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Record W2047984491 · doi:10.1177/0961203312454344

SLEDAI-2K Responder Index 50 captures 50% improvement in disease activity over 10 years

2012· article· en· W2047984491 on OpenAlexaffabout
Zahi Touma, DD Gladman, Dominique Ibañez, Murray B. Urowitz

Bibliographic record

VenueLupus · 2012
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusLupus nephritisInternal medicineDisease

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the frequency and the time to complete recovery identified by Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) and the time to partial recovery identified by the SLEDAI-2K Responder Index 50 (SRI-50) in three laboratory systems over 10 years. METHODS: This is a retrospective analysis of the data available from the Toronto Lupus Clinic over the last 10 years. Patients with SLEDAI-2K renal, immunological and hematologic active descriptors were identified. The percentage of descriptors with partial and complete recovery was studied at one year and over the study period. Descriptive analysis and the Kaplan-Meier estimator were applied to study the time to partial and complete recovery. RESULTS: Of the 795 patients, 94% had an active system at some point during the study period. Partial recovery was shown in 66% of patients by SRI-50 for at least one descriptor over the study period. None of these partial findings identified would have been captured using SLEDAI-2K alone. The time to partial recovery identified by SRI-50 was shorter than the time to complete recovery identified by SLEDAI-2K. CONCLUSION: The SRI-50 is a valid responder index derived form SLEDAI-2K and is very helpful in identifying clinically important improvement in active laboratory descriptors in an efficient time.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.022
GPT teacher head0.315
Teacher spread0.292 · 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

Citations28
Published2012
Admission routes2
Has abstractyes

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