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Record W4411433367 · doi:10.1016/j.ard.2025.06.1386

ABS0532 VALIDATION OF HANDHELD ULTRASOUND DEVICES FOR POINT OF CARE USE IN RHEUMATOLOGY: ANALYSIS FOR ENTHESITIS

2025· article· en· W4411433367 on OpenAlexaffabout
Ümmügülsüm Gazel, Shailja C. Shah, Marie Maguin, Rohan Machhar, P Leclerc, Lihi Eder, Gurjit S. Kaeley, Sahin Aydin

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsWomen's College HospitalNovartis (Canada)University of Ottawa
Fundersnot available
KeywordsMedicineEnthesitisRheumatologyInternal medicineMobile deviceMedical physicsArthritis

Abstract

fetched live from OpenAlex

Background: Ultrasonography (US) has experienced a rapid evolution in rheumatology. Despite many advantages being repeatedly shown, several barriers persist, equipment cost being an important one. Hand-held US technology promises to substantially lower this cost. However, before it can be used explicitly for rheumatology, its performance must be validated against gold-standard devices. Objectives: We aim to test the concurrent validity of a handheld US device versus a gold-standard device to detect characteristic features of enthesitis. Methods: Peripheral PsA patients with at least one tender and swollen joint were included. Each patient had consecutive US examinations using a handheld (Clarius Mobile Health Inc, HD3 L15 scanner) and a gold-standard US device (GE LogicE9-E10) for detecting elementary lesions of enthesitis (hypoechogenicity, thickening, erosion, enthesophyte, calcification and Doppler). Supraspinatus, triceps, common extensor tendon, quadriceps, patellar ligament (origin and insertion), Achilles tendon and plantar fascia entheses were evaluated. B-mode and power Doppler images were saved for each site and lesion. Every image was given a unique identifier number after collection for blinding purpose. A random order slide show was conducted for scoring, irrespective of the machine, anatomical site or patient, to ensure blindness. Scoring was done using previously validated methods. The inflammation score was obtained by summing hypoechogenicity, thickening, and Doppler scores, and the chronicity score was obtained by summing erosion, enthesophyte, and calcification scores. The total enthesitis score was determined by the sum of the inflammation and chronicity scores. Cohen's kappa coefficient was calculated to test the agreement for elementary lesions of enthesitis, in addition to intraclass correlation analysis. Results: Thirty patients were included in the study, scanning 480 entheses. On the day of the US, 19 (63.3%) patients had at least one tender enthesis on physical examination. The median (IQR) SPARCC enthesitis score was 1(0-5.0). The agreement was substantial (see Table 1) for enthesophytes and erosions; moderate for thickening, Doppler and hypoechogenicity; and fair for calcification (Table 1). A very strong agreement was detected between the devices both for the inflammation, chronicity and total enthesitis scores (ICC (intraclass correlation) and p values: inflammation: 0.909 and <0.001; chronicity: 0.917 and <0.001; total: 0.935 and <0.001). Conclusion: In this analysis, the handheld US device with L15 scanner showed moderate-substantial agreement to detect elementary lesions of enthesitis, with the exception of calcifications. In addition, a very strong consistency was found between the devices in inflammation, chronicity and total enthesitis scores, which enable physicians to evaluate enthesitis as a whole. These results encourage the use of handheld US devices for wider use. Table 1. The frequency, kappa and percent absolute agreement of elementary lesions in enthesitis areas. REFERENCES: NIL . Acknowledgements: NIL . Disclosure of Interests: Seyyid Acikgoz: None declared, Ummugulsum Gazel: None declared, Suharsh Shah Full-time employee at Novartis Pharmaceuticals Canada Inc, Marie Maguin Full-time employee at Novartis Pharmaceuticals Canada Inc, Rohan Machhar Full-time employee at Novartis Pharmaceuticals Canada Inc, Patrick Leclerc Novartis Employee, Lihi Eder Abbvie, Pfizer, UCB, Fresenius, Novartis, J&J, Abbvie, Pfizer, UCB, Novartis, Eli Lilly, BMS, Moonlake, J&J, Abbvie, Pfizer, UCB, Novartis, Eli Lilly, J&J, Fresenius Kabi, Gurjit Kaeley Research grants from Novartis, Gilead/ Galapagos, BMS,Janssen, Abbvie, Sibel Aydin received payment or honoraria for lectures, presentations, speaker's bureaus, manuscript writing, or educational events from Abbvie, Jannsen, Novartis, Pfizer, and UCB, received payment or honoraria for lectures, presentations, speaker's bureaus, manuscript writing, or educational events from Abbvie, Jannsen, Novartis, Pfizer, and UCB, stock options in Clarius, received consultant's fees from Abbvie, Celgene, Eli Lilly, Novartis, Pfizer, Sanofi, and UCB, received grants or contracts from Abbvie, Celgene, Eli Lilly, Jannsen, Novartis, Pfizer, Sanofi, and UCB. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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)0.014
metaresearch head score (Gemma)0.019
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.007

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 head0.042
GPT teacher head0.326
Teacher spread0.284 · 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
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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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