Clinical outcomes of contemporary lateral augmentation techniques in primary ACL reconstruction: a systematic review and meta‐analysis
Bibliographic record
Abstract
PURPOSE: The purpose of this investigation was to systematically review the contemporary literature to determine if a lateral augmentation (LA) added to an Anterior Cruciate Ligament Reconstruction (ACLR) provides better clinical and patient reported outcomes compared to an isolated ACLR. METHODS: , 2021 for level I-III randomized controlled trials (RCT) and prospective cohort studies without randomization, published after 2012 and with a minimum of two year follow-up. Publications were included when they reported on the objective knee stability examination, patient reported outcome scores, return to sports or graft rupture rate of any type of primary, isolated ACLR compared to ACLR combined with any type of LA. RESULTS: A total of 11 studies that reported on a combined total of 1892 unique patients were eligible for data extraction, including five RCTs and six prospective cohort studies. In 6 studies, an Anterolateral Ligament reconstruction (ALLR) was the LA of choice, while the 5 other publications used different types of Lateral Extra-articular Tenodesis (LET). A significant reduction in graft ruptures was found in patients treated with ACLR + LA (3%) compared to isolated ACLR (12%). Rotational laxity was significantly higher in isolated ACLR (14%) compared to ACLR + LA (6%). Addition of a LA reduced anterior translation when assessed via instrumented laxity testing. No significant difference was found in the patient reported outcome scores (IKDC and Tegner) between both patient groups, except for the Lysholm Score which was significant in favour of the ACLR + LA group. CONCLUSION: Combination of a primary ACLR with a LA can significantly reduce the risk of graft rupture and provide better rotatory stability, without jeopardizing patient reported outcomes. LEVEL OF EVIDENCE: Level III, Systematic Review of Level I, II and III studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.018 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".