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Enregistrement W2900395622 · doi:10.1212/wnl.90.15_supplement.s51.002

Oligoclonal Bands in Spinal Fluid Improve the Specificity of Different MRI Criteria for Dissemination in Space to Predict a First Clinical Event in Children with the Radiologically Isolated Syndrome (S51.002)

2018· article· en· W2900395622 sur OpenAlexaff
Naila Makhani, Chrisitne Lebrun, Aksel Sıva, Sona Narula, Evangeline Wassmer, J. Nicholas Brenton, David Brassat, Clarisse Carra‐Dallière, de Sèze, Françoise Durand Dubief, Megan Langille, Rinze F. Neuteboom, Jean Pelletier, Daniela Pohl, Daniel S. Reich, Juan Ignacio Rojas, Veronika Shabanova, Eugene D. Shapiro, Robert Thompson Stone, Sílvia Tenembaum, Mar Tintoré, Uğur Uygunoğlu, Wendy Vargas, Sunita Venkateswaran, Orhun H. Kantarci, Darin T. Okuda, Daniel Pelletier

Notice bibliographique

RevueNeurology · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueSpinal Fractures and Fixation Techniques
Établissements canadiensChildren's Hospital of Eastern Ontario
Organismes subventionnairesnon disponible
Mots-clésFrenchEvent (particle physics)MedicinePathologyHumanitiesArtPhysics

Résumé

récupéré en direct d'OpenAlex

Objective: To determine whether the addition of oligoclonal band (OCB) status (present/absent in cerebrospinal fluid [CSF]) improved the performance of 2005 and proposed MAGNIMS 2016 MRI criteria for dissemination in space (DIS) to predict a first clinical event consistent with central nervous system demyelination in children with the radiologically isolated syndrome (RIS), defined using 2010 MRI criteria for DIS (RIS-2010). Background: Improved diagnostic criteria for RIS are needed to predict which children will develop a first clinical event. We reported that neither the 2005 nor the 2016 MAGNIMS MRI criteria for DIS had both high sensitivity and specificity to predict a first clinical event in children with RIS-2010. Design/Methods: We analyzed a historical cohort of children (<18 years) with RIS-2010 in an international longitudinal study. We determined whether children also met 2005 and 2016 MAGNIMS MRI criteria for DIS at baseline and whether ≥2 unique OCBs were present in CSF. We calculated sensitivity and specificity for different MRI criteria for DIS with and without the addition of OCB status. Results: Of 55 children with RIS-2010, 33 (60%) had OCB status determined and were included (6M/27F, mean follow-up=5.3 ± 5.2 years). 19/33 children tested OCB+ (58%) and 15/33 children (45%) developed a first clinical event. Diagnostic indices and 95% C.I.s for the 2005 DIS criteria with and without OCBs status were: sensitivity 67% (38%–88%) vs. 67% (41%–87%); specificity 83% (59%–96%) vs. 53% (35%–70%). For the 2016 MAGNIMS DIS criteria diagnostic indices were: sensitivity 87% (60%–98%) vs. 100% (82%–100%) and specificity 72% (46%–90%) vs. 25% (11%–41%). Conclusions: The addition of OCB status improved the specificity of both the 2005 and the 2016 MAGNIMS MRI criteria for DIS to predict a first clinical event in children with RIS-2010. The 2016 MAGNIMS DIS criteria plus OCB status had the best combination of sensitivity and specificity. Study Supported by: This study was funded, in part, by Grant Number K23NS101099 from the National Institute of Neurological Diseases and Stroke (NINDS) and CTSA Grant Number UL1 TR000142 from the National Center for Advancing Translational Science (NCATS) at the National Institutes of Health and NIH roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NIH. Disclosure: Dr. Makhani has nothing to disclose. Dr. Lebrun-Freney has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Consulting fees, honoraria or scientific committee support: Bayer Schering, Biogen, Genzyme, Merck Serono, Novartis, Teva. Dr. Siva has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Merck, Novartis, Teva, Genzyme, Bayer, Roche. Dr. Narula has nothing to disclose. Dr. Wassmer has nothing to disclose. Dr Brenton has nothing to disclose. Dr. Brassat has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Bayer, Biogen, MedDay, Merck Serono, Novartis, Sanofi-Genzyme, Roche, Teva. Dr. Carra-Dalliere has nothing to disclose. Dr. De Seze has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Sanofi. Dr. De Seze has received research support from Sanofi. Dr. Durand Dubief has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Sanofi-Genzyme, Novartis, Teva, Merck, Roche. Dr. Langille has nothing to disclose. Dr. Neuteboom has nothing to disclose. Dr. Pelletier has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Sanofi-Genzyme, Novartis, Teva, Merck-Serono, Roche, MedDay. Dr. Pelletier has received research support from Biogen, Novartis, Roche, Merck-Serono. Dr. Pohl has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Novartis, Forward. Dr. Reich has nothing to disclose. Dr. Rojas has nothing to disclose. Dr. Shabanova has nothing to disclose. Dr. Shapiro has nothing to disclose. Dr. Thompson-Stone has nothing to disclose. Dr. Tenembaum has nothing to disclose. Dr. Tintoré has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Bayer Schering Pharma, Merck-Serono, Biogen-Idec, Teva Pharmaceuticals, Sanofi-Aventis, Novartis, Almirall, Genzyme, and Roche. Dr. Uygunoglu has nothing to disclose. Dr. Vargas has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Alexion Pharmaceuticals. Dr. Vargas has received research support from Teva Pharmaceuticals. Dr. Venkateswaran has nothing to disclose. Dr. Kantarci has nothing to disclose. Dr. Okuda has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Acorda, EMD Serono, Genentech, Genzyme, Novartis, and Teva. Dr. Pelletier has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen, Merck Serono, Novartis, Roche, and Sanofi. Dr. Pelletier has received research support from Biogen, Merck Serono, Novartis, Roche, and Sanofi. Dr. (OFSEP) has nothing to disclose. Dr. (SFSEP) has nothing to disclose. Dr. (RISC) has nothing to disclose. Dr. Consortium (PARIS) has nothing to disclose.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,030

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0090,002

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.

Tête enseignante Opus0,014
Tête enseignante GPT0,329
Écart entre enseignants0,315 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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