Appropriate questionnaires for knee arthroplasty
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
The Swedish Knee Arthroplasty Registry (SKAR) has recorded knee arthroplasties prospectively in Sweden since 1975. The only outcome measure available to date has been revision status. While questionnaires on health outcome may function as more comprehensive endpoints, it is unclear which are the most appropriate. We tested various outcome questionnaires in order to determine which is the best for patients who have had knee arthroplasty as applied in a cross-sectional, discriminative, postal survey. Four general health questionnaires (NHP, SF-12, SF-36 and SIP) and three disease/site-specific questionnaires (Lequesne, Oxford-12, and WOMAC) were tested on 3600 patients randomly selected from the SKAR. Differences were found between questionnaires in response rate, time required for completion, the need for assistance, the efficiency of completion, the validity of the content and the reliability. The mean overall ranks for each questionnaire were generated. The SF-12 ranked the best for the general health, and the Oxford-12 for the disease/site-specific questionnaires. These two questionnaires could therefore be recommended as the most appropriate for use with a large knee arthroplasty database in a cross-sectional population.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it