Use of Inpatient Continuous Passive Motion Versus No CPM in Computer-Assisted Total Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Continuous passive motion (CPM) has shown positive effects on tissue healing, edema, hemarthrosis, and joint function (L. Brosseau et al., 2004). CPM has also been shown to increase short-term early flexion and decrease length of stay (LOS) ( L. Brosseau et al., 2004; C. M. Chiarello, C. M. S. Gundersen, & T. O'Halloran, 2004). The benefits of CPM for the population of patients undergoing computer-assisted total knee arthroplasty (TKA) have not been examined. PURPOSE: The primary objective of this study was to determine whether the use of CPM following computer-assisted TKA resulted in differences in range of motion, edema/drainage, functional ability, and pain. METHODS: This was an experimental, prospective, randomized study of patients undergoing unilateral, computer-assisted TKA. The experimental group received CPM thrice daily and physical therapy (PT) twice daily during their hospitalization. The control group received PT twice daily and no CPM during the hospital stay. Both groups received PT after discharge. Measurement included Knee Society scores, Western Ontario McMaster Osteoarthritis Index values, range of motion, knee circumference, and HemoVac drainage. Data were collected at various intervals from preoperatively through 3 months. RESULTS: Although the control group was found to be higher functioning preoperatively, there was no statistically significant difference in flexion, edema or drainage, function, or pain between groups through the 3-month study period.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".