Comparison of clinical outcomes between hamstring tendon autografts and hybrid grafts in ACL reconstruction: a systematic review and meta-analysis
Bibliographic record
Abstract
Hamstring tendon (HT) autografts have become a popular choice for anterior cruciate ligament (ACL) reconstruction. However, small-diameter grafts are inevitably encountered during surgery, which have poor biomechanical properties. Hybrid grafts (HGs) using an allograft combined with small diameter HT are gaining interest from surgeons. There would be no difference between the HT autograft and HG in terms of failure, knee stability, and patient-reported outcomes. Systematic review and meta-analysis; Level of evidence, 4. The PubMed, Embase, web of science and Cochrane databases were systematically searched from their inception until July 1, 2022. Clinical trials that compared HG and HT autografts were included. The quality of the included studies was assessed with the Cochrane Collaboration’s risk of bias tool and the modified Newcastle-Ottawa Scale. Extracted data were pooled with fixed or random effects depending on the detected heterogeneity. A total of 14 eligible studies involving 1411 patients (HT: 863; HG: 548) were included in the quantitative meta-analysis. The mean age of the patients involved ranged from 14.6 to 40.4 years. Compared to patients who received HT autografts, patients receiving HGs had similar postoperative failure rate (OR, 0.99; P = 0.97; I 2 = 41%), side-to-side difference (MD, -0.16; P = 0.13; I 2 = 41%), Subjective IKDC (MD, 0.51; P = 0.58; I 2 = 69%), Lysholm (MD, 2.79; P = 0.1; I 2 = 79%), Tegner (MD, -0.88; P = 0.56; I 2 = 0%). When the available data for failure rate were analyzed by the dose of irradiation, patient age, and mean diameter of the HT, the results of subgroup analyses did not change substantially. This review found no significant differences in failure rates, knee stability, or patient-reported outcomes between autologous HT and HG in ACLR. Surgeons should prioritize autografts of adequate size through optimized techniques and consider hybrid grafts as a last resort, considering the risks associated with allografts.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.040 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".