P0452 / #926: CARE OF THE DYING CHILDREN AND THEIR FAMILIES IN BRAZILIAN PICUS: ARE WE DOING WHAT WE CAN?
Bibliographic record
Abstract
Aims & Objectives: Care of the dying child involves alleviating suffering, compassion and memory building. We aimed to survey Brazilian PICU teams about the current End of Life (EoL) approaches, examining if common procedures performed elsewhere are feasible or applied in their country. Methods: A survey tested beforehand, containing Likert style answers and few open questions, was sent via email to professionals in 3 PICUs in Brazil’s center-south hospitals (A.Private, B.Public and a C.University Oncology) as a pilot study. Institutional ethics committees, Gov. research registry, and individual consent were obtained. During the 3 months (09-11/2019), 3 reminders were sent. Few open questions were applied, and a thematic analysis was taken. Results: Overall, 136 surveys returned (response rate: 23% total; Physicians: A.31%, B.25% and C.60%), Overall 35% Physicians, 31% Nurses, 20% Nurses technicians and 14% Physiotherapists responded. The majority (80%) felt that having parents present or holding the child while treatment withdrawal is performed is feasible, even though only 15% have witnessed terminal extubation. Over 85% feel comfortable medicating for comfort at EoL, with opioids and benzodiapenics (98%), but 8% added a paralytic drug in the combo. After the child’s death, 47% agree/somewhat agree that meeting the family is important; 52% agree/somewhat agree that sending a condolence’s letter is important, but only 13% had done it; 15% have organized memorial celebrations for the children. Conclusions: Many common practices at EoL are accepted but not performed consistently in the Brazilian PICUs. Further studies are needed to ascertain the reasons behind these findings and perhaps education may be necessary.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".