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Record W1949318789

Effets indésirables métaboliques en pédopsychiatrie

2009· article· fr· W1949318789 on OpenAlexaff
Ursula Winterfeld, Jean‐François Bussières, Johanne Boivin, Patricia Garel

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineGynecology
DOInot available

Abstract

fetched live from OpenAlex

Resume Objectif : Presenter un cas en pedopsychiatrie d’une prise de poids avec evolution vers un syndrome metabolique observe lors d’un traitement par olanzapine chez un adolescent. Resume du cas : Il s’agit d’un adolescent, age de 17 ans, traite pour schizophrenie paranoide avec un antipsychotique atypique, ayant presente des effets indesirables metaboliques. Le patient a presente une prise de poids importante (27 kg) passant d’un poids normal (30e percentile) a un surpoids (95e percentile). De plus, le patient a developpe une dyslipidemie avec hypertriglyceridemie, hypercholesterolemie et un taux abaisse de lipoproteines de haute densite. Discussion : On observe chez les enfants et les adolescents une prise de poids lors d’un traitement antipsychotique. La prise de poids augmente les risques de complications, en particulier metaboliques (intolerance au glucose, diabete non insulinodependant, dyslipidemie, syndrome metabolique), respiratoires et osteoarticulaires. De plus, elle augmente le risque d’arret du medicament en cause et de rechute. La prise en charge comporte des mesures associant la surveillance reguliere et precoce du poids, un bilan biologique a intervalles reguliers, des conseils hygieno-dietetiques, mais aussi une prise en charge dans le cadre d’un programme d’education nutritionnelle. Conclusion : L’utilisation d’antipsychotiques pour traiter les adolescents est associee a une prise de poids et a un syndrome metabolique. La surveillance clinique et biologique reguliere des enfants et adolescents sous antipsychotiques permet non seulement de depister ces effets indesirables mais aussi de les prendre en charge de facon adequate. Abstract Objective : To present a child psychiatry case of weight gain leading to metabolic syndrome observed in an adolescent treated with olanzapine. Case summary : A 17-year-old adolescent treated with an atypical antipsychotic for paranoid schizophrenia presented with metabolic adverse effects. The patient presented significant weight gain (27 kg), going from a normal weight (30th percentile) to being overweight (95th percentile). In addition, the patient developed dyslipidemia with hypertriglyceridemia and low high-density lipoprotein. Discussion : Weight gain in children and adolescents taking an antipsychotic has been observed. Such weight gain increases the risk of complications, especially metabolic (glucose intolerance, noninsulin-dependent diabetes, dyslipidemia, metabolic syndrome), and respiratory and osteoarticular complications. In addition, weight gain increases the risk of discontinuing the causative medication as well as the risk of relapse. Management involves early and regular monitoring of weight, routine bloodwork, consultation with a dietician, and participation in a nutritional education program. Conclusion : The use of antipsychotics to treat adolescents is associated with weight gain and with metabolic syndrome. Routine clinical and biological monitoring of children and adolescents treated with antipsychotics ensures the detection and appropriate management of adverse effects. Key words : Antipsychotics; child psychiatry; metabolic adverse effects.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.297
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2009
Admission routes1
Has abstractyes

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