A Common Health Problem in Children: Tracheobronchial Foreign Body Aspirations
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".