Risk factors for the development of autism spectrum disorder in children with tuberous sclerosis complex: protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: Tuberous sclerosis complex (TSC) is an autosomal dominant condition, caused by mutations in either the TSC1 or TSC2 gene. It has widespread systemic manifestations and is associated with significant neurological morbidity. In addition to seizures and cerebral pathology including cortical tubers, subependymal nodules, subependymal giant cell astrocytoma and abnormal white matter, there are recognised neuropsychiatric difficulties including intellectual disability, autism spectrum disorder (ASD) and a range of learning and behaviour problems, recently conceptualised as "tuberous sclerosis-associated neuropsychiatric disorders", or "TAND". ASD in TSC is of particular importance because (1) it affects up to 50% of people with TSC and is a source of considerable difficulty for them and their families and (2) it provides a model for considering neurobiological pathways involved in ASD. Multiple factors are implicated in the development of ASD in TSC, including (1) seizures and related electrophysiological factors, (2) cerebral pathology, (3) genotype and (4) child characteristics. However, the neurobiological pathway remains unclear. We will conduct a systematic review to investigate and synthesise existing evidence about the role of these risk factors, individually and in combination, in leading to the development of ASD. METHODS: Our review will report on all studies that include one or more of four predefined risk factors in the development of ASD in children with TSC. We will search five databases: MEDLINE, EMBASE, PubMed, The Cochrane Library and Web of Science (Conference Proceedings Citation Index). Studies will be selected for reporting after two authors independently (1) review all titles and abstracts, (2) read full text of all appropriate papers and (3) assess for bias using the Newcastle-Ottawa Scale recommended by the Guidelines for Meta-Analysis and Systematic Reviews of Observational Studies (MOOSE guidelines) and the ROBINS-I. DISCUSSION: To our knowledge, this is the first systematic review investigating multiple risk factors in the development of ASD in children with TSC. Clarifying the evidence in this area will be important to researchers in the field and to clinicians providing prognostic information to families. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016042841.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.049 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.018 | 0.017 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".