Which knee replacement do the patients forget? Unicondylar or total knee arthroplasty
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine which type of knee arthroplasty is easier to forget by comparing levels of joint awareness evaluated with the Forgotten Joint Score (FJS-12) after unicondylar versus total knee arthroplasty. METHODS: Patients who underwent either unicondylar or total knee arthroplasty due to primary gonarthrosis were retrospectively identified and then divided into 2 groups: the TKA group (218 patients; mean age = 68.93 ± 7.14 years) and the UKA group (131 patients; mean age = 60.39 ± 7.03 years). The status of joint awareness after knee replacement surgery was assessed using the Turkish version of the FJS-12 at the final follow-up by telephone interview. Also, The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and The EuroQol five-dimensional (EQ-5D) scores were obtained to assess the clinical status of the patients. RESULTS: The mean follow-up was 2.8 years (range = 24-49 months) in the TKA group and 3.2 years (range = 24-50 months) in the UKA group. The FJS-12 was significantly higher in the UKA group (73.60 ± 9.95) than in the TKA group (64.88 ± 9.47) (P = .001). The WOMAC score was significantly better in the UKA group (81.39 ± 9.84) than in the TKA group (74.92 ± 9.99) (P = .001). No significant difference in EQ-5D existed between the groups (0.76 ± 0.14 for the TKA group, 0.79 ± 0.17 for the UKA group; P = .441). In terms of gender, the FJS-12 showed no differences between the groups; however, more favorable scores were recorded in younger patients with UKA. CONCLUSION: The results of this study have demonstrated that UKA may be better than TKA in terms of the patient perception of pain, stiffness, and physical functioning. LEVEL OF EVIDENCE: Level IV, Therapeutic Study.
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 | 0.000 | 0.003 |
| 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) | 0.002 | 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".