Factors that affect patient reported outcome after anterior cruciate ligament reconstruction–a systematic review of the Scandinavian knee ligament registers
Bibliographic record
Abstract
OBJECTIVE: To perform a systematic review of findings from the Scandinavian knee ligament registers with regard to factors that affect patient reported outcome after anterior cruciate ligament (ACL) reconstruction. DESIGN: Systematic review. DATA SOURCES: Four electronic databases: PubMed, EMBASE, the Cochrane Library and AMED were searched, and 157 studies were identified. Two reviewers independently screened the titles, abstracts and full text articles for eligibility. A modified version of the Downs and Black checklist was applied for quality appraisal. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies published from the Scandinavian registers from their establishment in 2004 and onwards that documented patient reported outcome and provided information on concomitant injuries were eligible. RESULTS: A total of 35 studies were included. Younger age at ACL reconstruction, male sex, not smoking and receiving a hamstring tendon autograft positively influenced patient reported outcome. Patients with concomitant cartilage and meniscal injuries reported inferior subjective knee function compared with patients with an isolated ACL tear. One study reported that patients treated non-reconstructively reported inferior knee function compared with patients who had ACL reconstruction. CONCLUSION: Younger age, male sex, not smoking, receiving a hamstring tendon autograft and the absence of concomitant injuries were associated with superior patient reported outcomes after ACL reconstruction.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".