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Record W2905826320 · doi:10.1177/2325967118816317

Graft-Tunnel Mismatch in Endoscopic ACL Reconstruction: Reliability of Measuring Tunnel Lengths and Intra-articular Distance

2018· article· en· W2905826320 on OpenAlexaff
Tim Dwyer, Lucas Bristow, Nicholas Bayley, Ujash Sheth, Jihad Abouali, M. Lucas Murnaghan, David Wasserstein, Darrell Ogilvie‐Harris, Benjamin Fine, John Theodoropoulos, Jaskarndip Chahal

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsWomen's College HospitalUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineCadaveric spasmAnterior cruciate ligamentArthroscopyOrthopedic surgeryAnterior cruciate ligament reconstructionSurgeryOrthodonticsNuclear medicine

Abstract

fetched live from OpenAlex

BACKGROUND: A continued technical challenge for surgeons performing bone-patellar tendon-bone anterior cruciate ligament (ACL) reconstruction with endoscopic techniques is graft-tunnel mismatch. If tibial tunnel and intra-articular distances could be reliably estimated, surgeons could adjust the length of the femoral tunnel to minimize graft-tunnel mismatch. PURPOSE/HYPOTHESIS: To determine whether arthroscopic measurement of the following was reliable: femoral tunnel distance (FTD), tibial tunnel distance (TTD), intra-articular distance (IAD), and total distance (TD; sum of these 3 measurements). It was hypothesized that intraoperative measurement of these distances would be reliable. STUDY DESIGN: Controlled laboratory study. METHODS: Eight sports fellowship-trained orthopedic surgeons independently performed arthroscopic measurements of the FTD, TTD, IAD, and TD in 7 cadaveric knees in which femoral and tibial tunnels had been drilled. Each surgeon performed the measurements twice using an EndoButton depth gauge. Following this, each parameter was measured open with a medial parapatellar approach. Finally, a computed tomography (CT) scan of each knee was performed, with the FTD, TTD, and IAD measured by a musculoskeletal radiologist. Inter- and intrarater reliability of the arthroscopic measurements was calculated, as well as the correlation between arthroscopic measurements and open and CT measurements. RESULTS: Interrater reliability for the arthroscopic measurements was 0.8 for FTD, 0.89 for TTD, 0.61 for IAD, and 0.76 (range, 0.54-0.93) for TD. Intrarater reliability was 0.94 for FTD, 0.97 for TTD, 0.83 for IAD, and 0.93 for TD. The correlation between arthroscopic and open measurements was 0.9 for FTD, 0.94 for TTD, 0.4 for IAD, and 0.84 for TD. The correlation between arthroscopic and CT measurements was 0.85 for FTD, 0.92 for TTD, and 0.71 for IAD. CONCLUSION: The results of this study show that arthroscopic measurement of FTD and TTD has a high degree of intra- and interrater reliability, while that of IAD and TD demonstrates high intrarater reliability but moderate interrater reliability. CLINICAL RELEVANCE: Reliable measurement of the TTD and IAD can potentially allow adjustment of the FTD, minimizing graft-tunnel mismatch in endoscopic ACL reconstruction.

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 imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.252
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations6
Published2018
Admission routes1
Has abstractyes

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