A PROSPECTIVE ANALYSIS OF THE RATES AND PATTERNS OF AUTISM SPECTRUM DISORDER DIAGNOSIS IN AN ATLANTIC CANADIAN CITY
Bibliographic record
Abstract
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and interaction, with repetitive patterns of behaviors, interests or activities. As prevalence rates of ASD in Canada continue to rise, general pediatricians care for many children with ASD and serve as consultants for diagnosis. The importance of early detection and diagnosis of ASD has been well established in the literature, with early intervention and support leading to improved outcomes for children. Thereby, it is important that consultants are confident in their ability to screen and diagnose ASD. However, little is known about the clinical comfort level and frequency with which consultant pediatricians diagnose ASD. OBJECTIVES: The primary objectives of this study are to determine the frequencies with which consultant pediatricians, pediatric subspecialists and developmental teams are diagnosing ASD and the associated wait times. Potential barriers to diagnosis and clinical comfort with diagnosis will be explored. DESIGN/METHODS: All referrals received by consultant pediatricians in an Atlantic Canadian city, for children less than five years of age with a reason for referral meeting the study inclusion criteria were prospectively tracked recording: patient demographic information, reason for consultation, referral, consult and diagnosis dates, and diagnosing specialty. Consultants were also asked their interest in receiving more training on ASD and diagnosis. At the end of the one-year study period forms were collected for children diagnosed with ASD and children waiting for further consultation. RESULTS: Data was obtained for 90 children during the study period, with 52 children receiving a diagnosis of ASD and 38 waiting for further consultation. Preliminary data suggests that of the children diagnosed greater than 50% were diagnosed at initial pediatric consult, followed by developmental team and consulted pediatric neurologist diagnoses, with additional consults being associated with longer wait times to diagnosis. Further statistical analyses to comment on statistically significant differences between groups is pending. CONCLUSION: The results of this study will provide insight into the various pediatric subspecialties diagnosing ASD, the frequencies of these diagnoses and the wait times associated. It will also provide the opportunity to evaluate clinical comfort of initial consultant pediatricians and potential gaps in knowledge to improve outcomes and access to care for children receiving this diagnosis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".