Childhood asthma admissions: Determinants of short stay
Bibliographic record
Abstract
The objective of this study was to identify the determinants of short hospital stay (< 24 h) among children admitted because of an acute asthma exacerbation. Computerized health records were used to identify children with a discharge diagnosis of asthma (ICD code 493.0) at the Hospital for Sick Children, Toronto, during the period October 1994 to October 1995. Cases were children with a length of hospital stay of < 24 h (short-stay group) and controls were children with a length of stay of > 24 h (long-stay group). Clinical and demographic data were extracted from the medical record. Over the 12-month period, 485 children were hospitalized because of asthma. Of these, 121 (25%) had short-stay admissions (< 24 h), whereas 364 (75%) had long-stay admissions (> 24 h). Simple random sampling was used to select 85 children from each of the two groups. There were no differences between the two groups regarding language, primary care physician, asthma history, management prior to emergency department (ED) presentation, respiratory rate on presentation, use of the observation unit, and time in the ED. Logistic regression analyses identified three variables associated with short hospital stay: milder asthma (adjusted odds ratio [OR] 4.9), male gender (adjusted OR 2.4), and availability of a delivery device at home (adjusted OR 2.0). In conclusion, many children admitted to hospital because of an asthma exacerbation have short, yet expensive, hospital stays. The results of this study highlight the importance of developing alternative models of health care delivery for asthmatic children requiring short hospital contact.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".