Revision in previously satisfied knee arthroplasty patients is the result of their call on the physician, not on pre-planned follow-up: A retrospective study of 181 patients who underwent revision within 2 years
Bibliographic record
Abstract
BACKGROUND: Degree of satisfaction with a knee arthroplasty is said to be correlated to reduced pain and better function. During a validation of the Swedish Knee Arthroplasty Register in 1997, previously operated patients were asked how satisfied they were with their knee. A subgroup of "satisfied" patients was identified who underwent revision within 2 years of having expressed satisfaction. Our aim was to study the revision diagnosis, to determine whether the problem leading to revision had been discovered as a result of routine follow-up, and also to find out when the symptoms leading to revision had started. METHODS: We retrospectively studied the medical records of 181 patients (181 knees), with a median age of 74 (31-88) years. 68% were women and the median time between primary operation and revision was 8 (3-21) years. RESULTS: Aseptic loosening (74/181) was the most common diagnosis. 2 cases were revised as a result of routine follow-up. 44% of the medical records included reports of pain in the replaced knee prior to answering the satisfaction questionnaire. INTERPRETATION: Few patients were admitted to knee revision surgery due to medical findings discovered during routine follow-up. The term "satisfaction" must be interpreted with care, as it seems to have a more complex meaning for the patients than absence of knee pain.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".