Ethical, Cultural, Social, and Individual Considerations Prior to Transition to Limitation or Withdrawal of Life-Sustaining Therapies
Bibliographic record
Abstract
As part of the invited supplement on Death and Dying in the PICU, we reviewed ethical, cultural, and social considerations for the bedside healthcare practitioner prior to engaging with children and families in decisions about limiting therapies, withholding, or withdrawing therapies in a PICU. Clarifying beliefs and values is a necessary prerequisite to approaching these conversations. Striving for medical consensus is important. Discussion, reflection, and ethical analysis may determine a range of views that may reasonably be respected if professional disagreements persist. Parental decisional support is recommended and should incorporate their information needs, perceptions of medical uncertainty, child's condition, and their role as a parent. Child's involvement in decision making should be considered, but may not be possible. Culturally attuned care requires early examination of cultural perspectives before misunderstandings or disagreements occur. Societal influences may affect expectations and exploration of such may help frame discussions. Hospital readiness for support of social media campaigns is recommended. Consensus with family on goals of care is ideal as it addresses all parties' moral stance and diminishes the risk for superseding one group's value judgments over another. Engaging additional supportive services early can aid with understanding or resolving disagreement. There is wide variation globally in ethical permissibility, cultural, and societal influences that impact the clinician, child, and parents. Thoughtful consideration to these issues when approaching decisions about limitation or withdrawal of life-sustaining therapies will help to reduce emotional, spiritual, and ethical burdens, minimize misunderstanding for all involved, and maximize high-quality care delivery.
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 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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".