Can Knees be Forgotten 2 Years After Total Knee Arthroplasty?
Bibliographic record
Abstract
Background: There have been multiple ways to measure outcomes post total knee arthroplasty. Ultimate goal is to replicate a natural joint to allow patients to perform most activities of daily living and give high satisfaction rates. Patient reported outcome measures (PROM) like Forgotten Joint Score (FJS), Oxford Knee Score (OKS)and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) have been validated and used for evaluation of TKA patients. FJS helps to evaluate how natural a prosthesis feels post surgery. Our aim was to study how natural a joint felt or was forgotten 2 year after surgery and how FJS correlates with OKS and WOMAC scores. Materials and Methods : We evaluated 254 total knee replacements with minimum 2 year post TKA. All the patients who were at least 2 year post operative, completed FJS questionnaire where scores are ranged from 0-100; OKS questionnaire where scores are ranged between 0-48; Short – form WOMAC questionnaire where scores are ranged between 0-28. Correlation analysis was performed for FJS with OKS and short - form WOMAC scores. Results: 254 patients with mean age of 65.01 years of which 83 males and 171 females were evaluated with minimum of 24 months follow up and average follow-up of 30.85 months. Average FJS, OKS and SF WOMAC were 77.24, 38.75 & 79.97 respectively. FJS showed good correlation with OKS and SF WOMAC scores. Conclusion : FJS is an easy and equally effective outcome measure, which is valid and reliable like the other common well know measures like OKS and WOMAC. Patients experience a marked improvement in the FJS over the first two years. Patients in our series had good outcomes who had more natural feel of knees or a feeling of “forgotten knees” in their day to day activity after 2 years of surgery.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".