MétaCan
Menu
Back to cohort
Record W4414205250 · doi:10.2196/71909

Platelet Indices as Unequivocal Markers of Active Disease in Patients With Nonradiographic Axial Spondyloarthritis: Protocol for a Cross-Sectional Study

2025· article· en· W4414205250 on OpenAlexvenueno aff
Abhijeet Kumar Agrawal, Sourya Acharya, Jahnabi Bhagawati, Shivali Kashikar, Nishant Raj

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)PlateletDiseaseRandomizationMEDLINEPopulation

Abstract

fetched live from OpenAlex

BACKGROUND: Spondyloarthritis is divided into axial and peripheral subtypes. The axial subtype is further divided into ankylosing spondylitis (AS) or radiographic axial spondyloarthritis and nonradiographic axial spondyloarthritis (nr-axSpA). Although AS and nr-axSpA share some common features, nr-axSpA lacks X-ray-based sacroiliitis as defined by the modified New York criteria, that is, the presence of either bilateral grade 2 sacroiliitis or unilateral grade 3 sacroiliitis, which is present in AS. Disease activity in either of them is measured via C-reactive protein (CRP) levels or magnetic resonance imaging (MRI) of the pelvis showing sacroiliitis due to the presence of bone marrow edema. A person with active disease can have normal CRP and MRI findings, especially in nr-axSpA. Immune system activation during inflammation has been shown to alter platelet maturation and morphology, as reflected by platelet indices. These platelet indices have been studied in the past in various autoimmune diseases, such as psoriatic arthritis, AS, and rheumatoid arthritis, and have been correlated with disease activity. Particularly, in spondyloarthritis, platelet indices are more central to the pathology of sacroiliitis, and CRP, which is currently used, is a generalized marker of inflammation. Therefore, platelet indices can provide a better understanding of inflammation, particularly in patients with sacroiliitis. OBJECTIVE: This study aims to investigate whether platelet indices can be better markers of inflammation in patients with nr-axSpA. We will determine whether platelet indices are reliable biomarkers for measuring disease activity in patients with nr-axSpA. METHODS: All patients who are classified as having axial spondyloarthritis as per the Assessment of Spondylarthritis International Society criteria will be included in this study. Patients will be divided into 2 case groups: group A (patients without radiographic sacroiliitis [nr-axSpA]) and group B (patients with radiographic sacroiliitis [AS]). Healthy individuals will be enrolled as controls to compare and correlate platelet indices such as platelet count, plateletcrit, mean platelet volume, and platelet distribution width with CRP, erythrocyte sedimentation rate, and MRI findings in patients with AS and nr-axSpA. RESULTS: This is a nonfunded study. The data collection started on February 1, 2025, and we expect to complete the study by December 2027. As of July 2025, 7 individuals had been enrolled in groups A and B, respectively, and 5 individuals had been included in the control group. At the end of the study, we will be able to correlate whether platelet indices are trustworthy biomarkers of active disease in patients with nr-axSpA. CONCLUSIONS: If platelet indices prove to be better markers of active disease in patients with nr-AxSpA, then these markers should be included in the routine evaluation of these patients. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/71909.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0180.005

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 head0.080
GPT teacher head0.504
Teacher spread0.424 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research ProtocolsSame topicInflammatory Biomarkers in Disease PrognosisFrench-language works237,207