Nurse-Driven Clinical Pathway for Inpatient Asthma: A Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: We examined the impact of a nurse-driven clinical pathway on length of stay (LOS) for children hospitalized with asthma. METHODS: We conducted a randomized controlled trial involving children hospitalized with asthma. Nurses of children in the intervention group weaned salbutamol frequency using an asthma scoring tool, whereas physicians weaned salbutamol frequency for the control group patients as per standard care. The primary outcome was LOS in hours. Secondary outcomes included number of salbutamol treatments administered, ICU transfers, unplanned medical visits postdischarge, and stakeholders' pathway satisfaction. Research staff, investigators, and statisticians were blinded to group assignment, except for research assistants enrolling participants. Qualitative interviews were done to assess acceptability of intervention by physicians, nurses, residents, and patients. RESULTS: = .11), for the control and intervention groups, respectively. A post hoc analysis designed to deal with highly skewed LOS data resulted in a relative 18% (95% confidence interval 0.68-0.99) LOS reduction for the intervention group. There was no difference in secondary outcomes. No significant adverse events resulted from the intervention. The 14 participants included in the qualitative component reported a positive experience with the pathway. CONCLUSIONS: This nurse-driven pathway led to increased efficiency as evidenced by a modest LOS reduction. It allowed for care standardization, improved utilization of nursing resources, and high stakeholder satisfaction.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".