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Record W2055476374 · doi:10.1186/1546-0096-10-s1-a68

Developing juvenile localized scleroderma (jLS) consensus treatment regimens for comparative effectiveness studies

2012· article· en· W2055476374 on OpenAlexaff
Suzanne C. Li, Robert C. Fuhlbrigge, Fatma Dedeoğlu, Polly J. Ferguson, Gloria C. Higgins, Sandy Hong, Heidi Jacobe, Andrew Lasky, Ronald M. Laxer, Mimi C Morris, Elena Pope, C. Egla Rabinovich, Kathryn S. Torok

Bibliographic record

VenuePediatric Rheumatology · 2012
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineRheumatologyJuvenileInternal medicineScleroderma (fungus)OncologyImmunology

Abstract

fetched live from OpenAlex

A core group of pediatric rheumatologists based in CARRA was formed to evaluate and develop standardized jLS regimens and assessments. Two dermatologists who study jLS and a lay person were also recruited. Members reviewed literature on current treatments and assessments, and through surveys and Delphi processes, developed criteria to define different levels of disease severity, generated consensus regimens for jLS treatment, and agreed upon clinical parameters to evaluate disease activity and damage. Preliminary regimens and assessments were discussed with the CARRA membership, and modified based on feedback. We have developed criteria to define high, moderate, and low disease severity, and standardized clinical activity and damage assessments for jLS. An atlas of lesion images was generated to facilitate scoring the level of several parameters (erythema, hyperpigmentation, hypopigmentation, dermal atrophy, and subcutaneous tissue loss). See table 1 . Through use of the Delphi process, the jLS core group was able to generate consensus initial treatment regimens for MTX, MTX with oral CS, and MTX with intravenous CS, including a general tapering regimen for oral corticosteroids. Table 2 . There is a need for standardized jLS disease assessments and treatment regimens to be able to compare treatment efficacy. A CARRA subgroup has developed consensus assessments and treatment regimens for jLS. The efficacy of these regimens will be evaluated in future comparative effectiveness studies.

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)0.001
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 score0.341
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.142
GPT teacher head0.409
Teacher spread0.267 · 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
Published2012
Admission routes1
Has abstractyes

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