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Record W2102593535 · doi:10.1302/0301-620x.93b8.25750

Intercalary diaphyseal endoprosthetic reconstruction for malignant tibial bone tumours

2011· article· en· W2102593535 on OpenAlexaboutno aff
Mathew David Sewell, Sammy A. Hanna, A. McGrath, Will Aston, Gordon Blunn, Rob Pollock, John Skinner, S.R. Cannon, Timothy Briggs

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2011
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurgeryDiaphysisComplicationImplantBone tumoursOrthopedic surgeryProsthesisRetrospective cohort study

Abstract

fetched live from OpenAlex

The best method of reconstruction after resection of malignant tumours of the tibial diaphysis is unknown. In the absence of any long-term studies analysing the results of intercalary endoprosthetic replacement, we present a retrospective review of 18 patients who underwent limb salvage using a tibial diaphyseal endoprosthetic replacement following excision of a malignant bone tumour. There were ten men and eight women with a mean age of 42.5 years (16 to 76). Mean follow-up was 58.5 months (20 to 141) for all patients and 69.3 months (20 to 141) for the 12 patients still alive. Cumulative patient survival was 59% (95% confidence interval (CI) 32 to 84) at five years. Implant survival was 63% (95% CI 35 to 90) at ten years. Four patients required revision to a proximal tibial replacement at a mean follow-up of 29 months (10 to 54). Complications included metastases in five patients, aseptic loosening in four, peri-prosthetic fracture in two, infection in one and local recurrence in one. The mean Musculoskeletal Tumor Society score and the mean Toronto Extremity Salvage Score were 23 (17 to 28) and 74% (53 to 91), respectively. Although rates of complication and revision were high, custom-made tibial diaphyseal replacement following resection of malignant bone tumours enables early return to function and provides an attractive alternative to other surgical options, without apparent compromise of patient survival.

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)0.001
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 score0.400
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0000.000

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 head0.038
GPT teacher head0.231
Teacher spread0.193 · 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

Citations83
Published2011
Admission routes1
Has abstractyes

Explore more

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