ASSESSMENT OF FATIGUE IN A MONOCENTRIC ITALIAN COHORT OF PATIENTS AFFECTED BY SLE AND OTHER RHEUMATIC DISEASES (RDS) THROUGH VALIDATED QUESTIONNAIRES
Bibliographic record
Abstract
PV172 / #761 Poster Topic: AS19 - Patient-Reported Outcome Measures Background/Purpose Fatigue is one of the most common and disabling symptoms which might impair quality of life (QoL) in patients affected by chronic diseases.[1] Previous data showed that 35-82% of patient with rheumatic diseases (RDs) reported fatigue.[2] Often, fatigue is associated with a perceived higher disease activity and it has been identified as one of the implicated factors in the failure to achieve the remission.[3] We aimed to assess fatigue in our cohort of SLE and other RDs patients using validated questionnaires, to evaluate any differences in fatigue compared with healthy subjects and between various RDs subgroups. These represents the preliminary results of the IDEA-FAST project that aims to identify novel, objective and reliable digital endpoints of fatigue, by using mobile digital technologies in patients affected by neurodegenerative disorders and immune-mediated inflammatory diseases Methods We conducted a cross-sectional observational monocentric study including patients with SLE, rheumatoid arthritis (RA), primary Sjögren syndrome (pSS) and healthy volunteers (HV) between August 2023 and July 2024. Patients with a primary diagnosis of major sleep disorder and fibromyalgia were excluded. Fatigue was rated on a visual analog scale (fVAS:0-100 mm) and through FACIT-Fatigue and modified Mental Fatigue Scale (m-MFS). Additionally, all patients completed questionnaires investigating sleep quality (sqVAS and Medical Outcomes Study-Sleep Scale, MOS-SS), daily sleepiness (Epworth Sleepiness Scale, ESS), anxiety (Generalized Anxiety Disorder 2-item, GAD-2), depression (Patient Health Questionnaire-2, PHQ-2), QoL (EuroQoL 5 Dimensions 5 Levels, EQ-5D-5L) and social functioning (Social Functioning Questionnaires, SFQ). Results We enrolled 30 RA, 21 SLE, 14 pSS and 9 HV (Table 1). As expected SLE patients were younger and with a longer disease duration. A good construct validity was observed correlating fVAS scores with FACIT-Fatigue and m-MFS (rs:-0.81, p<0.001 and rs:0.42, p:0.002). Comparing the questionnaire scores RDs patients reported more fatigue, both physical and mental, and worst QoL and global health status (Table 2), however no differences between the different RDs subgroups regarding the questionnaires scores were observed except for m-MFS, showing a higher mental fatigue in patients with SLE+pSS than RA patients. The female patients reported higher fVAS scores (meaning greater fatigue) as compared to males (39.0 [20.0-60.0] vs 14.0 [0.0-35.0], p:0.0125), while no significant correlations were found between fVAS scores and age, disease duration and Charlson Comorbidity Index. In SLE and pSS subgroups no correlations with disease activity were found. Finally, fVAS correlated positively with sqVAS (rs:0.36, p:0.004), ESS (rs:0,28, p:0.022), MOS-SS (rs:0.38, p:0.050), GAD-2 (rs:0.45, p<0.001), PHQ-2 (rs:0,31, p:0.028), SFQ (rs:0.41, p:0.003) and negatively with EQ-5D-5L index value (rs:-0.61, p:0.003). This implies that as fatigue worsens, sleep quality, anxiety and depressive symptoms, social functioning, quality of life and global health status worsen. Table 1. Demographic and clinical characteristics Table 2. Questionnaire scores Conclusions patients affected by SLE and other RMDs reported worse fatigue and quality of life than HV. A greater fatigue appears associated with female sex as well as with sleep disturbances, anxiety symptoms, depression, poorer social functioning and lower QoL, without differences according to the RD diagnosis nor disease activity indices. Future perspectives include the implementation of the results with the questionnaire scores obtained during subsequent follow-up visits and the data derived from the digital devices used in the field of IDEA-FAST study to evaluate the data consistency. References: [1.] Huang CC. Annu Int Conf IEEE Eng Med Biol Soc 2022;2022:1823-6. [2.] Overman CL. Clin Rheumatol 2016;35:409-15. [3.] Pollard LC. Rheumatology 2006;45(6):885-9.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".