Classification of Children and Adolescents With Avoidant/Restrictive Food Intake Disorder
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Evidence suggests that children and adolescents with avoidant/restrictive food intake disorder (ARFID) have heterogeneous clinical presentations. To use latent class analysis (LCA) and determine the frequency of various classes in pediatric patients with ARFID drawn from a 2-year surveillance study. METHODS: Cases were ascertained using the Canadian Pediatric Surveillance Program methodology from January 1, 2016, to December 31, 2017. An exploratory LCA was undertaken with latent class models ranging from 1 to 5 classes. RESULTS: Based on fit statistics and class interpretability, a 3-class model had the best fit: Acute Medical (AM), Lack of Appetite (LOA), and Sensory (S). The probability of being classified as AM, LOA, and S was 52%, 40.7%, and 6.9%, respectively. The AM class was distinct for increased likelihood of weight loss (92%), a shorter length of illness (<12 months) (66%), medical hospitalization (56%), and heart rate <60 beats per minute (31%). The LOA class was distinct for failure to gain weight (97%) and faltering growth (68%). The S class was distinct for avoiding certain foods (100%) and refusing to eat because of sensory characteristics of the food (100%). Using posterior probability assignments, a mixed group AM/LOA (n = 30; 14.5%) had characteristics of both AM and LOA classes. CONCLUSIONS: This LCA suggests that ARFID is a heterogeneous diagnosis with 3 distinct classes corresponding to the 3 subtypes described in the literature: AM, LOA, and S. The AM/LOA group had a mixed clinical presentation. Clinicians need to be aware of these different ARFID presentations because clinical and treatment needs will vary.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it