Profile of Referrals for Early Childhood Developmental Delay to Ambulatory Subspecialty Clinics
Bibliographic record
Abstract
The objective of this study was to determine the profile and pattern of referral to subspecialty clinics of young children with suspected developmental delay together with the factors prompting their referral. All children under 5 years of age referred to either developmental pediatrics or pediatric neurology clinics at a single tertiary hospital over an 18-month period were prospectively identified. Standardized demographic and referral information were collected at intake, final developmental delay subtype diagnosed was identified, and referring physicians were surveyed regarding factors prompting referral. A total of 224 children met study criteria. There was a marked male preponderance (166/224), especially among those with either cognitive or language delay. Two delay subtypes, global developmental delay and developmental language disorder, accounted for two thirds of the diagnoses made. For slightly more than one third of the children (75/224), the delay subtype diagnosed following specialty evaluation was different from that initially suspected by the referring physician. A mean delay of 15.5 months was observed for the cohort as a whole between initial parental concern and specialty assessment. For referring physicians, the major factor prompting referral was the severity of the observed delay. The most important aspects of the specialty evaluation according to referral sources were the identification of a possible etiology and confirmation of delay. A profile of referrals and the rationale thereof for a cohort of children with suspected developmental delay is presented that, although locale specific, has implications for service provision and training.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".