ABS0147 EARLY IMPROVEMENTS IN QUADRICEPS MUSCLE INHIBITION AS A KEY DETERMINANT OF FUNCTIONAL RECOVERY FOLLOWING TOTAL KNEE ARTHROPLASTY
Bibliographic record
Abstract
Background: Total Knee Arthroplasty (TKA) is a common surgical procedure for knee osteoarthritis that aims to relieve pain and restore joint function. Despite its success, postoperative quadriceps muscular inhibition (QMI) is still a substantial barrier, delaying functional recovery and affecting quality of life. Understanding the temporal dynamics of QMI and its impact on functional outcomes could help guide rehabilitation efforts to optimize recovery timelines. Objectives: This study aimed to investigate the relationship between early improvements in QMI and functional performance at six weeks post-surgery. Methods: A total of 19 patients (mean age 69.4 years, BMI 32.9 kg/m2, 17f, 2m) who underwent unilateral TKA surgery included in the present study. QMI was assessed using a pressure biofeedback unit, while functional performance was evaluated through the 2-Minute Walk Test (2MWT) and the Five-Times Sit-to-Stand Test (5TSTS). Functional levels were assessed using the WOMAC and KOS-ADLS scales. Measurements were performed on postoperative days 1 and 2, as well as at weeks 2 and 6. Results: Significant improvements in QMI were observed during the first two postoperative weeks (p < 0.05), with no notable changes between weeks 2 and 6. Functional performance at six weeks post-surgery showed a moderate negative correlation with improvements in QMI during the initial two weeks (r = -0.591, p=0.01) post-surgery. Conclusion: Early rehabilitation efforts focusing on quadriceps muscle activation, particularly within the first two weeks after surgery, may facilitate better long-term functional outcomes following TKA. Future research should investigate targeted interventions to optimize muscle activation during this critical postoperative period. REFERENCES: NIL . Table 1Relationship Between Improvements Quadriceps Muscle Inhibition Levels and Functional Status.N=19QMI improvements5-TSTS2MWT10MWTWOMACpWOMACsWOMACfKOSADLS2 nd dayr=-0,098p= 0,698r= 0,360p=0,130r= -0,227p=0,351r= -0,235p=0,333r= 0,209p=0,390r=0,040p=0,872r= 0,023p=0,9262 nd weekr=-0,591p=0,010r= 0,228p=0,348r= -0,202p=0,408r= 0,037p=0,880r=-0,114p=0,643r= -0,110p=0,655r= 0,094p=0,7026 th weekr=-0,315p=0,203r= 0,182p=0,455r= -0,349p=0,143r= 0,088p=0,721r= 0,170p=0,486r= -0,152p=0,535r= -0,027p=0,912r: Spearman correlation analysis.5TSTS: Five-Times Sit-to-Stand Test, 2MWT: 2-Minute Walk Test, 10MWT: 10-Meter Walk Test, WOMACp: Western Ontario and McMaster Universities Osteoarthritis Index "Pain" subscale, WOMACs: Western Ontario and McMaster Universities Osteoarthritis Index "Stiffness" subscale, WOMACf: Western Ontario and McMaster Universities Osteoarthritis Index "Function" subscale, KOS-ADLS: Knee Outcome Survey - Activities of Daily Living Scale. Acknowledgements: NIL . Disclosure of Interests: None declared . © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
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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 | 0.000 | 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) | 0.005 | 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".