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Record W2896247111 · doi:10.1177/0363546518801314

Are Patellofemoral Joint Alignment and Shape Associated With Structural Magnetic Resonance Imaging Abnormalities and Symptoms Among People With Patellofemoral Pain?

2018· article· en· W2896247111 on OpenAlexafffund
Marienke van Middelkoop, Erin M. Macri, J.F.A. Eijkenboom, Rianne A. van der Heijden, Kay M. Crossley, Sita Bierma‐Zeinstra, Janneke L. de Kanter, Edwin H. G. Oei, Natalie J. Collins

Bibliographic record

VenueThe American Journal of Sports Medicine · 2018
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of British Columbia
FundersMedical Research CouncilCanadian Institutes of Health ResearchDutch Arthritis AssociationErasmus Universiteit RotterdamNational Health and Medical Research CouncilArthritis AustraliaAmerican Orthopaedic Society for Sports Medicine
KeywordsMagnetic resonance imagingMedicineOsteoarthritisSynovitisPatellofemoral jointKnee painPatellofemoral pain syndromeOdds ratioCartilageKnee JointPatellaFemurOrthodonticsRadiologyInternal medicineArthritisAnatomySurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Patellofemoral malalignment has been observed among people with patellofemoral pain (PFP) and may be associated with the presence of imaging features of osteoarthritis, symptoms, and function. PURPOSE: To determine whether patellofemoral joint alignment and bony shape are associated with (1) cartilage, bone, and soft tissue morphological abnormalities defined on magnetic resonance imaging (MRI) and (2) reported symptoms and function among people with PFP. STUDY DESIGN: Cross-sectional study; Level of evidence, 3. METHODS: Participants (mean ± SD age, 30.2 ± 9.5 years; range, 14-50 years; 78 females, 58.6%) completed questionnaires regarding demographics, pain, symptoms, and function and underwent a 3-T MRI scan of their more symptomatic eligible knee. Structural MRI abnormalities were scored with the MOAKS (Magnetic Resonance Imaging Osteoarthritis Knee Score), and MRI alignment and shape were measured with standardized methods. Associations among MOAKS features, PFP symptoms, and alignment and shape measures were evaluated with regression analyses (α = .05). RESULTS: Minor cartilage defects were present in 22 (16.5%) participants, patellar osteophytes in 83 (62.4%), anterior femur osteophytes in 29 (21.8%), Hoffa synovitis in 81 (60.9%), and prefemoral fat pad synovitis in 49 (36.8%). A larger Insall-Salvati ratio was significantly associated with the presence of patellar osteophytes (odds ratio [OR], 51.82; 95% CI, 4.20-640.01), Hoffa synovitis (OR, 60.37; 95% CI, 4.66-782.61), and prefemoral fat pad synovitis (OR, 43.31; 95% CI, 4.28-438.72) in the patellofemoral joint. A larger patellar tilt angle was significantly associated with the presence of minor cartilage defects (OR, 1.10; 95% CI, 1.00-1.20), the presence of patellar osteophytes (OR 1.12; 95%CI 1.02-1.22), and prefemoral fat pad synovitis (OR, 1.11; 95% CI, 1.03-1.20) in the patellofemoral joint. Finally, a larger bisect offset was significantly associated with the presence of minor cartilage defects (OR, 1.05; 95% CI, 1.00-1.11) and patellar osteophytes (OR, 1.07; 95% CI, 1.01-1.14) in the patellofemoral joint. The majority of patellofemoral alignment measures were not associated with symptoms or function. CONCLUSION: For people with PFP, the presence of morphological abnormalities defined on MRI appears to be related to particular patellofemoral alignment measures, including higher Insall-Salvati ratio (indicating patella alta), larger patellar tilt angle (indicating greater lateral tilt), and larger bisect offset (indicating greater lateral displacement). Hardly any associations were found with symptoms or function. So there might be a distinct subgroup of PFP that is more prone to developing patellofemoral osteoarthritis later in life, as particular alignment measures seem to be associated with the presence of patellar osteophytes. Prospective studies are required to investigate the longitudinal relationship between alignment or bony shape and morphological abnormalities defined on MRI in this patient population.

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 score0.273
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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".

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Citations37
Published2018
Admission routes2
Has abstractyes

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