Potassium disturbance associated with an inpatient childhood asthma pathway
Bibliographic record
Abstract
BACKGROUND: Paediatric asthma exacerbations in Alberta are treated via standardized order sets known as the Alberta Acute Childhood Asthma Pathway (ACAP). This pathway is utilized in paediatric tertiary hospitals and in remote and rural locations. Incidence, magnitude, and risk factors for hypokalemia in inpatients receiving salbutamol for asthma exacerbations via this pathway are presently unknown. OBJECTIVE: Establish incidence, magnitude, and risk factors for hypokalemia associated with salbutamol therapy as directed by a paediatric asthma pathway. METHODS: ], nil per os (NPO) status during admission, potassium supplementation, gender, and age. RESULTS: There were 821 patients screened for analysis and 433 patients were analyzed after exclusions. There was an incidence of hypokalemia of 38.8%. Of patients experiencing hypokalemia, 71.4% were mild, 25.6% moderate, and 3.0% severe. Risk factors included nebulized salbutamol, patient location (emergency department or paediatric intensive care unit), and age (>5 years) although these risk factors may actually represent patients receiving higher doses of salbutamol. CONCLUSIONS: The majority of the 38.8% of children experiencing hypokalemia associated with the ACAP were mild. Routine monitoring of potassium status in children receiving salbutamol per standardized pathway is recommended for children with described risk factors, and ideally within the first 12 hours of presentation.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".