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Femoral Head Blood Flow during Hip Resurfacing

2006· article· en· W2012279265 on OpenAlexaff
Paul E. Beaulé, Patricia A. Campbell, Paul Shim

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2006
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineFemoral headHip resurfacingFemoral neckBlood flowVascularitySurgeryReamerFemurArthroplastyRadiologyOsteoporosis

Abstract

fetched live from OpenAlex

Preserving femoral head vascularity during hip resurfacing may avoid femoral neck fractures and late femoral loosening. The posterior approach and notching of the femoral neck influence femoral head perfusion. However, it is not known if standard preparation of the femoral head during hip resurfacing can disrupt blood flow. Ten patients (10 hips) with advanced osteoarthritis having metal-on-metal hip resurfacing by means of a vascular-preserving surgical approach had femoral head blood flow measurements using laser Doppler flowmetry. Nine hips had a mean decrease of 70% in femoral head blood flow after standard reaming and preparation. The data suggest femoral head reaming during hip resurfacing substantially impacts blood flow to the femoral head and infers the extra osseous blood supply is still important in the arthritic femoral head. To avoid damaging the retinacular vessels, surgeons should direct the cylindrical reamer superolaterally staying as close as possible to the inferomedial neck.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.079
GPT teacher head0.408
Teacher spread0.329 · 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

Citations83
Published2006
Admission routes1
Has abstractyes

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