MétaCan
Menu
Back to cohort
Record W4372300318 · doi:10.1002/jso.27300

Endoprosthetic reconstruction for lower extremity soft tissue sarcomas with bone involvement

2023· review· en· W4372300318 on OpenAlexaff
Philip D. Rowell, Peter C. Ferguson, Kim M. Tsoi, Jennifer Nevin, Rostislav Novak, Anthony M. Griffin, Jay S. Wunder

Bibliographic record

VenueJournal of Surgical Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineSoft tissueBone SarcomaSarcomaSurgeryRadiologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Bone resection and endoprosthetic reconstruction (EPR) in the setting of soft tissue sarcoma (STS) management is rare and incurs unique challenges. We aim to report on the surgical and oncological outcomes of this relatively previously undocumented cohort. METHODS: This is a single-center retrospective review of prospectively collected data for patients who required EPRs following resection of STSs of the lower extremity. Following inclusion criteria, we assessed 29 cases of EPR for primary STS of the lower limb. RESULTS: The mean age was 54 years (range 18-84). Of the 29 patients, there were 6 total femur, 11 proximal femur, 4 intercalary, and 8 distal femur EPRs. Fourteen of 29 patients (48%) underwent re-operations for surgical complications, with 9 relating to infection (31%). When a matched cohort analysis was performed comparing our cohort to STSs that did not necessitate EPR, a reduced rate of overall survival and metastasis-free survival was found in those requiring EPR. CONCLUSION: This series identifies a high rate of complication from EPRs performed for STS. Patients should be cautioned about the high rate of infection, surgical complications, and lower overall survival in this setting.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.092
GPT teacher head0.383
Teacher spread0.292 · 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 designOther design
Domainnot available
GenreReview

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

Citations9
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Surgical OncologySame topicSarcoma Diagnosis and TreatmentFrench-language works237,207