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Record W2791603023 · doi:10.1177/0363546518755150

Anatomic Predictors of Sagittal Hip and Pelvic Motions in Patients With a Cam Deformity

2018· article· en· W2791603023 on OpenAlexafffund
K. C. Geoffrey Ng, Mario Lamontagne, Jonathan R.T. Jeffers, George Grammatopoulos, Paul E. Beaulé

Bibliographic record

VenueThe American Journal of Sports Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsUniversity of Ottawa
FundersEngineering and Physical Sciences Research CouncilCanadian Institutes of Health Research
KeywordsMedicinePelvic tiltSagittal planeDeformitySquatting positionPelvisAsymptomaticRange of motionOrthodonticsSurgeryPhysical therapyRadiology

Abstract

fetched live from OpenAlex

Background: As there is a high prevalence of patients with cam deformities and no ongoing hip dysfunction, understanding the biomechanical factors predicting the onset of symptoms and degenerative changes is critical. One such variable is how the spinopelvic parameters may influence hip and pelvic sagittal mobility. Hypothesis/Purpose: Pelvic incidence may predict sagittal hip and pelvic motions during walking and squatting. The purpose was to determine which anatomic characteristics were associated with symptoms and how they influenced functional hip and pelvic ranges of motion (ROMs) during walking and squatting. Study Design: Controlled laboratory study. Methods: Fifty-seven participants underwent computed tomography and were designated either symptomatic (n = 19, cam deformity with pain), asymptomatic (n = 19, cam deformity with no pain), or control (n = 19, no cam deformity or pain). Multiple femoral (cam deformity, neck angle, torsion), acetabular (version, coverage), and spinopelvic (pelvic tilt, sacral slope, pelvic incidence) parameters were measured from each participant’s imaging data, and sagittal hip and pelvic ROMs during walking and squatting were recorded using a motion capture system. Results: Symptomatic participants had large cam deformities, smaller femoral neck-shaft angles, and larger pelvic incidence angles compared with the asymptomatic and control participants. Discriminant function analyses confirmed that radial 1:30 alpha angle (λ 1 = 0.386), femoral neck-shaft angle (λ 2 = 0.262), and pelvic incidence (λ 3 = 0.213) ( P < .001) were the best anatomic parameters to classify participants with their groups. Entering these 3 parameters into a hierarchical linear regression, significant regressions were achieved for hip ROM only when pelvic incidence was included for walking ( R 2 = 0.20, P = .01) and squatting ( R 2 = 0.14, P = .04). A higher pelvic incidence decreased walking hip ROM ( r = −0.402, P = .004). Although symptomatic participants indicated a trend of reduced squatting hip and pelvic ROMs, there were no significant regressions with the anatomic parameters. Conclusion: A cam deformity alone may not indicate early clinical signs or decreased ROM. Not only was pelvic incidence a significant parameter to classify the participants, but it was also an important parameter to predict functional ROM. Symptomatic patients with a higher pelvic incidence may experience limited sagittal hip mobility. Clinical Relevance: Patients with symptomatic femoroacetabular impingement showed a higher pelvic incidence and, combined with a cam deformity and varus neck, can perhaps alter the musculature of their iliopsoas, contributing to a reduced sagittal ROM. With an early and accurate clinical diagnosis, athletes could benefit from a muscle training strategy to protect their hips.

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)0.000
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 score0.032
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.005
GPT teacher head0.236
Teacher spread0.231 · 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

Citations60
Published2018
Admission routes2
Has abstractyes

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