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Social impairments in Rett syndrome: characteristics and relationship with clinical severity

2011· article· en· W2159950131 on OpenAlexaff
Walter E. Kaufmann, Elaine Tierney, Charles A. Rohde, M. C. Suarez‐Pedraza, Megan A. Clarke, Cynthia F. Salorio, Genila Bibat, Irena Bukelis, D. Naram, Diane C. Lanham, S. Naidu

Bibliographic record

VenueJournal of Intellectual Disability Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsEmergent BioSolutions (Canada)
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Research Resources
KeywordsRett syndromeMECP2PsychologyVineland Adaptive Behavior ScaleAutismDevelopmental psychologyClinical psychologyNeurodevelopmental disorderRating scaleIntellectual disabilityChildhood Autism Rating ScaleAdaptive behaviourPsychiatryAudiologyAutism spectrum disorderMedicinePhenotype

Abstract

fetched live from OpenAlex

BACKGROUND: While behavioural abnormalities are fundamental features of Rett syndrome (RTT), few studies have examined the RTT behavioural phenotype. Most of these reports have focused on autistic features, linked to the early regressive phase of the disorder, and few studies have applied standardised behavioural measures. We used a battery of standardised measures of behaviour and functioning to test the following hypotheses: (1) autistic behaviour is prominent throughout childhood in RTT; (2) autistic features are more salient in individuals with milder presentation; (3) severity of autistic behaviour is associated with a wider range of behavioural problems; and (4) specific MECP2 mutations are linked to more severe autistic behaviour. METHODS: Eighty MECP2 mutation-positive girls with RTT (aged 1.6-14.9 years) were administered: (1) the Screen for Social Interaction (SSI), a measure of autistic behaviour suited for individuals with severe communication and motor impairment; (2) the Rett Syndrome Behaviour Questionnaire (RSBQ), covering a wide range of abnormal behaviours in RTT; (3) the Vineland Adaptive Behavior Scales (VABS); and (4) a modified version of the Rett Syndrome Severity Scale (RSSS). Regression analyses examined the predictive value of age and RSSS on autistic behaviour and other behavioural abnormalities. T-tests further characterised the behavioural phenotype of individual MECP2 mutations. RESULTS: While age had no significant effect on SSI or RSBQ total scores in RTT, VABS Socialization and Composite scores decreased over time. Clinical severity (i.e. RSSS) also increased with age. Surprisingly, SSI performance was not related to either RSSS or VABS Composite scores. Autistic behaviour was weakly linked with the RSBQ Hand behaviour factor scores, but not with the RSBQ Fear/Anxiety factor. Clinical (neurological) severity did not predict RSBQ scores, as evidenced by the analysis of individual MECP2 mutations (e.g. p.R106W, p.R270X and p.R294X). CONCLUSIONS: Our data suggest that in RTT, autistic behaviour persists after the period of regression. It also demonstrated that neurological and behavioural impairments, including autistic features, are relatively independent of one another. Consistent with previous reports of the RTT phenotype, individual MECP2 mutations demonstrate complex associations with autistic features. Evidence of persistent autistic behaviour throughout childhood, and of a link between hand function and social skills, has important implications not only for research on the RTT behavioural phenotype, but also for the clinical management of the disorder.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.148
GPT teacher head0.396
Teacher spread0.247 · 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 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".

Quick stats

Citations136
Published2011
Admission routes1
Has abstractyes

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