MétaCan
Menu
Back to cohort
Record W4206539004 · doi:10.2147/ijgm.s347133

Distribution of Acute and Chronic Lesions in the Sacroiliac Joints of Patients with Axial Spondyloarthritis

2022· article· en· W4206539004 on OpenAlexaboutno aff

Bibliographic record

VenueInternational Journal of General Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsSacroiliac jointAxial spondyloarthritisDistribution (mathematics)SpondylarthritisSacroiliitisAxial skeleton

Abstract

fetched live from OpenAlex

OBJECTIVE: In this study, we aimed to investigate whether there was a pattern of distribution of acute and chronic lesions in the sacroiliac joints (SIJ) of patients with axial spondyloarthritis (axSpA). METHODS: A total of 96 patients diagnosed as axSpA were retrospectively included in this study. The Spondyloarthritis Research Consortium of Canada sacroiliac joint inflammation score (SIS) and structural score (SSS) were used to evaluate the acute and chronic lesions in the SIJs. Scores representing the distribution of bone marrow edema, fatty lesions and erosions were extracted respectively. By dividing the SIJs into sacral or iliac sections, upper or lower sections, anterior and posterior levels, differences of scores representing acute and chronic lesions were analyzed by Kruskal Wallis' tests. RESULTS: SIS scores were not significantly different in sacral or iliac sections, in upper or lower sections, on anterior or posterior levels. SSS scores were also not significantly different in different sections, except for higher occurrence rates of erosions in the iliac sections. Post-hoc analysis showed that there was a higher erosion score in the left ilium than left sacrum, as well as in right ilium than left sacrum. CONCLUSION: There was no specific distribution pattern of acute or chronic lesions in the SIJs in patients with axSpA. A bigger study sample was needed to confirm the distribution of erosions in sacral or iliac sections.

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)0.000
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 score0.123
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.010
GPT teacher head0.271
Teacher spread0.261 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of General MedicineSame topicSpondyloarthritis Studies and TreatmentsFrench-language works237,207