Paediatric death after withdrawal of life-sustaining therapies: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: The physiology of dying after withdrawal of life-sustaining measures (WLSM) is not well described in children. This lack of knowledge makes predicting the duration of the dying process difficult. For families, not knowing this process's duration interferes with planning of rituals related to dying, travel for distant relatives and emotional strain during the wait for death. Time-to-death also impacts end-of-life care and determines whether a child will be eligible for donation after circulatory determination of death. This scoping review will summarise the current literature about what is known about the dying process in children after WLSM in paediatric intensive care units (PICUs). METHODS AND ANALYSIS: This review will use Joanna Briggs Institute methodology for scoping reviews. Databases searched will include Ovid MEDLINE, Ovid Embase, Cochrane Central Register of Controlled Trials via EBM Reviews Ovid, Ovid PsycINFO, CINAHL and Web of Science. Literature reporting on the physiology of dying process after WLSM, or tools that predict time of death in children after WLSM among children aged 0-18 years in PICUs worldwide will be considered. Literature describing the impact of prediction or timing of death after WLSM on families, healthcare workers and the organ donation process will also be included. Quantitative and qualitative studies will be evaluated. Two independent reviewers will screen references by title and abstract, and then by full text, and complete data extraction and analysis. ETHICS AND DISSEMINATION: The review uses published data and does not require ethics review. Review results will be published in a peer-reviewed scientific journal.
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 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 | 0.074 | 0.066 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.018 | 0.013 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.091 | 0.015 |
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".