No difference between extraction drilling and serial dilation for tibial tunnel preparation in anterior cruciate ligament reconstruction: a systematic review
Bibliographic record
Abstract
IMPORTANCE: This review highlights a lack of consensus and need for further study regarding optimal tibial tunnel preparation method in anterior cruciate ligament reconstruction (ACLR). OBJECTIVE: This review examines existing clinical and biomechanical outcomes of both extraction drilling (ED) and serial dilation (SD) as a technique for tibial tunnel preparation in ACLR. EVIDENCE REVIEW: In accordance with PRISMA guidelines, three electronic databases (MEDLINE, EMBASE, and PubMed) were searched and systematically screened in duplicate from database inception to September 6, 2017 for English-language, human studies, of all levels of evidence that examined ED and/or SD for tibial tunnel preparation in ACLR. Data including patient demographics, tibial tunnel preparation techniques, biomechanical and clinical outcomes and complications were retrieved from eligible studies. FINDINGS: ED was used in 71 patients, who were mean age 29.9 years (range: 17-50), 68% male, and followed for mean 16.5 months (range: 3.8-46). SD was used in 70 patients (70 knees), who were mean age 29.3 years (range: 18-50), 69% male, and followed for mean 14.1 months (range: 3.8-46). There were no statistically significant differences (mean preoperative; mean postoperative) for either tibial preparation technique for Lysholm (50.1; 92.5), Tegner (3.5; 6.1), International Knee Documentation Committee (IKDC) (48.8; 92.7), and Lachman or laxity scores. However, ED demonstrated statistically significant increased postoperative tibial tunnel expansion (1.8 mm versus 1.4 mm) and (at 12 weeks) graft migration at the tibial fixation site (1.3 mm versus 0.8 mm). Across biomechanical studies, there were no statistically significant differences (ED; SD) with forces required to initiate graft slippage (156 N; 174 N), graft stiffness (187 N; 186.5 N), and screw torque (1.6 N/m; 1.8 N/m). ED demonstrated a lower mean load to failure for the graft construct (433 N versus 631 N; p<0.05). CONCLUSIONS AND RELEVANCE: Though biomechanical data demonstrated lower mean load to failure for the graft using ED, clinical data suggest increased tibial tunnel expansion and post-operative graft migration at the tibial fixation site. Future studies with long-term follow-up data are required to ascertain the optimal technique for graft incorporation and postoperative success. LEVEL OF EVIDENCE: IV:Systematic Review of Level I-IV studies.
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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 | 0.009 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".