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Incidence and Age-Specific Presentation of Restrictive Eating Disorders in Children

2011· article· en· W2153726347 on OpenAlexaffabout
Leora Pinhas

Bibliographic record

VenueArchives of Pediatrics and Adolescent Medicine · 2011
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsAnorexia nervosaEating disordersIncidence (geometry)PediatricsMedicineBody mass indexPopulationPercentilePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To document and describe the incidence and age-specific presentation of early-onset restrictive eating disorders in children across Canada. DESIGN: Surveillance study. Cases were ascertained through the Canadian Paediatric Surveillance Program by surveying approximately 2453 Canadian pediatricians (a 95% participation rate) monthly during a 2-year period. SETTING: Canadian pediatric practices. PARTICIPANTS: Pediatricians and pediatric subspecialists. MAIN OUTCOME MEASURES: A description of clinical presentations and characteristics of eating disorders in this population and the incidence of restrictive eating disorders in children. RESULTS: The incidence of early-onset restrictive eating disorders in children aged 5 to 12 years seen by pediatricians was 2.6 cases per 100 000 person-years. The ratio of girls to boys was 6:1, and 47.1% of girls and 54.5% of boys showed signs of growth delay. Forty-six percent of children were below the 10th percentile for body mass index, 34.2% were initially seen with unstable vital signs, and 47.2% required hospital admission. Only 62.1% of children met criteria for anorexia nervosa. Although children with anorexia nervosa were more likely to be medically compromised, some children who did not meet criteria for anorexia nervosa were equally medically unstable. CONCLUSIONS: Young children are seen with clinically significant restrictive eating disorders, with the incidence exceeding that of type 2 diabetes mellitus. These eating disturbances can result in serious medical consequences, ranging from growth delay to unstable vital signs, which can occur in the absence of weight loss or other restrictive eating disorder symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.287
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations151
Published2011
Admission routes2
Has abstractyes

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