Health‐related quality of life does not deteriorate while waiting for anterior cruciate reconstruction
Bibliographic record
Abstract
PURPOSE: The aim of this study was to determine how preoperative health-related quality of life (HRQoL) is affected by the duration of the wait time (WT) for anterior cruciate ligament reconstruction (ACLR) once a decision is made to proceed with surgery. METHODS: This was a multi-centre prospective cohort study. One hundred and twenty-two patients 14 years of age and above waiting for ACLR completed the International Knee Documentation Committee (IKDC) demographic, current health assessment and subjective knee evaluation (SKF) forms on the day of decision to operate and the day of surgery. Changes in scores were analyzed for the entire cohort, adjusted for WTs and a subset was compared for patients with isolated anterior cruciate ligament (ACL) tears and ACL tears with concurrent meniscal involvement. Changes in HRQoL scores from the day of the decision to operate to the 9-month postoperative appointments were also assessed. RESULTS: Energy/Fatigue (p < 0.05), Pain (p < 0.05), General Health (p < 0.05) and the IKDC-SKF Score (p < 0.05) significantly increased between the day of the decision to operate and the day of surgery. Only the change in IKDC-SKF score remained significantly higher after adjusting for WT. Baseline HRQoL scores significantly improved by the 9-month postoperative appointment. CONCLUSION: The length of time waiting for ACLR did not adversely influence HRQoL in this study. However, low preoperative HRQoL and the significant improvement in HRQoL of patients followed postoperatively suggest that timely surgery is beneficial for this patient population. LEVEL OF EVIDENCE: Level II.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".