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Record W4392239502 · doi:10.3390/life14030319

Optimizing Childhood Obesity Management: The Role of Edmonton Obesity Staging System in Personalized Care Pathways

2024· article· en· W4392239502 on OpenAlexaboutno aff
Astrid De Wolf, Elise Nauwynck, Jesse Vanbesien, Willem Staels, Jean De Schepper, Inge Gies

Bibliographic record

VenueLife · 2024
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersFonds Wetenschappelijk Onderzoek
KeywordsPsychological interventionMultidisciplinary approachChildhood obesityObesityMedicineManagement of obesityHealth careWeight managementPromotion (chess)Health promotionPublic healthFamily medicineGerontologyNursingOverweightWeight lossPathology

Abstract

fetched live from OpenAlex

Childhood obesity, affecting 29% of 7-9-year-olds across 33 European countries, is a significant public health challenge. Its persistence into adulthood poses grave health risks influenced by genetic, environmental, and socio-economic factors. Belgium introduced a new care pathway in December 2023, based on the Edmonton Obesity Staging System for Pediatrics (EOSS-P), addressing four health domains and staging obesity severity. This pathway operates across three levels: primary care physicians, Paediatric Multidisciplinary Obesity Management Centres (PMOCs), and Centers of Expertise for Paediatric Obesity Management (CEPOs). Each stage of EOSS-P demands tailored interventions. Early stages involve dietary interventions, physical activity promotion, and behavior modifications. As obesity severity progresses, treatments intensify, encompassing psychological support, anti-obesity medications, and, in some cases, bariatric surgery. Throughout these stages, the involvement of multidisciplinary teams is crucial, emphasizing family-based approaches and continuous monitoring. This article provides detailed guidelines for healthcare professionals, delineating interventions and recommendations tailored to each EOSS-P stage. It emphasizes a holistic approach that extends beyond BMI-based diagnosis, promoting personalized care and prompt escalations between care levels, thereby ensuring optimal management of childhood obesity. This comprehensive framework aims to address the complexities of childhood obesity, emphasizing the importance of timely and targeted interventions for better health outcomes.

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 score0.254
Threshold uncertainty score0.650

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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