Delirium in Children Undergoing Hematopoietic Cell Transplantation: A Multi-Institutional Point Prevalence Study
Bibliographic record
Abstract
Introduction: Delirium occurs frequently in adults undergoing hematopoietic cell transplantation, with significant associated morbidity. Little is known about the burden of delirium in children in the peri-transplant period. This study was designed to determine delirium rates, define risk factors (demographic and treatment related), and establish feasibility of multi-institutional bedside screening for delirium in children undergoing hematopoietic cell transplant. Methods: This is a multi-institutional point prevalence study. All subjects were prospectively screened for delirium twice daily using the Cornell Assessment of Pediatric Delirium over a 10-day period. De-identified data, including basic demographics and daily characteristics, were extracted from the electronic medical record. Results: Eleven North American institutions were included, 106 children were enrolled, and 883 hospital days were captured. Delirium screening was successfully completed on more than 98% of the study days. Forty-eight children (45%) developed delirium over the course of the 10-day study. Children were diagnosed with delirium on 161/883 study days, for an overall delirium rate of 18% per day. Higher delirium rates were noted in children <5 years old (aOR 0.41 for children over 5 years), and in association with specific medications (melatonin, steroids, and tacrolimus). Conclusion: Delirium was a frequent occurrence in our study cohort, with identifiable risk factors. Delirium screening is highly feasible in the pediatric hematopoietic cell transplant patient population. A large-scale prospective longitudinal study following children throughout their transplant course is urgently needed to fully describe the epidemiology of pediatric delirium, explore the effects of delirium on patient outcomes, and establish guidelines to prevent and treat delirium in the peri-transplant period.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".