Total Knee Replacement as a Knee Osteoarthritis Outcome
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To predict, using clinical and qMRI data, the incidence of total knee replacement (TKR) during the long-term follow-up of knee osteoarthritis (OA) patients who formerly received chondroitin sulfate (CS) or placebo treatment. DESIGN: A post hoc intention-to-treat analysis to evaluate the incidence of TKR was done on knee OA patients who had participated in a 12-month trial evaluating the impact of CS (800 mg/d) versus placebo for 6 months, followed by a 6-month open-phase in which all patients received CS. Additionally, the clinical and qMRI predictors of TKR were determined. RESULTS: Thirteen TKRs were performed in the population after a 4-year follow-up. More TKRs were performed in the placebo group than in the CS group (69% vs. 31%, P = 0.150, logistic regression). The statistically significant predictors of TKRs were, at baseline, higher WOMAC pain and function scores, presence of bone marrow lesions (BMLs), and higher C-reactive protein levels. Loss of medial cartilage volume and increase in WOMAC pain and function at one-year were also predictors of TKR. Multivariate analyses revealed that baseline presence of BML and higher WOMAC pain score were independent predictors. Time to occurrence of the TKR also favored the CS group versus placebo (log-rank, P = 0.094). CONCLUSION: Symptoms such as knee pain and function, presence of BML, and cartilage volume loss predict the long-term occurrence of a "hard" outcome such as TKR.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.006 |
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 it