End-of-life care in Brazilian Pediatric Intensive Care Units
Bibliographic record
Abstract
OBJECTIVE: Most deaths in Pediatric Intensive Care Units involve forgoing life-sustaining treatment. Such deaths required carefully planned end-of-life care built on compassion and focused on palliative care measures. This study aims to assess topics related to the end of life care in Brazilian pediatric intensive care units from the perspective of a multidisciplinary team. METHOD: The authors used a tested questionnaire, utilizing Likert-style and open-ended questions. After ethics committee approval, it was sent by email from September to November/2019 to three Pediatric Intensive Care Units in the South and Southeast of Brazil. One unit was exclusively dedicated to oncology patients; the others were mixed units. RESULTS: From 144 surveys collected (23% response rate) 136 were analyzed, with 35% physicians, 30% nurses, 21% nurse technicians, and 14% physiotherapists responding. Overall, only 12% reported enough end-of-life care training and 40% reported never having had any, albeit this was not associated with the physician's confidence in forgoing life-sustaining treatment. Furthermore, 60% of physicians and 46% of other professionals were more comfortable with non-escalation than withdrawing therapies, even if this could prolong suffering. All physicians were uncomfortable with palliative extubation; 15% of all professionals have witnessed it. The oncologic team uniquely felt that "resistance from the teams of specialists" was the main barrier to end-of-life care implementation. CONCLUSION: Most professionals felt unprepared to forego life-sustaining treatment. Even for terminally ill patients, withholding is preferred over the withdrawal of treatment. Socio-cultural barriers and the lack of adequate training may be contributing to insecurity in the care of terminally ill patients, diverging from practices in other countries.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".