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Record W4401828782 · doi:10.2106/jbjs.23.00795

Early Compared with Delayed Reconstruction in Multiligament Knee Injury

2024· article· en· W4401828782 on OpenAlexaff
Graeme Hoit, Jaskarndip Chahal, Ryan Khan, Matthew Rubacha, Aaron Nauth, Daniel B. Whelan

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineSurgeryRetrospective cohort studyPropensity score matchingQuality of life (healthcare)CohortInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of this study was to compare outcomes following early compared with delayed reconstruction in patients with multiligament knee injury (MLKI). METHODS: A retrospective cohort analysis of patients with MLKI from 2007 to 2019 was conducted. Patients who underwent a reconstructive surgical procedure with ≥12 months of postoperative follow-up were included. Patients were stratified into early reconstruction (<6 weeks after the injury) and delayed reconstruction (12 weeks to 2 years after the injury). Multivariable regression models with inverse probability of treatment weighting (IPTW) were utilized to compare the timing of the surgical procedure with the primary outcome (the Multiligament Quality of Life questionnaire [MLQOL]) and the secondary outcomes (manipulation under anesthesia [MUA], Kellgren-Lawrence [KL] osteoarthritis grade, knee laxity, and range of motion). RESULTS: A total of 131 patients met our inclusion criteria, with 75 patients in the early reconstruction group and 56 patients in the delayed reconstruction group. The mean time to the surgical procedure was 17.6 days in the early reconstruction group compared with 280 days in the delayed reconstruction group. The mean postoperative follow-up was 58 months. The early reconstruction group, compared with the delayed reconstruction group, included more lateral-sided injuries (49 patients [65%] compared with 23 [41%]; standardized mean difference [SMD], 0.44) and nerve injuries (36 patients [48%] compared with 9 patients [16%]; SMD, 0.72), and had a higher mean Schenck class (SMD, 0.57). After propensity adjustment, we found no difference between early and delayed reconstruction across the 4 MLQOL domains (p > 0.05). Patients in the early reconstruction group had higher odds of requiring MUA compared with the delayed reconstruction group (24 [32%] compared with 8 [14%]; IPTW-adjusted odds ratio [OR], 3.85 [95% confidence interval (CI), 2.04 to 7.69]; p < 0.001) and had less knee flexion at the most recent follow-up (β, 6.34° [95% CI, 0.91° to 11.77°]; p = 0.023). Patients undergoing early reconstruction had lower KL osteoarthritis grades compared with patients in the delayed reconstruction group (OR, 0.46 [95% CI, 0.29 to 0.72]; p < 0.001). There were no differences in clinical laxity between groups. CONCLUSIONS: Early reconstruction of MLKIs likely increases the likelihood of postoperative arthrofibrosis compared with delayed reconstruction, but it may be protective against the development of osteoarthritis. When considering the timing of MLKI reconstruction, surgeons should consider the benefit that early reconstruction may convey on long-term outcomes but should caution patients regarding the possibility of requiring an MUA. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.256
Teacher spread0.240 · 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".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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