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Record W4398237140 · doi:10.1186/s43166-024-00258-5

Serum sclerostin as a biomarker of disease activity in ankylosing spondylitis in correlation with radiographic imaging

2024· article· en· W4398237140 on OpenAlexaboutno aff
Nouran Medhat Abd El Samad Sakrana, Nevine Mohamed ElSayed Badr, Mona Abd El-Sabour Hassan, Marwa Ahmed Kamel Hassan

Bibliographic record

VenueEgyptian Rheumatology and Rehabilitation · 2024
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAnkylosing spondylitisSclerostinMedicineRadiographyBiomarkerSpondylitisDiseaseRadiologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Abstract Background The wingless signaling pathway of bone development is inhibited by sclerostin, which may contribute to the etiology of ankylosing spondylitis. Aim The study aimed to evaluate serum sclerostin levels in ankylosing spondylitis patients and investigate how it correlated with radiographic damage using the Spondylo-arthritis Research Consortium of Canada index (SPARCC), disease activity, and functional impairment. Results This cross-sectional case–control study revealed a significantly lower mean serum sclerostin (11.28 ng/ml) in AS patients compared with controls (101.25 ng/ml). Serum sclerostin levels showed a significant negative correlation with each of Bath Ankylosing Spondylitis Metrology Index (BASMI) ( p = 0.043), sacroiliac joints SPARCC, spine SPARCC, and overall SPARCC scores ( p = 0.012, p = 0.036, and p = 0.007). The detection of AS, serum sclerostin levels ≤ 20 ng/ml showed 100% sensitivity and specificity. Conclusion Serum sclerostin had good discriminating power between ankylosing spondylitis cases and healthy control individuals and was correlated with subclinical activity status on magnetic resonance imaging.

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 score0.017
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.252
Teacher spread0.246 · 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
Published2024
Admission routes1
Has abstractyes

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