OP0276-HPR DAY-TO-DAY FLUCTUATIONS OF FATIGUE IN SYSTEMIC SCLEROSIS
Notice bibliographique
Résumé
Background Systemic sclerosis (SSc) is a rare auto-immune disease with a huge impact on physical health as well as social well-being, with fatigue being the major problem experienced by patients with respect to their well-being [1]. While fatigue is being reported to be fluctuating and unpredictable, the dynamic nature of fatigue is not well understood [1, 2]. Objectives To examine the within-person fluctuations and clinically meaningful changes in fatigue, as well as the within-person association of fatigue and time-varying determinants in SSc. Methods We performed a daily-diary study in adult patients with a clinical diagnosis of SSc. Patients with pulmonary hypertension or severe pulmonary function disturbances (i.e. vital capacity and diffusing capacity for carbon monoxide < 50%) were excluded. During 14 days patients completed daily assessments at four fixed time points (i.e. 9 a.m., 1 p.m., 5 p.m., 9 p.m.) of fatigue severity and time-varying determinants (i.e. negative affect, positive affect, pain, quality of sleep and perceived exertion of physical activity. As proxy for clinical meaningful change in fatigue the probability of acute change(PAC) was assessed, i.e. the chance that change in day-to-day fatigue levels exceeded the minimally clinical important difference for fatigue[3]. Using multilevel models the within-person fluctuations in fatigue and its association with time-varying determinants were examined. Based on the extent of clustering, the time-varying determinants were disentangled into their corresponding levels (within persons (within day as well as across days) and between persons) and added to the multilevel model. Models were adjusted for confounding (i.e. BMI, sex, age, and history of covid-infection) where appropriate. Results Fifty-seven patients with SSc, 35% male with mean(SD) age 54.3(14.6) years, participated. The disease duration was mean(SD) 6.9(4.8) years and 29.8 % was diagnosed with diffuse cutaneous SSc. Eighty percent of all observations were completed. During the study period, change in day-to-day level fatigue exceeded the MCID mean(SD) 5.7(1.9) times. The PAC was mean(SD) 0.44(0.14), ranging from 0.08-0.77. For fatigue a between-person variation of 49% and a within-person variation of 51% was observed. With respect to confounders, only BMI was significant in the models for time-varying negative and positive affect. The final models showed significant within-person association with fatigue fluctuations and changes in time-varying determinants within a day, between days and between patients (Table 1). Conclusion This is the first quantitative study showing that fatigue in SSc is characterized by a dynamic course and that approximately half of the day-to-day fluctuations are clinically meaningful, confirming the results of qualitative studies[2]. Moreover, when patients reported more fatigue than usual, they also reported more pain, more negative affect, less positive affect, more perceived exertion of physical activity, and worse quality of sleep than usual. References [1]Basta F et al., Clin Exp Rheumatol. 2018;36 Suppl 113(4):150-60. [2]Nakayama A et al., J Rheumatol. 2016;43(7):1363-75. [3]Khanna D et al., J Rheumatol. 2008;35(12):2339-43. Disclosure of Interests Arthiha Velauthapillai: None declared, Madelon Vonk Speakers bureau: Boehringer Ingelheim, Bristol-Myers Squibb, GSK, Janssen, MSD, Novartis and Roche, Consultant of: Boehringer Ingelheim and Janssen, Grant/research support from: Research grants from Boehringer Ingelheim, Janssen,Ferrer and Galapagos, Cornelia van den Ende: None declared, Johanna E. Vriezekolk Speakers bureau: Eli Lilly, but not pertaining to this study.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».