Impact of tibial supplementary fixation in anterior cruciate ligament reconstruction for soft tissue auto and allografts: Modest enhancement in stability and increased incidence of pain: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Purpose To evaluate whether the joint function, stability and safety of tibial supplementary fixation in anterior cruciate ligament reconstruction is superior compared with tibial screw fixation alone. Methods PubMed, Cochrane Library, EMBASE and Web of Science were searched, tracking until 12 April 2025. Eligible studies included published randomized controlled trials (RCTs) and low‐risk cohort studies comparing clinical outcomes and complications between tibial screw interference with supplementary fixation (Group I) and tibial screw interference alone or with a sheath (Group II). RCTs were assessed using the Cochrane Risk of Bias tool, while cohort studies were evaluated with the Newcastle–Ottawa Scale and Methodological index for non‐randomized studies. Model selection (random or fixed‐effects) was based on data heterogeneity. Results This meta‐analysis included eight studies with 943 patients (Group I: 386, Group II: 557). Group I showed no significant differences in side‐to‐side difference (SSD) in the sheath subgroup at 24 months, SSD <3 mm at 9.1 kg at 12 and 24 months, or manual maximum testing at 24 months, Pivot test at 8–12 and 24 months, Lachman test at 8–12 months, International Knee Documentation Committee objective and subjective score at 24 months compared to Group II. Group I demonstrated statistically significant reductions in SSD (mean difference: −1.02; 95% CI: −1.79 to −0.25; p = 0.009) in the no‐sheath subgroup and lower Lachman test positivity (odds ratio [OR] = 0.30; 95% confidence interval [CI]: 0.13–0.71; p = 0.01) at 24 months. Ligament retear rates were similar; however, Group I experienced a substantially higher incidence of kneeling pain (OR = 6.28; 95% CI: 1.86–2.25; p < 0.01), an outcome that could adversely affect patient comfort and long‐term functional recovery. Conclusion Enhanced supplementary tibial fixation with soft tissue autografts and allografts offers similar joint function and a modest enhancement of stability compared to tibial interference screw fixation alone, but is associated with a higher incidence of pain. Level of Evidence Level III, retrospective cohort studies have been analysed, alongside RCTs, and thus this is the level of evidence.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".