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Record W2087155677 · doi:10.1186/1546-0096-8-14

Sonographic evaluation of pediatric localized scleroderma: preliminary disease assessment measures

2010· article· en· W2087155677 on OpenAlexaff
Suzanne C. Li, Melissa S. Liebling, Faridali Ramji, Sven Opitz, Arun Mohanta, Tatiana Kornyat, Shuzhen Zhang, Molly Dempsey, Carsten Hamer, Stephanie Edgerton, José Jarrín, Mike Malone, Andrea Doria

Bibliographic record

VenuePediatric Rheumatology · 2010
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsSickKids FoundationHospital for Sick Children
FundersHallym University Medical CenterArthritis Foundation
KeywordsVascularityMedicineEchogenicityUltrasoundRadiologyLesionDiseasePathologyMedical physics

Abstract

fetched live from OpenAlex

BACKGROUND: Our earlier work in the ultrasonograpy of localized scleroderma (LS) suggests that altered levels of echogenicity and vascularity can be associated with disease activity. Utrasound is clinically benign and readily available, but can be limited by operator dependence. We present our efforts to standardize image acquisition and interpretation of pediatric LS to better evaluate the correlation between specific sonographic findings and disease activity. METHODS: Several meetings have been held among our multi-center group (LOCUS) to work towards standardizing sonographic technique and image interpretation. Demonstration and experience in image acquisition were conducted at workshop meetings. Following meetings in 2007, an ultrasound measure was developed to standardize evaluation of differences in echogenicity and vascularity. Based upon our initial observations, we have labeled this an ultrasound disease activity measure. This preliminary measure was subsequently evaluated on over 180 scans of pediatric LS lesions. This review suggested that scoring levels should be expanded to better capture the range of observed differences. The revised levels and their definitions were formulated at a February 2009 workshop meeting. We have also developed assessments for scoring changes in tissue thickness and lesion size to better determine if these parameters aid evaluation of disease state. RESULTS: We have standardized our protocol for acquiring ultrasound images of pediatric LS lesions. A wide range of sonographic differences has been seen in the dermis, hypodermis, and deep tissue layers of active lesions. Preliminary ultrasound assessments have been generated. The disease activity measure scores for altered levels of echogenicity and vascularity in the lesion, and other assessments score for differences in lesion tissue layer thickness and changes in lesion size. CONCLUSIONS: We describe the range of sonographic differences found in pediatric LS, and present our efforts to standardize ultrasound acquisition and image interpretation for this disease. We present ultrasound measures that may aid evaluation of disease state. These assessments should be considered a work in progress, whose purpose is to facilitate further study in this area. More studies are needed to assess their validity and reliability.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.313
Teacher spread0.280 · 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".

Quick stats

Citations37
Published2010
Admission routes1
Has abstractyes

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