Neurodevelopmental outcomes in children with cerebellar malformations: a systematic review
Bibliographic record
Abstract
Cerebellar malformations are increasingly diagnosed in the fetal period. Consequently, their consideration requires stressful and often critical decisions from both clinicians and families. This has resulted in an emergent need to understand better the impact of these early life lesions on child development. We performed a comprehensive literature search of studies describing neurodevelopmental outcomes of cerebellar malformations between January 1997 and December 2007. Overall, the data suggested that children with isolated inferior vermis hypoplasia (IVH) and mega cisterna magna (MCM) have a good developmental outcome, whereas children with molar tooth sign/Joubert syndrome, vermis hypoplasia, pontocerebellar hypoplasia (PCH) type II, and cerebellar agenesis experience moderate to severe global developmental delays. Reports for Dandy-Walker malformation (DWM) were conflicting; however, the presence of a normally lobulated vermis and the absence of associated brain anomalies were associated with a more favourable outcome. Finally, children with isolated cerebellar hypoplasia experienced fewer impairments. Important methodological limitations highlighted include a lack of standardized outcome measure use in 79% of studies and the predominant use of retrospective study designs (85%), with 40% limited to case reports or case-series. In summary, rigorous outcome studies describing the spectrum of disabilities in survivors are urgently needed to accurately delineate the long-term neurodevelopmental consequences of cerebellar malformations.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".