Male and Female Healthcare Trajectories in Autism: Are There Any Differences Considering Age at Diagnosis and Intellectual or Developmental Disabilities Status?
Bibliographic record
Abstract
The aim of this study was to compare the healthcare trajectories (HCTs) 2 years after a first diagnosis of autism according to sex, age at diagnosis, and intellectual or developmental disabilities (IDD) status. This is a retrospective cohort study using health administrative data from Québec, Canada. The cohort included all individuals with a first diagnosis of autism registered by a physician between April 2012 and March 2015. HCTs were stratified by sex, presence of IDD, and age at diagnosis (youth, adult), and analyzed using state sequence analysis across healthcare settings, providers, and reasons for use. Our cohort included 5289 individuals, 76.6% were male, and 26.3% were adults at the time of diagnosis. The healthcare use decreased slightly over time, though intensity was higher in females. Sex differences in HCTs were strongly influenced by IDD status and age at diagnosis. While no significant sex differences were observed in HCTs for individuals with IDD diagnosed with autism in adulthood, the psychiatric condition profiles showed notable differences between males and females. Hospital days nearly doubled for females diagnosed in childhood compared to males, while males with IDD diagnosed with autism in childhood and males without IDD diagnosed in adulthood had fewer physical illness visits. Although physical and mental health challenges appear largely managed in ambulatory care during youth, high hospitalization rates in those diagnosed in adulthood, particularly females and those with IDD, highlight concerns about continuity of care and avoidable hospitalizations for these subgroups of patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".