Practice parameter: Evaluation of the child with global developmental delay [RETIRED]
Bibliographic record
Abstract
OBJECTIVE: To make evidence-based recommendations concerning the evaluation of the child with a nonprogressive global developmental delay. METHODS: Relevant literature was reviewed, abstracted, and classified. Recommendations were based on a four-tiered scheme of evidence classification. RESULTS: Global developmental delay is common and affects 1% to 3% of children. Given yields of about 1%, routine metabolic screening is not indicated in the initial evaluation of a child with global developmental delay. Because of the higher yield (3.5% to 10%), even in the absence of dysmorphic features or features suggestive of a specific syndrome, routine cytogenetic studies and molecular testing for the fragile X mutation are recommended. The diagnosis of Rett syndrome should be considered in girls with unexplained moderate to severe developmental delay. Additional genetic studies (e.g., subtelomeric chromosomal rearrangements) may also be considered in selected children. Evaluation of serum lead levels should be restricted to those children with identifiable risk factors for excessive lead exposure. Thyroid studies need not be undertaken (unless clinically indicated) if the child underwent newborn screening. An EEG is not recommended as part of the initial evaluation unless there are historical features suggestive of epilepsy or a specific epileptic syndrome. Routine neuroimaging, with MRI preferred to CT, is recommended particularly if abnormalities are found on physical examination. Because of the increased incidence of visual and auditory impairments, children with global developmental delay may undergo appropriate visual and audiometric assessment at the time of diagnosis. CONCLUSIONS: A specific etiology can be determined in the majority of children with global developmental delay. Certain routine screening tests are indicated and depending on history and examination findings, additional specific testing may be performed.
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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".