Pediatric Decontamination Considerations in CBRN Events: A Scoping Review
Bibliographic record
Abstract
INTRODUCTION: Children are uniquely vulnerable to chemical, biological, radiological, and nuclear (CBRN) events due to anatomical, physiological, and psychological differences. Current decontamination practices are adapted from adult protocols. OBJECTIVE: To evaluate current practices, challenges, and special considerations in pediatric decontamination during CBRN events. METHOD: A scoping review was conducted using six databases in accordance with PRISMA-ScR framework. Studies were eligible if they evaluated decontamination methods involving children (0-18 years) in real or simulated CBRN scenarios. Fourteen studies met the inclusion criteria, and data were thematically analyzed into four domains. RESULTS: Disrobing is widely recognized as a critical first step in the decontamination process, and 43% of the studies reviewed identified it as such. When done immediately and appropriately, it can remove a significant amount of contaminants. Although its effectiveness varies based on how much of the body is covered and the nature of the exposure. Dry decontamination was discussed in 21% of studies, and wet decontamination was the most commonly reported approach, appearing in 93%. Key pediatric challenges included hypothermia, psychological distress, separation from caregivers, and difficulties managing non-ambulatory or special needs populations. Few studies addressed age-specific protocols or long-term psychological impacts. The results are presented in procedural order to reflect the typical sequence of decontamination in CBRN response. CONCLUSIONS: Current decontamination guidelines inadequately address pediatric-specific needs. There is a critical need for standardized, age-appropriate guidelines that integrate caregiver support and psychosocial considerations. A pediatric decontamination algorithm was developed to consolidate current evidence into a practical framework for CBRN mass casualty incidents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".