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Record W4406803289 · doi:10.36149/0390-5276-326

Use of highly porous shell and variable-angle locking screws for acetabular revision surgery: our experience and medium term results

2024· article· en· W4406803289 on OpenAlexaboutno aff
Jacopo Ambrosini, Stefano Giaretta, Giovanni Vicenti, Claudia Zocca, Claudio Buono, Pietro Spolettini, Giuseppe Solarino, Alberto Momoli

Bibliographic record

VenueLO SCALPELLO-OTODI Educational · 2024
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)Shell (structure)MedicineSurgeryMaterials scienceOrthodonticsPhysicsComposite material

Abstract

fetched live from OpenAlex

This article presents the clinical outcomes and experiences of our hospital in utilizing highly porous shells with variable-angle locking screws in acetabular revision surgery in patients with total hip arthroplasty (THA). A retrospective analysis was conducted on 16 acetabular revision cases, and patients were followed for an average of 22 months. The postoperative functional outcomes were evaluated with the Harris Hip Score (HHS) and Western Ontario and McMaster Universities Arthritis Index (WOMAC). Complications and radiographic findings were also analyzed. The results demonstrate promising outcomes with improved hip function, pain relief, minimal complications and implant stability. Our findings contribute to the growing evidence supporting the efficacy and safety of high porosity cotyles in revision surgery of THA.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.043
GPT teacher head0.310
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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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