Medical Evaluation of Children with Intellectual Disability: Clinician Compliance with Published Guidelines
Bibliographic record
Abstract
Background: Children with intellectual disability (CWID) in the USA are typically referred to child neurologists (CN) and developmental-behavioral pediatricians (DBP) for medical evaluation. Although the American Academy of Neurology/Child Neurology Society (AAN/CNS) and the American Academy of Pediatrics (AAP) have published evaluation guidelines, experience suggests CN and DBP do not consistently follow them. Our goal was to assess CN’s and DBP’s approach to evaluating CWID and overall compliance with published guidelines. Methods: Questionnaires were mailed to CN and DBP in the U.S. (n=1897). Physicians were asked demographic information and which laboratory tests they would "routinely order" for the hypothetical case of a 3½ year old boy with Full Scale IQ=58 and unremarkable neurological history and exam. Chi-square tests were performed to compare sub-specialists’ ordering practices. Results: 127 CN and 140 DBP responded. 7.1% CN (n=9) and 11.4% DBP (n=16) complied with AAN/CNS and AAP guidelines, respectively. Although routinely indicated, 36.2% CN and 31.4% DBP would not routinely order chromosomal microarray (CMA), and 42.5% CN and 26.4% DBP would not routinely order DNA for Fragile X (χ2=7.67, p=0.006). 7.9% CN and 7.1% DBP would order a karyotype without CMA. Although not indicated, 7.1% CN and 0.7% DBP noted they would routinely order an EEG (χ2=7.50, p=0.006). A brain MRI is only recommended by AAN/CNS guidelines; 49.6% CN and 12.9% DBP reported they would routinely order it (χ2=42.55, p<.0001). Conclusion: Few CN and DBP follow published guidelines for laboratory evaluation of CWID. Relative to DBP, CN more frequently order EEGs and MRIs but less frequently order recommended genetic tests.
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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 | 0.013 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".