Pharmacotherapy in Critically Ill Children: A Retrospective Review of 17,199 Admissions
Bibliographic record
Abstract
OBJECTIVES: Despite the ubiquitous role of pharmacotherapy in the care of critically ill children, descriptions of the extent of pharmacotherapy in critical illness are limited. Greater understanding of drug therapy can help identify clinically important associations and assist in the prioritization of efforts to address knowledge gaps. The objectives of this study were to describe the diversity, volume, and patterns of pharmacotherapy in critically ill children. DESIGN: A retrospective cohort study was performed with patient admissions to the ICU between July 31, 2006, and July 31, 2015. SETTING: The study took place at a single, free-standing, pediatric, quaternary center. PATIENTS: Eligible patient admissions were admitted to the ICU for more than 6 hours and received one or more drug administration. There were a total 17,482 patient-admissions and after exclusion of 283 admissions (2%) with no documented enteral or parenteral drug administration, 17,199 eligible admissions were studied. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The 17,199 eligible admissions were admitted to the ICU for 2,208,475 hours and received 515 different drugs. The 1,954,171 administrations were 894,709 (45%) enteral administrations, 998,490 (51%) IV injections and 60,972 (3%) infusions. Infusions were administered for 4,476,538 hours. Twelve-thousand two-hundred seventy-three patients (71%) were administered five or more different drugs on 80,943 of patient days (75%). The 10 most commonly administered drugs comprised of 834,441 administrations (43%). CONCLUSIONS: Drug administration in the ICU is complex, involves many medications, and the potential for drug interaction and reaction is compounded by the volume and diversity of therapies routinely provided in ICU. Further evaluation of polytherapy could be used to improve outcomes and enhance the safety of pharmacotherapy in critically ill children.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".