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Record W4403058980 · doi:10.58931/cait.2024.4267

Understanding and Managing Adenotonsillar Hypertrophy in Pediatric Otolaryngology

2024· article· en· W4403058980 on OpenAlexaff
Ivry Zagury‐Orly, Jonathan MacLean

Bibliographic record

VenueCanadian allergy & immunology today. · 2024
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOtorhinolaryngologyMuscle hypertrophyMedicineInternal medicineSurgery

Abstract

fetched live from OpenAlex

Adenotonsillar hypertrophy (ATH) is a common pediatric condition marked by the growth of lymphoid tissues within the Waldeyer’s ring, which includes adenoids, palatine tonsils, and lingual tonsils. These tissues surround the upper airway and food passage, and play an immunological role, enlarging until about age 12, before gradually reducing during adolescence and adulthood. Untreated or poorly managed ATH can severely impact multiple health aspects of children. It is the primary cause of upper airway obstruction and obstructive sleep apnea (OSA) syndrome in children, which disrupts sleep and can severely impair cognitive development, school performance and behaviour. Chronic mouth breathing from ATH can alter dental arches and facial growth, known as adenoid facies. More severe outcomes include increased pulmonary pressures and the potential development of pulmonary hypertension and cor pulmonale due to chronic hypoxia and CO2 retention. As a result, tonsillectomy, with or without adenoidectomy (T&A), has become one of the most frequently performed surgeries in North America, with over 530,000 operations performed annually on children under age 15. This paper discusses the significant impact of ATH on pediatric health and the frequent need for surgical intervention. It covers the immunophysiology, influence of atopy, community-based assessments prior to specialist referrals, and an overview of available medical and surgical treatment options. Additionally, it outlines general indications for referring patients to otolaryngology.

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 score0.452
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.256
Teacher spread0.224 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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