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Record W2944156230 · doi:10.1177/1120700019848107

Capsular closure outweighs head size in preventing dislocation following revision total hip arthroplasty

2019· article· en· W2944156230 on OpenAlexaff
Christopher Pedneault, Dylan Tanzer, Anas Nooh, Karen Smith, Michael Tänzer

Bibliographic record

VenueHip International · 2019
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineFemoral headSurgeryTotal hip arthroplastyDislocationCapsuleArthroplasty

Abstract

fetched live from OpenAlex

Introduction: The high dislocation rate following revision total hip arthroplasty (THA) has been shown to be significantly reduced by closing the posterior capsule and by the use of large diameter femoral heads. The relative importance of each of these strategies on the rate of dislocation remains unknown. We undertook a study to determine if increasing femoral head diameter, in addition to posterior capsular closure would influence the dislocation rate following revision THA. Methods: We retrospectively reviewed 144 patients who underwent a revision THA. We included all patients who underwent revision THA with closure of the posterior capsule and who had at least a 2-year minimum follow-up. 48 patients had a 28-mm femoral head, 47 had a 32-mm head and 49 patients had a 36-mm femoral head. Results: At a minimum follow-up of 2 years, there were 3 dislocations. There were no dislocations in the 28-mm group (0%), 2 in the 32-mm group (4%) and 1 in the 36-mm group (2%). Head size alone was not found to significantly decrease the risk of dislocation (28-mm versus 32-mm p = 0.12; 28-mm versus 36-mm p = 0.27; 32-mm versus 36-mm p = 0.40). Conclusion: Both large diameter heads and careful attention to surgical technique with posterior capsular closure can decrease the historically high dislocation rate after revision THA when utilising the posterolateral approach. Capsular closure outweighs the effect of femoral head diameter in preventing dislocation following revision THA through a posterolateral approach.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.012
GPT teacher head0.280
Teacher spread0.268 · 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.

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

Citations14
Published2019
Admission routes1
Has abstractyes

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