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Enregistrement W7117479418 · doi:10.1002/mdc3.70487

Reply to: Severity‐Based and Family‐Centered Approaches to Deep Brain Stimulation in <scp>GNAO1</scp> ‐Related Disorders

2025· article· en· W7117479418 sur OpenAlexaffabout
Marcela Montiel, Carolina Gorodetsky, Nardo Nardocci, Alfonso Fasano

Notice bibliographique

RevueMovement Disorders Clinical Practice · 2025
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGenomics and Rare Diseases
Établissements canadiensOntario Brain InstituteHospital for Sick ChildrenToronto Western HospitalUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésDeep brain stimulationDystoniaComparabilityPerspective (graphical)Movement disordersNeuroimagingScale (ratio)

Résumé

récupéré en direct d'OpenAlex

We greatly appreciate Dominguez-Carral and Ortigoza-Escobar's thoughtful comments on our recent publication.1, 2 Their experience with GNAO1-related disorders highlights the value of phenotype-based severity frameworks and caregiver-centered assessments, particularly in conditions with highly variable trajectories and crisis-prone phenotypes. As we emphasized in our article, our primary aim was to review the landscape of rating scales used internationally in pediatric dystonia and to underline the current absence of a universally accepted, developmentally appropriate tool for evaluating pediatric patients with dystonia who are candidates for deep brain stimulation (DBS). While disease-specific severity scores offer an important level of detail within defined genetic subgroups, we believe it remains impractical to develop or implement unique scales for every etiological category of dystonia. From a methodological standpoint, relying solely on disease-specific instruments would limit multicenter data aggregation, reduce comparability across heterogeneous cohorts, and hinder the development of broadly applicable evidence-based algorithms. For this reason, we advocate for an approach that combines both perspectives: (1) a robust, generic, pediatric-adapted dystonia scale capable of capturing motor and non-motor symptoms, the impact of dystonia on both patient and caregiver's quality of life, and the caregiver's perspective on the child's day-to-day functioning, and (2) optional disease-specific modules when additional precision is required. This conceptual model mirrors the dual-framework used in other neurological fields such as, for example, generic versus disease-specific quality-of-life measures.3, 4 Finally, we fully agree that integrating caregiver-reported experience and burden is essential, especially in urgent and emotionally complex decision-making contexts such as pediatric DBS. In line with the points raised by the authors, we also underscore that caregiver-reported severity and quality of life assessments are not only valuable for monitoring dystonia and its evolution, but are equally crucial in determining when DBS should be considered or deferred in specific conditions, such as GNAO1-related disorders.5 In conclusion, we are grateful for the authors’ contribution to this dialogue and for their commitment to improving the assessment and care of children undergoing DBS for severe dystonia. We hope that future collaborative efforts, aligned with ongoing international harmonization initiatives, will support the development and validation of assessment tools that can be applied consistently while still accommodating disease-specific nuances when appropriate. (1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript Preparation: A. Writing of the first draft, B. Review and Critique. M.A.M.: 1A, 1B, 1C, 3A. C.G.: 3B. N.N.: 3B. A.F.: 1A, 1B, 1C, 3B. Ethical Compliance Statement: The authors confirm that the approval of an institutional review board was not required for this work. Informed patient consent was not necessary for this work. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines. Funding Sources and Conflict of Interest: This study was partly funded by the University Health Network and University of Toronto Chair in Neuromodulation to AF. The authors declare that there are no conflicts of interest relevant to this work. Financial Disclosures for the previous 12 months: MM has no financial disclosures. CG has received payments as consultant and Advisory board from Medtronic and consulting fees from Ipsen. NN has no financial disclosures. AF has stock ownership in Inbrain Pharma and has received payments as consultant and/or speaker from Abbvie, Abbott, Boston Scientific, Ceregate, Dompé Farmaceutici, Inbrain Neuroelectronics, Ipsen, Medtronic, Iota, Syneos Health, Merz, Sunovion, Paladin Labs, UCB, Sunovion. He has received research support from Abbvie, Boston Scientific, Medtronic, Praxis, ES and receives royalties from Springer. Data sharing not applicable to this article as no datasets were generated or analyzed during the current 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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,428
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,034
Tête enseignante GPT0,321
Écart entre enseignants0,287 · 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 tête enseignante, pas un consensus.

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
Publié2025
Routes d'admission2
Résumé présentoui

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