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Record W4384831914 · doi:10.1016/j.arthro.2023.07.011

Suture‐Augmented Anterior Cruciate Ligament Repair for Proximal Avulsion or High‐Grade Partial Tears Shows Similar Side‐to‐Side Difference and No Clinical Differences at Two Years Versus Conventional Anterior Cruciate Ligament Reconstruction for Mid‐Substance Tears or Poor Anterior Cruciate Ligament Tissue Quality

2023· article· en· W4384831914 on OpenAlexaboutno aff
Wiemi A. Douoguih, Nicholas A. Apseloff, Jerome C. Murray, Richard Lance Kelly, Steven J. Svoboda

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
FundersArthrex
KeywordsAnterior cruciate ligamentAvulsionMedicineTearsFibrous jointSurgery

Abstract

fetched live from OpenAlex

PURPOSE: To compare objective and subjective clinical outcomes between suture-augmented anterior cruciate ligament (ACL) repair (SAACLR) and conventional ACL reconstruction (CACLR) with minimum 2-year follow-up. METHODS: In this nonrandomized, prospective study, 30 patients underwent SAACLR for proximal ACL avulsion or high-grade partial ACL tear (Sherman grade 1 or 2) and 30 patients underwent CACLR for proximal one-third/distal two-thirds junction tears and mid-substance tears (Sherman grade 3 or 4) tear types by 1 surgeon between 2018 and 2020. Failure was defined as ACL reinjury. Outcome measures were KT-1000 for side-to-side knee laxity evaluation, Visual Analog Scale for pain, International Knee Documentation Committee (IKDC) Subjective Knee Evaluation Form, Knee Injury and Osteoarthritis Severity Score (KOOS), Tegner Activity Scale, Western Ontario and McMaster Universities Osteoarthritis Index, Lysholm Knee Scoring Scale, and Single Assessment Numeric Evaluation. Minimal clinically important difference (MCID) was calculated for IKDC and KOOS subscores. RESULTS: Three failures (10%) occurred in the SAACLR group, with no failures in the CACLR group (P = .24). A total of 23 (85%) SAACLR patients and 27 (90%) CACLR patients had patient-reported outcomes and physical examination at minimum 2 years. Two-year KT-1000 testing with 20 lbs showed less than 1 mm side-to-side difference between the groups. No significant differences in the percentage of patients meeting the MCID were found between the SAACLR and CACLR groups at 2 years: IKDC, 10.81 (82%) versus 10.54 (93%) (P = .48); KOOS Pain, 11.55 (73%) versus 10.58 (78%) (P = .94); KOOS Symptoms, 8.15 (77%) versus 10.32 (74%) (P = 1.0); KOOS Activities of Daily Living, 12.19 (59%) versus 12.28 (70%) (P = .60); 18.99 (71%) versus 16.77 (86%) (P = .42). Significantly higher IKDC scores were observed with SAACLR versus CACLR at 3 months (P = .01) and 6 months (P = .02), and significantly higher Lysholm scale, Tegner Activity Scale, and all KOOS subscale scores were observed at 6 months. CONCLUSIONS: At 2 years after surgery, KT-1000 testing showed less than 1 mm side-to-side difference and no differences were observed between the groups in the percentage of patients who met or exceeded the MCID. Significantly higher early patient-reported outcome scores were found with SAACLR versus CACLR. The rerupture rate between the groups was not significantly different. LEVEL OF EVIDENCE: Level II, Prospective cohort study.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.367
Teacher spread0.317 · 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 teacher head, not a consensus.

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".

Quick stats

Citations39
Published2023
Admission routes1
Has abstractyes

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