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Record W2768587107 · doi:10.29333/ejgm/81895

A Common Health Problem in Children: Tracheobronchial Foreign Body Aspirations

2016· article· en· W2768587107 on OpenAlexaboutno aff
Bayram Altuntaş, Yener Aydın, İlker İnce, Atilla Eroğlu

Bibliographic record

VenueElectronic Journal of General Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicForeign Body Medical Cases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineForeign bodyThoracotomyForeign body aspirationBronchoscopySurgeryForeign BodiesComplication

Abstract

fetched live from OpenAlex

Introduction:Tracheobronchial foreign body aspiration is serious health problem in children. In this paper, we aimed to present our experience in tracheobronchial foreign body aspirations and rigid bronchoscopy in children.Material and Methods:Between January 1990 and May 2015, 693 patients less than 17 years of age with presumptive diagnosis of tracheobronchial aspiration of foreign bodies were included this study. Patients records were retrospectively analysed according to age, gender, symptoms and physical fndings, foreign body type and localization, radiologic fndings and treatments.Results:Three hundred ffty one of the patients were male (51%) and 342 patients were female (49%). All patients underwent rigid bronchoscopy procedure except six patients. Foreign bodies were found in 589 patients (85%). Mcgill clemp was used for removing of foreign bodies settled on vocal cords in six patients and subsequently, rigid bronchoscopy was performed for checking of tracheobronchial system. Thoracotomy was required in four patients (0.7%). The most common foreign bodies were nuts (n=373). The most frequent localization site of foreign bodies was right bronchial system (n=292). The chief radiologic fnding was obstructive emphysema (n=296). Cardiopulmonary arrest occurred in 11 patients and 2 of them died (0,3%).Conclusions:The gold standard in diagnosis and management of tracheobronchial foreign body aspiration is bronchoscopy, which can be performed with a low complication rate.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.296
Teacher spread0.279 · 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
Published2016
Admission routes1
Has abstractyes

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