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Record W4398763327 · doi:10.1093/rap/rkae061

Disease-specific definitions of new bone formation on spine radiographs: a systematic literature review

2024· article· en· W4398763327 on OpenAlexaff
Ümmügülsüm Gazel, Gizem Ayan, Nicole Hryciw, Jean-Philippe Delorme, Elliot Hepworth, Marcos Loreto Sampaio, Zaid Jibri, Jacob Karsh, Sibel Zehra Aydın

Bibliographic record

VenueRheumatology Advances in Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersCelgeneSanofiPfizer
KeywordsMedicineDiseaseRadiographySPINE (molecular biology)PathologyRadiologyBioinformatics

Abstract

fetched live from OpenAlex

Objectives: We aimed to explore the radiographic definitions of types of New Bone formation (NBF) by focusing on the terminology, description and location of the findings. Methods: Three systematic literature reviews were conducted in parallel to identify the radiographic spinal NBF definitions for spondyloarthritis (SpA), Diffuse Idiopathic Skeletal Hyperostosis (DISH) and Osteorathritis (OA). Study characteristics and definitions were extracted independently by two reviewers. Definitions were analysed and collated based on whether they were unique, modified or established from previous research. Results: We identified 33 studies that indicated a definition for the NBF in SpA, 10 for DISH and 7 for spinal OA. In SpA, the variations in syndesmophytes included the description as well as the subtypes and locations. The differentiation of syndesmophytes from osteophytes were included in 12 articles, based on the origin and the angle of the NBF and associated findings. The definitions of DISH varied in the number of vertebrae, level and laterality. For OA, five articles indicated that osteophytes arose from the anterior or lateral aspects of the vertebral bodies, and two studies required a size cut-off. Discussion: Our ultimate aim is to create formal NBF definitions for SpA, DISH and OA guided by an atlas, through a Delphi exercise with international experts. The improved ability to differentiate these conditions radiographically will not only allow the clinicians to accurately approach patients but also will help the researchers to better classify patient phenotypes and focus on accurate radiographic outcomes.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.351
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.322
Teacher spread0.299 · 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 designSystematic review
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

Citations7
Published2024
Admission routes1
Has abstractyes

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