Potassium disturbance associated with an inpatient childhood asthma pathway
Bibliographic record
Abstract
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 Retrospective cohort study using visit-level electronic medical data. Inpatients aged <18 years old receiving salbutamol via the ACAP with at least one potassium level were included. Hypokalemia was defined as mild (3.0 ≤ [K+] < 3.5 mEq/L), moderate (2.5 ≤ [K+] < 3.0 mEq/L), or severe ([K+] < 2.5 mEq/L), as measured in serum or blood gas. Binomial logistic regression was utilized to examine risk factors for hypokalemia, route of administration, location of lowest [K+], 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".