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Record W4401828634 · doi:10.2106/jbjs.23.01007

Mapping the Course of Recovery Following Limb-Salvage Surgery for Soft-Tissue Sarcoma of the Extremities

2024· article· en· W4401828634 on OpenAlexaffabout
Alexander L. Lazarides, Zachary D. C. Burke, Manit K. Gundavda, David Clever, Anthony M. Griffin, Kim M. Tsoi, Peter C. Ferguson, Jay S. Wunder

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineSarcomaSoft tissue sarcomaSurgerySoft tissuePelvisRetrospective cohort study

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the goal of an acceptable functional result, the surgical treatment of soft-tissue sarcoma can portend a prolonged course of recovery. More comprehensive data on the expected course of recovery following extremity sarcoma surgery are needed to help to inform physicians and patients. The purpose of the present study was to describe the typical course of functional recovery following limb-salvage resection of a soft-tissue sarcoma and to identify factors associated with a delayed postoperative course of recovery. METHODS: A retrospective review of a prospectively maintained institutional database was performed for all patients undergoing surgical treatment with limb salvage of a soft-tissue sarcoma of the extremities or pelvis with at least 1 year of follow-up after the definitive surgical procedure. All patients were required to have preoperative functional outcomes recorded for either the Toronto Extremity Salvage Score (TESS) or the Musculoskeletal Tumor Society (MSTS) score and functional outcome measures at 1 year postoperatively. The primary outcome measures were time to recovery and maximal functional improvement. RESULTS: In this study, 916 patients met inclusion criteria following surgical resection of a soft-tissue sarcoma of the extremities. The median follow-up was 74 months. Patients typically achieved a return to their baseline preoperative level of function for all functional outcome measures by 1 to 2 years and achieved maximal functional recovery by 2 years postoperatively. Older age, female sex, deep tumor location, larger tumor size, pelvic location, osseous resection, motor nerve resection, free and/or rotational soft-tissue coverage, and postoperative complications were independently associated with worse TESS and/or MSTS scores (p ≤ 0.05). Tumor recurrence was associated with worse functional outcomes scores. An analysis was performed to determine which patients had a prolonged course of recovery (i.e., were considered to still be recovering). Older age, female sex, larger tumor size, osseous resection, and motor nerve resection were associated with a delayed course of recovery (p ≤ 0.04). Complications and tumor recurrence were associated with delayed functional recovery across all domains. CONCLUSIONS: Most patients will achieve maximal recovery by 2 to 3 years following surgical resection for soft-tissue sarcoma of the extremities. Older age, female sex, larger tumor size, osseous resection, motor nerve resection, postoperative complications, and tumor recurrence portend poorer functional outcomes and a delayed course of recovery. LEVEL OF EVIDENCE: Prognostic Level IV . See Instructions for Authors for a complete description of levels of evidence.

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)0.002
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.276
Teacher spread0.221 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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