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Record W3043375255 · doi:10.1177/0363546520932912

High-Grade Posterolateral Tibial Plateau Impaction Fractures in the Setting of a Primary Anterior Cruciate Ligament Tear Are Correlated With an Increased Preoperative Pivot Shift and Inferior Postoperative Outcomes After Anterior Cruciate Ligament Reconstruction

2020· article· en· W3043375255 on OpenAlexaboutno aff
David L. Bernholt, Grant J. Dornan, Nicholas N. DePhillipo, Zachary S. Aman, Mitchell I. Kennedy, Robert F. LaPrade

Bibliographic record

VenueThe American Journal of Sports Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineImpactionAnterior cruciate ligamentWOMACTibial plateau fractureSurgeryTearsAnterior cruciate ligament reconstructionOsteoarthritisOrthodonticsInternal fixation

Abstract

fetched live from OpenAlex

Background: Impaction fractures of the posterolateral tibial plateau have been previously described to occur in association with anterior cruciate ligament (ACL) tears; however, the effect of these injuries on patient-reported outcomes (PROs) after ACL reconstruction (ACLR) is not well known. Purpose: (1) To assess the effect of posterolateral tibial plateau impaction fractures on preoperative clinical knee stability assessed by the Lachman and pivot-shift examinations and (2) to assess the effect of impaction fractures on PROs after ACLR. Study Design: Cohort study; Level of evidence, 3. Methods: Patients undergoing ACLR for primary ACL tears with available magnetic resonance imaging (MRI) scans were included in this study. MRI scans were reviewed for the presence of posterolateral tibial plateau impaction fractures, which were classified according to the morphological variant. Associations with clinical laxity determined by an examination under anesthesia were assessed using binary logistic regression. Also, 2-year postoperative PROs (12-Item Short Form Health Survey [SF-12] Mental Component Scale and Physical Component Scale [PCS], Lysholm, Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC], and Tegner scores) were modeled using multiple ordinal logistic regression to assess the effect of posterolateral tibial plateau impaction fracture classification while adjusting for other covariates. Pearson correlation coefficients (PCCs) were used to assess for correlations between postoperative PROs and the amount of tibial plateau bone loss present. Results: Displaced posterolateral tibial plateau impaction fractures were present in 407 (49.3%) of 825 total knees included in this study. Knees with type IIIB impaction fractures had an increased likelihood of having a high-grade pivot shift (odds ratio, 2.3; P = .047), with no other impaction fracture types showing a significant association. There were no significant associations between posterolateral tibial plateau impaction fracture type and a higher Lachman grade. Of the 599 eligible knees with 2-year follow-up, postoperative information was obtained for 419 (70.0%). Patients improved in all PROs at a mean of 3.0 years after ACLR ( P < .001). Multiple ordinal logistic regression demonstrated a posterolateral tibial plateau impaction fracture as an independent predictor of the postoperative Lysholm score, with higher grade impaction fractures showing decreased Lysholm scores. Pearson correlation testing demonstrated weak but statistically significant correlations between sagittal bone loss of posterolateral tibial plateau impaction fractures and SF-12 PCS (PCC = –0.156; P = .023), WOMAC total (PCC = 0.159; P = .02), Lysholm (PCC = –0.203; P = .003), and Tegner scores (PCC = –0.151; P = .032). Conclusion: When classified into distinct morphological subtypes, high-grade posterolateral tibial plateau impaction fractures were independently associated with decreased postoperative outcomes after ACLR when controlling for other demographic or clinical variables. Patients with large depression-type posterolateral tibial plateau impaction fractures (type IIIB) had an increased likelihood of having high-grade pivot-shift laxity on clinical examination under anesthesia.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.249
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.006
GPT teacher head0.259
Teacher spread0.253 · 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.

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

Citations49
Published2020
Admission routes1
Has abstractyes

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