ± 13.06° in the short- and long-duration flexion groups, respectively (p < 0.01). Furthermore, the Western Ontario and McMaster Universities Arthritis Index scores at postoperative week 6 were 35.52 ± 24.71 and 17.17 ± 15.37 in the short- and long-duration flexion groups, respectively (p < 0.01). CONCLUSIONS: Long-duration flexion positioning after total knee arthroplasty may lead to better middle-term flexion range of motion and physical function scores than short-duration flexion positioning.
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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".