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Record W4238577595 · doi:10.1177/2325967118s00062

Double Bundle Posterior Cruciate Ligament Reconstruction in 100 Patients at a Mean 3 Years Follow up: Outcomes were Comparable to an Anterior Cruciate Ligament Reconstructions

2018· article· en· W4238577595 on OpenAlexaboutno aff
Jorge Chahla, Mark E. Cinque, Andrew G. Geeslin, Grant J. Dornan, Gilbert Moatshe, Robert F. LaPrade

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePosterior cruciate ligamentWOMACSurgeryTearsArthrofibrosisPatient satisfactionRange of motionMinimal clinically important differenceOsteoarthritisRadiographyAnterior cruciate ligamentRandomized controlled trial

Abstract

fetched live from OpenAlex

Objectives: 1) To report on the outcomes after double-bundle PCL reconstructions in isolated versus combined injuries and acute versus chronic PCL tears and 2) to compare the outcomes of isolated double-bundle PCL reconstruction (DB PCLR) to isolated ACL reconstruction (ACLR). Methods: All patients who underwent a primary arthroscopic assisted DB PCLR for grade-III isolated or combined PCL injuries between May 2010 and March 2015 were reviewed. Patient reported outcome scores (Lysholm, Tegner, Western Ontario and McMaster Universities Arthritis Index (WOMAC), 12 item Short Form Health Survey (SF-12) Physical Component Summary (PCS) and patient satisfaction with outcome) and objective posterior stress radiographs were collected preoperatively and at a minimum of two years postoperatively. Cohort subanalyses comparing isolated versus combined, and acute versus chronic PCL reconstructions were also performed. Patients who underwent isolated ACLR over the same inclusion period were selected as a comparison group. Results: One hundred patients that underwent DB PCLR were included in this study. There were 31 isolated PCL injuries and 69 combined PCL injuries and the mean follow-up was 2.9 years (range 2-6 years). The median Tegner activity score improved from 2 to 5, Lysholm from 48 to 86, WOMAC from 35.5 to 5, and SF-12 PCS from 34 to 54.8 (all p values <0.001). The mean side-to-side difference (SSD) in posterior tibial translation on kneeling stress radiographs improved from 11.0 mm preoperatively to 1.6 mm postoperatively (p<0.001). There were no significant differences in postoperative functional scores between isolated PCL reconstructions and combined PCL reconstructions (all p values >0.229). The mean SSD in postoperative posterior tibial translation on stress radiographs was 1.2 ± 1.1 mm for isolated PCL tears and 1.7 ± 2.2 mm for combined PCL tears. The improvement in posterior tibial translation from preoperative to postoperative was significant for both the isolated and combined PCL injury groups (p<0.001). Only the Tegner score (p<0.001) and patient satisfaction (p=0.011) were significantly different postoperatively between acute and chronic reconstructions, both favoring acutely treated PCL injuries. The mean SSD in posterior tibial translation on stress radiographs improved from 11.6 ± 3.1 mm preoperatively to 1.9 ± 2.5 mm postoperatively (p<0.001) for acute PCL tears, and 10.3 ± 3.7 mm to 1.2 ± 1.0 mm (p<0.001) for chronic PCL tears. There were no significant differences in postoperative outcome scores between patients that underwent an isolated ACLR or isolated DB PCLR [all p values >0.064]. Conclusion: Significantly improved functional and objective outcomes were observed after anatomic-based DB PCLR at a mean 3 years follow-up, regardless of concomitant ligamentous pathology or timing to surgery. Posterior tibial translation was restored to near normal after DB PCLR. Additionally, contrary to previous reports, similar results were achieved compared to a control isolated ACLR cohort. [Table: see text][Figure: see text]

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)0.000
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.298
Teacher spread0.279 · 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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Citations0
Published2018
Admission routes1
Has abstractyes

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