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Record W4400360844 · doi:10.1186/s11689-024-09552-x

An integrated clinical approach to children at genetic risk for neurodevelopmental and psychiatric conditions: interdisciplinary collaboration and research infrastructure

2024· article· en· W4400360844 on OpenAlexafffund
Jane Summers, Danielle Baribeau, Polina Perlman, Ny Hoang, Sunny Cui, Aneta Krakowski, Patricia Ambrozewicz, Ariel Ho, Thanuja Selvanayagam, Kinga A. Sándor-Bajusz, Katrina Palad, Nishi Patel, Sarah McGaughey, Louise Gallagher, Stephen W. Scherer, Péter Szatmári, Jacob Vorstman

Bibliographic record

VenueJournal of Neurodevelopmental Disorders · 2024
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsSickKids FoundationCentre for Addiction and Mental HealthHolland Bloorview Kids Rehabilitation HospitalHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsNeurologyPsychiatryNeuropsychologyPsychologyMedicineCognition

Abstract

fetched live from OpenAlex

BACKGROUND: A sizeable proportion of pathogenic genetic variants identified in young children tested for congenital differences are associated with neurodevelopmental psychiatric disorders (NPD). In this growing group, a genetic diagnosis often precedes the emergence of diagnosable developmental concerns. Here, we describe DAGSY (Developmental Assessment of Genetically Susceptible Youth), a novel interdisciplinary 'genetic-diagnosis-first' clinic integrating psychiatric, psychological and genetic expertise, and report our first observations and feedback from families and referring clinicians. METHODS: We retrieved data on referral sources and indications, genetic and NPD diagnoses and recommendations for children seen at DAGSY between 2018 and 2022. Through a survey, we obtained feedback from twenty families and eleven referring clinicians. RESULTS: 159 children (mean age 10.2 years, 57.2% males) completed an interdisciplinary (psychiatry, psychology, genetic counselling) DAGSY assessment during this period. Of these, 69.8% had a pathogenic microdeletion or microduplication, 21.5% a sequence-level variant, 4.4% a chromosomal disorder, and 4.4% a variant of unknown significance with emerging evidence of pathogenicity. One in four children did not have a prior NPD diagnosis, and referral to DAGSY was motivated by their genetic vulnerability alone. Following assessment, 76.7% received at least one new NPD diagnosis, most frequently intellectual disability (24.5%), anxiety (20.7%), autism spectrum (18.9%) and specific learning (16.4%) disorder. Both families and clinicians responding to our survey expressed satisfaction, but also highlighted some areas for potential improvement. CONCLUSIONS: DAGSY addresses an unmet clinical need for children identified with genetic variants that confer increased vulnerability for NPD and provides a crucial platform for research in this area. DAGSY can serve as a model for interdisciplinary clinics integrating child psychiatry, psychology and genetics, addressing both clinical and research needs for this emerging population.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.002
Science and technology studies0.0040.002
Scholarly communication0.0040.004
Open science0.0030.023
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.028
GPT teacher head0.387
Teacher spread0.359 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

Quick stats

Citations11
Published2024
Admission routes2
Has abstractyes

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