Assessing physical and respiratory distress in children with bronchiolitis admitted to a community hospital emergency department: A retrospective chart review
Bibliographic record
Abstract
Introduction: Bronchiolitis is a leading cause of infant hospitalization with wide variation in its diagnosis and management, especially in smaller community hospitals.The objective of this study is to describe children admitted to a community-based hospital emergency department (ED) for bronchiolitis and explore alternate assessments of illness severity.Methods: A retrospective chart review (January to September 2014) of 100 children, < 2 years old and meeting International Classification of Diseases 10 for bronchiolitis.Outcomes included demographics, symptoms, and interventions.In addition, the Respiratory Distress Assessment Instrument (RDAI) score was calculated using documented assessments of wheezing and retractions.Descriptive and comparative statistics were completed with p < 0.05 considered significant.Results: The mean (standard deviation) age 10.6 (8.4) months, n = 41 females.Sixty-seven percent had a chest X-ray (CXR), 17% oral antibiotics, 65% bronchodilators, and 19% oral steroids; 19% were admitted in hospital.There was a significant difference in RDAI score between those given oral antibiotics (mean (95% CI), 6.35 (4.96-7.75))versus not (4.70 (4.20-5.20)),p = 0.01.Those who received a CXR had a significantly higher oxygen flowrate (1.4 (0.6-2.1) litres per minute (lpm)) and worse physical appearance (tri-pod position, head bobbing) versus those who did not (0.15 (-0.05 to 0.35) lpm), p = 0.002 and p = 0.04, respectively.Conclusions: A large number of children admitted to a community-based ED for bronchiolitis received unnecessary CXR and medications.Assessing physical and respiratory distress may be more effective at determining illness severity compared with radiological or laboratory testing.Local clinical practice guidelines may aid in optimal management of bronchiolitis for community-based EDs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".