Paediatricians underuse recommended genetic tests in children with global developmental delay
Bibliographic record
Abstract
OBJECTIVES: To assess paediatricians' use of genetic testing for children with global developmental delay (GDD). STUDY DESIGN: We developed and piloted a questionnaire assessing the use of genetic tests in children with GDD and awareness of relevant guidelines. All practicing Quebec paediatricians were contacted. Paediatricians who did not evaluate children with GDD in their practice were excluded. Descriptive and statistical analyses were performed with SPSS. RESULTS: Of the 651 paediatricians, 225 answered (34.5%) and 141 were eligible. Only 31.9% were familiar with at least one guideline about genetic tests for the investigation of children with GDD, but 93.6% had ordered genetic testing for children with GDD (Fragile X testing [92.9%], karyotype [87.2%] and chromosomal microarray [63.8%]). Based on vignettes, 20.6% of participants would order genetic tests for isolated GDD and 95.0% for GDD with dysmorphic features and microcephaly. Only 56.7% ordered Fragile X testing for a girl with GDD and a known family history of Fragile X syndrome. Use of tests for isolated GDD was increased in presence of maternal pregnancy, compared with absence of pregnancy (44.7% and 27.7%, respectively). More participants would order genetic tests for a child with GDD and fetal exposure to alcohol (69.5%) than isolated GDD (20.6%). CONCLUSIONS: Even though paediatricians often order genetic testing for children with GDD, practices and knowledge regarding testing are not optimal. As new and more complex genetic tests are developed, up-to-date training about the use of genetic tests for children with GDD needs to be integrated into paediatrics residency programs and continuous medical education.
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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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".