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Record W3133840173 · doi:10.3390/life11030218

The Role of Clinical and Ultrasound Enthesitis Scores in Ankylosing Spondylitis

2021· article· en· W3133840173 on OpenAlexaboutno aff
Alesandra Florescu, Vlad Pădureanu, Dan Nicolae Florescu, Anca Bobîrcă, Lucian-Mihai Florescu, Ana Maria Bumbea, Rodica Pădureanu, Anca Emanuela Mușetescu

Bibliographic record

VenueLife · 2021
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsEnthesitisAnkylosing spondylitisBASDAIMedicineInternal medicinePhysical therapySpondylitisRheumatologyDiseasePsoriatic arthritis

Abstract

fetched live from OpenAlex

Introduction: Ankylosing spondylitis (AS) is a chronic inflammatory disease, part of the spondyloarthritis (SpA) group, characterized by axial (spine and sacroiliac joints), entheseal, and peripheral joint involvement, which is frequently associated with extra-articular manifestations. Material and Methods: The study included a number of 30 patients diagnosed with AS according to the New York modified criteria, with history of entheseal pain, hospitalized between 2016–2018 in the Department of Rheumatology of the Emergency County Hospital of Craiova. Results: Regarding the Belgrade Ultrasound Enthesitis Score (BUSES) score and the disease activity calculated using the Ankylosing Spondylitis Disease Activity Score (ASDAS), they did not show a statistically significant association (p = 0.738). Additionally, BUSES did not have a statistically significant association with the disease activity quantified by the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) score (p = 0.094). The Spondyloarthritis Research Consortium of Canada Enthesitis Index (SPARCC) clinical score was not statistically associated with ASDAS (p = 0.434) nor with BASDAI (p = 0.130). The SPARCC clinical score and the BUSES ultrasound score were statistically significantly associated, registering a value of p = 0.018. Conclusions: Our study proved a significant correlation between SPARCC and BUSES, although in literature the evidence is contrasting.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.317
Teacher spread0.295 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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