The elements of end-of-life care provision in paediatric intensive care units: a systematic integrative review
Bibliographic record
Abstract
BACKGROUND: Deaths in paediatric intensive care units (PICUs) are not uncommon. End-of-life care in PICUs is generally considered more challenging than other settings since it is framed within a context where care is focused on curative or life-sustaining treatments for children who are seriously ill. This review aimed to identify and synthesise literature related to the essential elements in the provision of end-of-life care in the PICU from the perspectives of both healthcare professionals (HCPs) and families. METHODS: A systematic integrative review was conducted by searching EMBASE, CINAHL, MEDLINE, Nursing and Allied Health Database, PsycINFO, Scopus, Web of Science, and Google Scholar databases. Grey literature was searched via Electronic Theses Online Service (EthOS), OpenGrey, Grey literature report. Additionally, hand searches were performed by checking the reference lists of all included papers. Inclusion and exclusion criteria were used to screen retrieved papers by two reviewers independently. The findings were analysed using a constant comparative method. RESULTS: Twenty-one studies met the inclusion criteria. Three elements in end-of-life care provision for children in the PICUs were identified: 1) Assessment of entering the end-of-life stage; 2) Discussion with parents and decision making; 3) End of life care processes, including care provided during the dying phase, care provided at the time of death, and care provided after death. CONCLUSION: The focus of end-of-life care in PICUs varies depending on HCPs' and families' preferences, at different stages such as during the dying phase, at the time of death, and after the child died. Tailoring end-of-life care to families' beliefs and rituals was acknowledged as important by PICU HCPs. This review also emphasises the importance of HCPs collaborating to provide the optimum end-of-life care in the PICU and involving a palliative care team in end-of-life care.
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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 | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".