MétaCan
Menu
Back to cohort
Record W2560232595 · doi:10.1371/journal.pone.0166865

Degeneration in ACL Injured Knees with and without Reconstruction in Relation to Muscle Size and Fat Content—Data from the Osteoarthritis Initiative

2016· article· en· W2560232595 on OpenAlexaboutno aff
Pia M. Jungmann, Thomas Baum, Michael C. Nevitt, Lorenzo Nardo, Alexandra S. Gersing, Nancy E. Lane, Charles E. McCulloch, Ernst J. Rummeny, Thomas M. Link

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftTechnische Universität MünchenGlaxoSmithKlineNovartis Pharmaceuticals CorporationPfizerNational Institutes of HealthU.S. Department of Health and Human ServicesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesFoundation for the National Institutes of Health
KeywordsMedicineOsteoarthritisAnterior cruciate ligamentBody mass indexWOMACThighCartilageACL injuryAnterior cruciate ligament reconstructionKnee JointSurgeryInternal medicineAnatomyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Anterior cruciate ligaments (ACL) injuries represent a major risk factor for early osteoarthritis (OA). PURPOSE: To evaluate the prevalence and 4-year progression of knee OA measured with 3T MR-imaging in individuals with ruptured, reconstructed or normal ACL and to assess the impact of thigh muscle characteristics. METHODS: A total of 54 knees (23/54 male, 31/54 female) were recruited from the Osteoarthritis Initiative (OAI). At baseline, 15/54 subjects had prevalent ACL ruptures and 15/54 subjects had prevalent ACL reconstruction (24/54 normal ACL). Western Ontario and McMasters Universities Arthritis Index (WOMAC) scores, Physical Activity Scores of the Elderly (PASE) and thigh muscle characteristics including strength, fat infiltration (Goutallier score) and thigh muscle cross-sectional area (CSA) MR measurements were obtained at baseline. Whole-organ MR-imaging Scores (WORMS) were obtained at baseline and at a 4-year follow-up time-point. Multivariate regression models, adjusting for covariates (age, gender, body mass index), were used for statistical analysis. RESULTS: At baseline, subjects with prevalent ACL ruptures had worse WORMS total scores (mean±SEM, 44.1±3.5) than subjects with ACL reconstruction (30.8±4.0; P = 0.015) and worse than subjects with normal ACL (21.3±3.0; P<0.001). Cartilage scores were worse in both femorotibial compartments in ACL injured knees than in knees with normal ACL (P<0.05). Knees with ACL reconstruction showed an increased degeneration of the medial meniscus (P = 0.036), cartilage degeneration at the medial femoral condyle (P = 0.011). In a multivariate regression model, including both ACL groups and total muscle characteristics as influence parameters, high thigh muscle CSA, high muscle/ fat ratio and low Goutallier scores were associated with less degenerative changes at the knee, independent of ACL status. Knees with ACL reconstruction showed an increased progression of cartilage degeneration at the medial tibia compared to the normal ACL group (P = 0.027). CONCLUSIONS: High thigh muscle CSA is associated with less degenerative changes at the knee, independent of the ACL status and may potentially be advantageous in the prevention of early OA.

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)0.003
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.067
GPT teacher head0.254
Teacher spread0.187 · 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

Citations26
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePLoS ONESame topicKnee injuries and reconstruction techniquesFrench-language works237,207