Trends in Neuropharmacological Medications Over Time in Mechanically Ventilated Nonsurgical Patients Aged Younger Than 3 Years
Bibliographic record
Abstract
OBJECTIVE: Children who require mechanical ventilation (MV) often receive neuropharmacological agents for analgosedation, although the US Food & Drug Administration has warned that some agents may be neurotoxic in young children. We have previously reported concurrent increases in neuropharmacological agent prescription and usage of rehabilitative services in children with bronchiolitis who received MV. We now aim to assess for similar trends in a more heterogeneous population. METHODS: With institutional review board approval, we queried the Pediatric Health Information Systems (PHIS) database for children aged younger than 36 months with receipt of MV for at least 2 days between 2006 and 2020 and (nonneonatal) intensive care unit admission. Surgical patients were identified by operating room charges and were excluded. Data extracted included demographics, neuropharmacological agents prescribed for at least 2 days, billing for services that evaluate and treat neurological morbidity (eg, physical therapy, swallow evaluation), and clinical outcomes. Temporal trends were analyzed using simple linear regression, Kruskal-Wallis rank-sum testing was used to compare years, and P < .01 defined statistical significance. RESULTS: Among 52 633 patients, the median (IQR) age was 0.4 (0.1-1.2) years, and 56.9% were male. The proportion of children prescribed at least 5 different drugs/drug classes increased significantly from 29.8% in 2006 to 42.4% in 2020. Drugs with significantly increased prescription from 2006 to 2020, respectively, included antipsychotics (1.2% to 6.1%), clonidine (2.4% to 22.1%), dexmedetomidine (4.2% to 57.1%), ketamine (7.9% to 17.0%), methadone (18.5% to 20.7%), and propofol (4.1% to 9.7%). Drugs with significantly decreased prescription included chloral hydrate (18.8% to 3.3%), midazolam (71.6% to 51.1%), and pentobarbital (5.8% to 1.7%). Usage of at least 2 morbidity-related services significantly increased (24.5% in 2006 to 60.6% in 2020). Mortality decreased significantly (12.5% in 2006 to 10.2% in 2020). CONCLUSIONS: Among young, nonsurgical pediatric intensive care unit patients who received MV, there have been concurrent increases in prescription of several neuropharmacological agents and services related to neurologic morbidity. Prospective studies are needed to evaluate the causes and effects of these changes in practice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".