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Record W1957465265 · doi:10.4137/cmamd.s28347

Role of Physical Evaluation in the Early Identification of Axial Spondyloarthritis: A Research Proposal

2015· article· en· W1957465265 on OpenAlexaff
Marcelo Peduzzi de Castro, Simon Stebbings, Stephan Milosavljevic, Melanie D. Bussey

Bibliographic record

VenueClinical Medicine Insights Arthritis and Musculoskeletal Disorders · 2015
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSacroiliac jointMedicineMagnetic resonance imagingGold standard (test)Provocation testPhysical therapyLow back painPhysical examinationRadiologyBack painPathology

Abstract

fetched live from OpenAlex

The aim of this study was to present a rationale to explore the use of clinical tests for the sacroiliac joints to detect early axial spondyloarthritis (SpA) and to suggest a protocol to validate these clinical tests. Based on the European Guidelines for Diagnosis and Treatments of Pelvic Girdle Pain, we propose a set of six clinical tests to identify the likely presence of inflammation in the sacroiliac joints associated with early axial SpA. As magnetic resonance imaging (MRI) is the current gold standard used to identify inflammation in the sacroiliac joints, the results of the proposed set of clinical tests are compared with those from the MRI examinations. We hypothesize that specific clinical tests, which combine pain provocation and functional tests, for assessing the sacroiliac joints will help to identify early active inflammation at the sacroiliac joints in axial SpA. If such tests prove to be sensitive and specific, they could add further value to the diagnostic classification criteria for axial SpA.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.061
GPT teacher head0.412
Teacher spread0.350 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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