Fluid and drug administration in a paediatric critical care: prospective, single centre, multimodal, direct observational study
Bibliographic record
Abstract
Abstract Critically ill children are intensively monitored and receive many drugs, fluids, and other therapies while in paediatric intensive care unit(PICU). The operational aspects of the provision of these therapies are not well understood. The objective of this study was to characterise the activities supporting fluid and drug administration in critically ill paediatric patients. This prospective, single centre, observational study used multi-modal direct observation approach (video, audio, and direct bedside observation) to understand the clinical activities associated with care of critically ill children. Administration was separated into the broad and varied activities required for drug and fluid administration ranging from drug information review through disposal. 43 patients, 84 nurses, 43 doctors, 27 respiratory therapists and 4 nurse practitioners were observed over 48 epochs and 143.15 h. The 23.61(16%) hours of drug and fluid therapy observed were comprised of 660 specific clinical administrations of drug and fluid therapy that took a median(IQR) 64.45(17.10–163.62) seconds and were comprised of 4396 administration activities. Interruptions to the process of drug and fluid administration were also counted and observed 261 times, occurring in 148(22%) of unique administrations and lasted a median(IQR) of 7.95(3.82–14.88) seconds each. This study has implications on safety measures pertaining to sources and duration of interruptions within administration, as well as considerations around nursing tasks, ratios and sheer workload of drug and fluid administration. Further work could explore targeting strategies that optimize efficiency, workflow, and safety in the PICU as it pertains to layout, staffing and ease of medication administration.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".