EVALUATING FATIGUE IN SYSTEMIC LUPUS ERYTHEMATOSUS: INSIGHTS FROM THE ISLA COHORT USING THE FUNCTIONAL ASSESSMENT OF CHRONIC ILLNESS THERAPY-FATIGUE SCALE
Notice bibliographique
Résumé
PV192 / #414 Poster Topic: AS22 - SLE Heterogeneity Background/Purpose The prevalence of fatigue among patients with systemic lupus erythematosus (SLE) varies between 67% and 90%, representing a multifaceted phenomenon that significantly impacts overall functionality. Despite its prevalence, fatigue is often an overlooked characteristic in clinical assessments. This condition is inherently complex, and numerous measurement tools exist. Notably, the Functional Assessment of Chronic Disease Therapy (FACIT) Fatigue Scale, a crucial tool in this study, has been validated for use in this patient population. Consequently, the objective of this study is to evaluate fatigue within a cohort of Guatemalan lupus patients utilizing the FACIT scale. Methods A cross-sectional study was conducted on 268 patients diagnosed with SLE at a single rheumatology center in Guatemala, specifically within the Lupus cohort of the Guatemalan Social Security Institute in the Autonomous Unit (ISLA). Participants completed the FACIT-fatigue questionnaire during the last follow-up evaluation in 2024, with prior authorization for using the scale by FACIT.org . Fatigue was defined as a score of less than 30 points. The study characterized participants based on the presence or absence of fatigue. Subsequently, we examined the correlation between disease activity by the SLEDAI-2K and the scores obtained from the FACIT-fatigue scale. Additionally, the frequency of responses to the statements within the FACIT scale was described according to its measurement scale. Results The study revealed that 40.67% of the patients experienced moderate to severe fatigue, with 93.6% being women (Table 1). In patients with fatigue, the mean FACIT score was recorded at 20.72, while 52.3% presented active disease, indicated by a mean SLEDAI-2K value of 4.17. The Pearson correlation analysis between disease activity, measured by the SLEDAI-2K, and fatigue, as assessed by the FACIT, revealed a coefficient of -0.16, suggesting a low negative correlation, as illustrated in Figure 1. Table 1. Figure 1. Furthermore, an examination of the statements included in the FACIT scale indicated that the statements with the worst ratings were “I feel tired, weak, listless (‘washed out’), I am tired,” and “I can do my usual activities” (Table 2). Table 2. Conclusions Fatigue is a prevalent symptom among individuals with lupus within our population and exhibits a low negative correlation with disease activity. This relationship indicates that the FACIT score decreases as the disease activity score increases, demonstrating greater fatigue levels in patients experiencing high disease activity. A critical implication of this fatigue is the difficulty in performing daily activities. Given these findings, it is imperative to recognize that fatigue should not be underestimated as a clinical symptom, and the ongoing monitoring of patients is essential to address this issue effectively.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».