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PROPOSALS FOR DEFINITIONS OF MODERATE AND SEVERE DISEASE ACTIVITY IN SYSTEMIC LUPUS ERYTHEMATOSUS. IMPACT ON FLARES, QUALITY OF LIFE, DAMAGE ACCRUAL, HOSPITALIZATIONS AND MORTALITY

2025· article· en· W4410513199 on OpenAlexvenueno aff
Irene Altabás González, Íñigo Rúa‐Figueroa, Karen Roberts, Ivonne Lourdes Mamani, Coral Mouriño, Julia Martínez‐Barrio, María Galindo-Izquierdo, J. Calvo, Celia Erausquin, B. Serrano, E. Uriarte, Eva Tomero, Mercedes Freire, Ricardo Blanco, Eva Salgado, Antonio Fernández‐Nebro, C. Sangüesa, Javier Narváez, Natalia Mena, R. Menor, Elena Aurrecoechea, Oihane Ibarguengoitia-Barrena, Carlos Montilla-Morales, G. Bonilla, Tarek Salman-Montes, V Torrente-Segarra, Antonio Juan Más, María Jesús García-Villanueva, C. Moriano, Loreto Horcada, Nuria Lozano‐Rivas, C. L. Iñíguez, Marta Arévalo, Beatriz Paredes, Lorena Expósito, F. J. Toyos Sáenz de Miera, Eduardo Flores Fernández, Francisco J. Nóvoa, Jorge Fragío Gil, C. Bohórquez Heras, José María Pego‐Reigosa

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAccrualSystemic diseaseQuality of life (healthcare)DiseaseLupus erythematosusSystemic lupus erythematosusIntensive care medicineInternal medicineImmunologyAntibody

Abstract

fetched live from OpenAlex

PV199 / #53 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose To propose a definition for moderate disease activity state (MODAS) and severe disease activity state (SEDAS) in SLE and using the RELESSER-PROS cohort to describe the prevalence of both states of activity and to analyze the impact of this categorization on mortality, organ damage, flares, hospital admissions and health-related quality of life (HRQoL) Methods We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. MODAS and SEDAS definitions are based on: cSLEDAI, presence of severe manifestations and PGA. MODAS was defined as the presence of at least 1 of the following conditions: <4 cSLEDAI < 8 or 1< PGA < 2 (without severe clinical manifestations); and SEDAS: SLEDAIc >8 or PGA > 2 or the presence of severe SLEDAI and Non-SLEDAI manifestations. We analyzed the impact of remaining in MODAS or SEDAS in terms of several robust outcomes. Results 1,463 patients were included, mean age (±SD): 56 (±13.5) years; mean disease duration (±SD): 14 (±8.5) years. Patients had a mean (±SD) of 4.2 (±1.2) visits and a mean (±SD) follow-up time of 3.6 (±1.4) years. Patients with at least 1 visit in MODAS or in SEDAS had significantly higher numbers of flares, worse HRQoL, more damage accrual and more hospital admissions. Both, damage accrual and hospital admissions were significantly higher in SEDAS than in MODAS (Table 1 and Table 2). When comparing MODAS and SEDAS vs low disease activity, worse were the outcomes in the moderate/severe activity states (Figure 1). Table 1. Outcomes, according to the number of visits in SEDAS. Table 2. Outcomes, according to the number of visits in MODAS. Figure 1. Comparison of risk of admissions, damage accrual, flares and quality of life between different states of activity with each other. Conclusions Patients who were in MODAS or SEDAS at least once had worse outcomes in terms of numbers of flares, HRQoL, damage accrual, and hospital admissions. Furthermore, the more time spent in these states entailed greater risks. These results emphasize the importance of an adequate stratification of disease activity in SLE patients.

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)0.061
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.061
Threshold uncertainty score0.324

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.048
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0120.009
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0050.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.002

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 head0.048
GPT teacher head0.362
Teacher spread0.315 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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 routes1
Has abstractyes

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