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Record W7034525015

Trends in Patient Outcome Scores in Orthopaedic Oncology: A Systematic Review

2022· article· en· W7034525015 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Commons - PCOM (Philadelphia College of Osteopathic Medicine) · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsOrthopedic surgeryStandardizationMEDLINEOutcome (game theory)Sports medicinePatient-reported outcome
DOInot available

Abstract

fetched live from OpenAlex

Introduction: The field of orthopaedic oncology has trailed in defining trends in reported outcome measures (ROMs) over the last decade. Although the Musculoskeletal Tumor Society (MSTS) Score is a well-recognized ROM, new ROMs developed and established in literature have created difficulty in identifying the standard ROM within the field. The aim of our study is to identify trends in the use of ROMs in orthopaedic oncology over time, as well as the frequency and distribution among specific pathologies and orthopaedic journals. Methods: A systematic review was conducted of all original articles reporting on topics relating to orthopaedic oncology in five orthopaedic journals over a ten-year period (2011-2021). The ROM used in all of the articles was recorded, in addition to study date, study design, clinical topic/pathology, and level of evidence. Results: Out of 197 articles reviewed that included at least one clinical outcome rating instrument, the most popular tools used were the MSTS (57%) and the Toronto Extremity Salvage (TESS) Score (12.5%), followed by the 36-Item Short Form (SF-36) Survey (5.11%), and Patient Reported Outcomes Measurement Information System (PROMIS) (3.14%). Conclusion: MSTS is consistently the most widely used ROM in orthopaedic oncology. Data from this study reflects that the reporting of ROMs in orthopaedic oncology is also sparse compared to other orthopaedic subspecialties. It is important to note the need for consensus for standardization of measuring outcome, and that the addition of PROMIS may provide clinicians a better perspective of patients’ overall outcome physically and mentally.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.042
GPT teacher head0.320
Teacher spread0.278 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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