Symptoms Prior to Diagnosis of Multiple Sclerosis in Individuals Younger Than 18 Years
Notice bibliographique
Résumé
Importance: A growing body of literature suggests the presence of a prodromal period with nonspecific signs and symptoms before onset of multiple sclerosis (MS). Objective: To systematically assess diseases and symptoms diagnosed in the 5 years before a first MS- or central nervous system (CNS) demyelinating disease-related diagnostic code in pediatric patients compared with controls without MS and controls with another immune-mediated disorder, juvenile idiopathic arthritis (JIA). Design, Setting, and Participants: This population-based, matched case-control study included children and adolescents (aged <18 years) in Germany with statutory health insurance from January 2010 to December 2020. The study population consisted of 3 groups: case individuals with MS, control individuals without MS, and control individuals with JIA. Data were analyzed from November 2023 to April 2024. Exposures: Diagnoses coded according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, German Modification (ICD-10-GM). Main Outcome and Measures: The main outcome was incident cases of MS, defined as the first confirmed diagnosis of MS (ICD-10-GM code G35) in 1 quarter between 2013 and 2020 and at least 1 additional diagnosis in the following quarters. In total, 163 ICD-10-GM codes before a first MS diagnosis were assessed using univariable and multivariable logistic regression analyses. Results: The study population consisted of 1091 children and adolescents with MS, 10 910 without MS, and 1068 with JIA. Of the children and adolescents with MS, 788 (72.2%) were female. Mean (SD) age at disease diagnosis was 15.7 (1.7) years. Nine ICD-10-GM codes were present more frequently among children and adolescents with MS in the 5 years before their first MS diagnosis than among controls without MS: obesity (adjusted odds ratio [AOR], 1.70; 95% CI, 1.42-2.02), disorders of eye refraction and accommodation (AOR, 1.26; 95% CI, 1.09-1.47), visual disturbances (AOR, 1.31; 95% CI, 1.10-1.55), gastritis and duodenitis (AOR, 1.35; 95% CI, 1.08-1.70), patella disorders (AOR, 1.47; 95% CI, 1.13-1.90), heartbeat abnormalities (AOR, 1.94; 95% CI, 1.27-2.96), flatulence (AOR, 1.43; 95% CI, 1.01-2.01), skin sensation disturbances (AOR, 12.93; 95% CI, 8.98-18.62), as well as dizziness and giddiness (AOR, 1.52; 95% CI, 1.22-1.89). Four of these ICD-10-GM codes were significantly more prevalent in children and adolescents with MS than in controls with JIA: obesity (AOR, 3.19; 95% CI, 2.03-5.02), refraction and accommodation disorders (AOR, 3.08; 95% CI, 2.33-4.08), visual disturbances (AOR, 1.62; 95% CI, 1.13-2.33), and skin sensation disturbances (AOR, 27.70; 95% CI, 6.52-117.64). Conclusions and Relevance: In this population-based, matched case-control study, children and adolescents with MS had diverse metabolic, ocular, musculoskeletal, gastrointestinal, and cardiovascular symptoms, signs, or diagnoses within 5 years before their first MS diagnosis. Better characterization of early symptoms and/or risk factors, comorbid disorders, and possible prodromal features of MS may have considerable implications for early recognition and subsequent progression of the disease.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,002 | 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 ».