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Aseptic Loosening is Uncommon with Uncemented Proximal Tibia Tumor Prostheses

2006· article· en· W2162296629 on OpenAlexaffabout
M. Flint, Anthony M. Griffin, Robert S. Bell, Peter C. Ferguson, Jay S. Wunder

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2006
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineSurgeryTibiaAseptic processingOrthopedic surgeryKnee JointRange of motion

Abstract

fetched live from OpenAlex

UNLABELLED: Aseptic loosening is a frequent cause of failure of cemented proximal tibia tumor endoprostheses. Uncemented prostheses may lessen this risk. We identified complications including aseptic loosening that affected prosthetic survival, limb survival and functional outcome for 44 consecutive patients after sarcoma resection from the proximal tibia and uncemented endoprosthetic reconstruction. At a mean final followup of 60 months (range, 9-152 months), there were no cases of aseptic loosening. Twelve (27%) patients suffered 14 complications leading to prosthetic failure due to infection (n = 7), stem fracture (n = 2), rotational instability (n = 1), vascular compromise (n = 2) and local tumor relapse (n = 2). However, limb salvage was successful in 37 of 44 (84%) patients. Functional assessment for 35 patients revealed a mean Toronto Extremity Salvage Score of 77/100 (range, 33-98) and Musculoskeletal Tumor Society 1987 and 1993 scores of 25/35 (range, 13-31) and 75/100 (range, 33-97), respectively. Mean knee joint flexion was 91 degrees (range, 0-110 degrees ) and knee extension lag was 6 degrees (range, 0-30 degrees ). Three patients with knee extensor complications had inferior functional outcomes. Aseptic loosening is uncommon with uncemented proximal tibia reconstruction, but decreasing other complications at this location remains challenging. LEVEL OF EVIDENCE: Therapeutic study, level IV-1 (case series).

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)0.002
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 score0.035
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.077
GPT teacher head0.407
Teacher spread0.330 · 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

Citations85
Published2006
Admission routes2
Has abstractyes

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