Impact of environmental tobacco smoke on children admitted with status asthmaticus in the pediatric intensive care unit
Bibliographic record
Abstract
INTRODUCTION: Environmental tobacco smoke (ETS) and allergens are risk factors in children with critical status asthmaticus. Genetic studies support that ETS-associated asthma is a special inflammatory entity, causing significant number of hospital admissions and relapses. Accordingly, the course and outcome of patients with ETS-induced status asthmaticus might also be different. HYPOTHESIS: We hypothesized that the progression, course, and outcome of patients with ETS-induced status asthmaticus would be worse than those of patients without ETS exposure. METHODS: Medical records of children who were admitted to the Pediatric Intensive Care Unit (PICU) with the diagnosis of asthma at the Children's Hospital of Winnipeg, Manitoba, over 10 years were audited after Institutional Review Board (IRB) approval. Two hundred thirty records were reviewed. We extracted data including demographics and analyzed the patient's deterioration defined as clinical asthma score (CAS) drift between the ED and PICU. We computed the treatment response, expressed as length of stay (LOS) in the PICU and in hospital. The risk factors were stratified as none, ETS exposure, allergies, and ETS with allergies. RESULTS: There were 55 (25%) patients with no risk factors, 66 (30%) with ETS exposure only, 46 (21%) with allergies only, and 53 (24%) with both. There was a 25% decrease in CAS deterioration when patients were exposed to ETS (P < 0.05). For patients with or without allergies but with exposure to ETS, both the PICU and overall hospital LOS were ∼15% longer (P < 0.05) than for those not exposed to ETS. Stratifying for gender and race in multivariate analysis did not alter the results. CONCLUSIONS: Patients with ETS-associated critical status asthmaticus deteriorate and recover slower than non-ETS-exposed patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".