Remnant-preserving techniques in anterior cruciate ligament reconstruction: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Anterior cruciate ligament reconstruction (ACLR) is a widely performed procedure to restore knee function and stability. Remnant-preserving techniques have been proposed to improve postoperative outcomes by retaining the proprioceptive and biological benefits of the ACL remnant. Remnant preservation is hypothesized to enhance graft integration and proprioceptive restoration. This systematic review and meta-analysis aimed to evaluate the surgical and functional outcomes of remnant-preserving ACLR compared to standard ACLR. METHODS: A systematic search of PubMed, Embase, Web of Science, and the Cochrane Library was conducted on November 6, 2024, adhering to PRISMA guidelines. Eligible studies included randomized controlled trials (RCTs) and cohort studies that compared remnant-preserving ACLR with standard ACLR. Outcomes assessed included functional scores (Lysholm and IKDC), knee stability (KT-1000/2000 measurements), and complication rates. Quality assessment was performed using the Newcastle-Ottawa Scale for cohort studies and the Cochrane Risk of Bias tool for RCTs. Statistical analyses utilized fixed- or random-effects models based on heterogeneity. RESULTS: The meta-analysis included 10 studies, comprising 6 RCTs and 4 cohort studies. Remnant-preserving ACLR demonstrated significant improvements in Lysholm scores (WMD = 0.85; 95% CI, 0.29-1.42; P < 0.05) and knee stability (RCTs: WMD = -0.45; 95% CI, -0.62 to -0.27; P < 0.01; cohort studies: WMD = -0.42; 95% CI, -0.62 to -0.23; P < 0.01). No significant difference was observed in IKDC scores (WMD = -0.21; 95% CI, -1.68 to 1.26; P > 0.05) or complication rates (RR = 1.16; 95% CI, 0.77-1.76; P > 0.05). Publication bias was not detected. CONCLUSIONS: Remnant-preserving ACLR provides superior functional outcomes and knee stability compared to standard ACLR without increasing complication rates. These findings support the adoption of remnant-preserving techniques in clinical practice. Further research is needed to assess long-term outcomes and refine patient selection criteria.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".