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Record W1968734232 · doi:10.1186/1546-0096-9-s1-p247

Achieving consensus on quality indicators (QI) for pediatric Systemic Lupus Erythematosus (pSLE)

2011· article· en· W1968734232 on OpenAlexaff
Joshua Pendl, Matt Hollander, Shannen Nelson, Wajeeha Yousaf, Michael W. Beresford, Marisa Klein‐Gitelman, Marilynn Punaro, Anne M. Stevens, Tadej Avčin, Graciela Espada, Tsz-Leung Lee, YL Lau, Jennifer Huggins, Esi Morgan-DeWitt, Hermine I. Brunner

Bibliographic record

VenuePediatric Rheumatology · 2011
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineDelphi methodFamily medicineQuality (philosophy)Pediatrics

Abstract

fetched live from OpenAlex

Background QI are retrospectively measurable elements of practice performance for which there is evidence or consensus that can be used to assess the quality of care provided. Aim To develop a set of consensus-derived QI for pSLE to serve as international benchmarks for the quality of patient care. Methods Based on the medical literature a Delphi survey was created and distributed to the physician membership of PRES, PANLAR, CARRA and the ACR via e-mail. Consensus was considered 80% or higher. Results There was consensus (97%) among the 297 respondents that simply applying QI developed by the ACR and EULAR for adults with SLE (adult QI) was insufficient and that distinct QI for pSLE were needed. Respondents concurred that 5 of the 20 ACR and 6 of the 24 EULAR adult QI are also suitable for pSLE. An additional 14 ACR and 13 EULAR adult QI might be useful for pSLE after modifications. There was no consensus whether to consider “Pregnancy” (45%) and “Reproductive Health” (65%) as domains in the set of pSLE QI. Conclusion There is great demand among pediatric rheumatologists to develop QI for pSLE. Initial agreement has been reached about the types and domains of QI for pSLE, but additional discussion and consensus formation under consideration of the medical evidence is needed to finalize a set of QI for pSLE that can be used to define standard of care treatment for children and adolescents with pSLE.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.816
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.054
GPT teacher head0.322
Teacher spread0.269 · 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.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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