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Record 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 on OpenAlexaffabout
Marcela Montiel, Carolina Gorodetsky, Nardo Nardocci, Alfonso Fasano

Bibliographic record

VenueMovement Disorders Clinical Practice · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsOntario Brain InstituteHospital for Sick ChildrenToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsDeep brain stimulationDystoniaComparabilityPerspective (graphical)Movement disordersNeuroimagingScale (ratio)

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.321
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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