SERUM NEUROFILAMENT LIGHT TO DISTINGUISH AND MONITOR ACTIVITY IN A COHORT OF NEUROPSYCHIATRIC SYSTEMIC LUPUS ERYTHEMATOSUS
Notice bibliographique
Résumé
PV044 / #345 Poster Topic: AS05 - CNS Lupus Background/Purpose Neuropsychiatric systemic lupus erythematosus (NPSLE) is a poorly recognized entity leading to diagnostic and therapeutic delays. This is likely due to heterogeneity of manifestations complicating recognition, and the lack of markers that portend neuropsychiatric activity, with conventional serology, neuroimaging studies and CSF analysis often yielding unremarkable results. Serum levels of neurofilament light (NfL), a neuronal cytoskeletal protein, have been associated with other neurological conditions, eg, multiple sclerosis, suggesting utility as a noninvasive biomarker in neuroinflammatory pathologies. Studies to date assessing its utility in SLE have been limited by heterogeneously defined study populations of NPSLE.[1] We present serum NfL concentrations in an NPSLE cohort, highlighting the need for more novel modalities for assessment of neuropsychiatric involvement by SLE. Methods Subjects: 83 patients (70 female, 13 male) under the Department of Immunology at Blacktown and Westmead Hospitals, Sydney, Australia. All fulfilled the European League Against Rheumatism / American College of Rheumatology (ACR) 2019 Classification Criteria for SLE and were recruited at various treatment time points between 2014-2024 (disease duration 0-41 years). Seven were reassessed at a second timepoint (range: 0.2-3 years) due to a change in clinical activity or treatment. NPSLE: Classification based on 1999 ACR nomenclature and case definitions for NPSLE and Italian Society of Rheumatology 2015 attribution model for neuropsychiatric manifestations to SLE.[2] Classified at onset of neuropsychiatric manifestations, independent of activity during study recruitment. Serum NfL: Performed using Single Molecular Array technology, units expressed as pg/mL. Normal values increase with age,[3] therefore age-adjusted reference ranges were not utilized, rather comparing mean differences MRI: The following considered abnormal – atrophy, cerebrovascular disease or infarction, multiple high signal changes in white matter, demyelinating lesions, myelitis. Statistical analysis: Mann-Whitney U test. P values less than 0.05 considered significant. Results Sixty-five patients with non-NP SLE (ages 18-81 years [mean ± SD: 42 ± 14 years]) and 18 NPSLE (ages 21-60 years [37 ± 13 years]) were included. Six NPSLE patients had active whereas 12 had inactive neuropsychiatric manifestations. Serum NfL levels trended 2.5 times higher in NPSLE than non-NP SLE cohorts (mean ± standard error of mean: 64.28 ± 25.63 pg/mL vs 24.03 ± 4.543 pg/mL; p = 0.41) (Figure 1). NfL levels trended higher in those with active than inactive NPSLE (103.7 ± 55.18 pg/mL vs 44.58 ± 26.91 pg/mL; p = 0.7) (Figure 2). There was a trend toward a younger age in both NPSLE than non-NP SLE cohorts and active than inactive NPSLE cohorts, suggesting that patient age did not contribute to the measured difference between groups. Abnormal MRIs were seen in 45% of patients with NPSLE and 24% non-NP SLE (p = 0.4). There were no differences in seropositivity for anti-dsDNA nor antiphospholipid antibodies, nor in hypocomplementemia between the NPSLE and non-NP SLE groups. Six patients with NPSLE and 1 with non-NP SLE were followed up, 3 of whom improved with treatment with corresponding reductions in serum NfL concentrations, 2 of whom who had persistent active disease due to inadequate treatment with an increasing serial NfL concentrations, and 1 of who developed new neuropsychiatric involvement with a corresponding rise in serum NfL concentration. Figure 1. Serum NfL levels in NPSLE and non-NP SLE (mean & SEM pg/mL). Figure 2. Serum NfL levels in NPSLE patients with active neuropsychiatric manifestations and those with inactive neuropsychiatric manifestations (mean & SEM pg/mL). Conclusions Serum NfL levels may be a useful method for diagnosing, monitoring and prognosticating patients with NPSLE. References: [1.] Emerson J. Front Neurol 2023;14:1111769. [2.] Bortoluzzi A. Rheumatology (Oxford) 2015;54(5):891-8. [3.] Khalil M. Nat Rev Neurol 2018;14(10):577-89.
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 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».