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DISEASE ACTIVITY IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS: A STUDY OF THE GUATEMALAN ISLA COHORT

2025· article· en· W4410513246 on OpenAlexvenueno aff
Diana Michelle Páez, Nilmo Chávez, Estuardo Anzueto, Silvia Rivera, Gilbert Martínez, Luis Alberto Gómez, Valeria Rodríguez

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSystemic diseaseCohortDiseaseCohort studyConnective tissue diseaseLupus erythematosusSystemic lupus erythematosusDermatologyInternal medicineAutoimmune diseaseImmunologyAntibody

Abstract

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PV225 / #406 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by periods of exacerbation and remission. Despite significant advancements in treatment strategies in recent years, patients may experience variable episodes of disease activity throughout their lives. Comorbidities and the accessibility of therapeutic interventions can influence the progression of SLE. Consequently, this study aims to elucidate the current disease activity among patients with SLE in a Guatemalan cohort. Methods This study employs a cross-sectional design and involves reviewing 268 patient records diagnosed with SLE from a single rheumatology center in Guatemala, specifically the Lupus cohort of the Guatemalan Social Security Institute in the Autonomous Unit (ISLA). The analysis focused on disease activity data from the most recent clinical follow-up evaluation conducted in 2024. The Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) was employed to assess disease activity. The study systematically described activity domains, categorized by current disease status; the activity was defined as SLEDAI-2K > 4 points and included an overview of treatment regimens and comorbidities. Results The study identified that 48.88% of patients were active cases, predominantly women at 92.4%. The mean SLEDAI-2K score was 6.51, indicating significant disease activity, especially in renal aspects, with proteinuria in 28.2% and pyuria in 31.3%, with a mean proteinuria value over 24 hours amounting to 560.83 mg. Hypocomplementemia was found in 49.6% of cases, and 55.7% had anti-DNA levels elevated. Among inactive patients, 11.7% had low C3-C4 levels, and 26.3% had anti-DNA elevated. (Table 1) Corticosteroids were the most common treatment used by 79.6% of inactive and 82.4% of active patients, with average dosages of 5.63 mg and 9.96 mg, respectively. Hydroxychloroquine (HCQ) and azathioprine (AZA) were also used, with cyclophosphamide (CYC) as the primary rescue therapy during follow-up. Kidney transplantation occurred in 2.92% of inactive and 2.29% of active patients. (Table 2) Concerning comorbidities, the cardiovascular system was identified as the most affected, with arterial hypertension being the most prevalent condition, affecting 33.58% of the total patient sample. Moreover, 17 cases overlapped with other autoimmune diseases, the most common being systemic sclerosis (Table 2). Table 1. Table 2. Conclusions This study describes the current activity characteristics of the patient cohort observed. It is essential to emphasize our population’s high percentage of activity, particularly regarding significant renal involvement associated with immunological phenomena. Furthermore, the study underscores the presence of the serologically active clinically quiescent phenomenon, which is pertinent as it may predict future clinical activity. In light of the crucial role that access to medications and related comorbidities play in the manifestation of disease activity, this observation prompts a critical inquiry into whether we possess the necessary tools to address the challenges posed by lupus adequately.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.010
GPT teacher head0.272
Teacher spread0.262 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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