Technology‐assisted anterior cruciate ligament reconstruction improves tunnel placement but leads to no change in clinical outcomes: a systematic review and meta‐analysis
Bibliographic record
Abstract
PURPOSE: To investigate the effect of technology-assisted Anterior Cruciate Ligament Reconstruction (ACLR) on post-operative clinical outcomes and tunnel placement compared to conventional arthroscopic ACLR. METHODS: CENTRAL, MEDLINE, and Embase were searched from January 2000 to November 17, 2022. Articles were included if there was intraoperative use of computer-assisted navigation, robotics, diagnostic imaging, computer simulations, or 3D printing (3DP). Two reviewers searched, screened, and evaluated the included studies for data quality. Data were abstracted using descriptive statistics and pooled using relative risk ratios (RR) or mean differences (MD), both with 95% confidence intervals (CI), where appropriate. RESULTS: Eleven studies were included with total 775 patients and majority male participants (70.7%). Ages ranged from 14 to 54 years (391 patients) and follow-up ranged from 12 to 60 months (775 patients). Subjective International Knee Documentation Committee (IKDC) scores increased in the technology-assisted surgery group (473 patients; P = 0.02; MD 1.97, 95% CI 0.27 to 3.66). There was no difference in objective IKDC scores (447 patients; RR 1.02, 95% CI 0.98 to 1.06), Lysholm scores (199 patients; MD 1.14, 95% CI - 1.03 to 3.30) or negative pivot-shift tests (278 patients; RR 1.07, 95% CI 0.97 to 1.18) between the two groups. When using technology-assisted surgery, 6 (351 patients) of 8 (451 patients) studies reported more accurate femoral tunnel placement and 6 (321 patients) of 10 (561 patients) studies reported more accurate tibial tunnel placement in at least one measure. One study (209 patients) demonstrated a significant increase in cost associated with use of computer-assisted navigation (mean 1158€) versus conventional surgery (mean 704€). Of the two studies using 3DP templates, production costs ranging from $10 to $42 USD were cited. There was no difference in adverse events between the two groups. CONCLUSION: Clinical outcomes do not differ between technology-assisted surgery and conventional surgery. Computer-assisted navigation is more expensive and time consuming while 3DP is inexpensive and does not lead to greater operating times. ACLR tunnels can be more accurately located in radiologically ideal places by using technology, but anatomic placement is still undetermined because of variability and inaccuracy of the evaluation systems utilized. LEVEL OF EVIDENCE: Level III.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.028 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".