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Record W2405105365 · doi:10.1177/107110070202300214

Microscopic Metallic Wear and Tissue Response in Failed Titanium Hallux Metatarsophalangeal Implants: Two Cases

2002· article· en· W2405105365 on OpenAlexaff
Navid Ghalambor, David R. Cho, Steven R. Goldring, Aneel Nihal, Elly Trepman

Bibliographic record

VenueFoot & Ankle International · 2002
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsMedicineRadiodensityImplantOsteolysisTitaniumSoft tissueGiant cellRadiographySurgeryAnatomyPathologyMaterials science

Abstract

fetched live from OpenAlex

The membranes present at the implant-bone interface were retrieved from two patients with titanium single stem hallux implants that had failed. Both patients had pain and valgus deformity of the hallux, and radiographs showed a radiolucent shadow around the implant stem, with thinning of the dorsal cortex of the proximal phalanx in one patient. After removal of the implants, arthrodesis of the first metatarsophalangeal (MP) joint was performed. Histologic analysis of the membrane tissue at the implant-bone interface showed a synovial-like appearance. There was a fibrous tissue stroma adjacent to the bone surface, with multiple regions of scalloping covered by mononuclear cells. Fine metallic debris was seen throughout the fibrous tissue. Multinucleated foreign body giant cells were sparsely observed associated with fine particulate metallic wear debris similar to observations from failed total hip arthroplasties. The histologic appearance is evidence that foreign-body granulomatous infiltration associated with metallic wear debris may be a causative factor of peri-implant osteolysis leading to aseptic loosening and failure of titanium single stem hallux implants.

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 score0.352
Threshold uncertainty score0.998

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)0.0030.000

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 head0.028
GPT teacher head0.304
Teacher spread0.276 · 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

Citations30
Published2002
Admission routes1
Has abstractyes

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